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, 

The Evolution of 

Mobile Teaching 

and Learning 

• 

, 

# t 

Retta Guy 

Digitized by Coogle


Mobile Teaching and 

Learning 

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Digitized by Google


Mobile Teaching and 


Edited by 

Retta Guy 

Informing Science Press 

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The Evolution of Mobile Teaching and Learning 

Copyright © 2009 Informing Science Press 

All rights reserved. Permission to make digital or paper copy of part or 

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ISBN: 978-1932886-14-6 

Published by 

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This book is dedicated to ... 

James Henry Sweat 

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Acknowledgements 

The following book benefited from the insights and direction of several 

people. First, lowe an immeasurable debt of gratitude to Eli Cohen 

and Betty Boyd for their direction and creative energies from the very 

start. Secondly, I want to personally thank all of the authors as well as 

the reviewers for their efforts in ensuring a quality publication that 

addresses education using cutting-edge technology. Above all, I want 

to thank God for His continued blessings and guidance. 

R. G. 

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Guy, R (Ed.). (2009). 

The Evolution r!f Mobile Teaching and Learning. 

Santa Rosa, California: Infonning Science Press. 


Mobile Teaching and Learning 

Contents 

Preface: 

Section 1 

Chapter 1: 

Chapter 2: 

Chapter 3: 

Chapter 4: 

Section 2 

Chapter 5: 

Chapter 6: 

.......................................................................................... zx 

Defining Mobile Learning 

The Evolution of Mobile Learning 

John Traxler ............................................................. 1 

Mobile Learning DeMystified 

James Kadirire .......................................................... 1 5 

Selecting Appropriate Technologies for Mobile 

Teaching and Learning 

Jerenry Dickerson and J. B. Browning ....................... 57 

From Classical Mobile Learning to Mobile Web 

2.0 Learning 

Chaka Chaka .......................................................... 79 

Pilots, Projects, and Trials 

M-Learning Adoption in Brazil 

Amarolinda I.c.z. Sacco!, Eliane Schlemmer, Jor;ge L 

V. Barbosa, Nicolau Reinhard, and Carolina Sarmento 

.................................................................................. 103 

Mobile and Pervasive Computing in a Computer 

Engineering Undergraduate Course 

Jor;ge Barbosa, Rodrigo Hahn, Debora Barbosa and 

William Segato .......................................................... 119 

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Chapter 7: 

A Short-Term Trial Documenting Students' 

Perceptions. Attitudes. and Experiences with 

Mobile Learning 

Retta GI!)I ................................................................. 141 

Chapter 8: Design and Assessment of E-Learning and M- 

Learning Tools for the Degree in Actuarial 

Sciences 

Mana Cruz Mqyorga-Toledano and Antonio Fernandez- 

Morales ..................................................................... 159 

Chapter 9: 

Understanding User Experience to Support 

Learning for Mobile Journalist's Work 

Heli Viiiitiijii, Anssi Mannistii, Teija Vainio and Tero 

Jokela ........................................................................ 177 

Section 3 

Chapter 10: 

Chapter 11: 

Chapter 12: 

The Assessment and Future of Mobile 


Measuring Quality of M-Learning Information 

Systems 

Ruti Gqfni ................................................................ 211 

Evaluation of Mobile Learning Contents and 

Mobile Services and Applications 

Gianna At,ellis .......................................................... 249 

The Future of Mobile Learning: The Paradigm 

Pioneers of Pedagogy 

Craig Wishart ........................................................... 271 

Reviewers ................................................................................. 291 

Index ......................................................................................... 293 

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Guy, R (Ed.). (2009). 


Santa Rosa, California: Infonning Science Press. 

Preface 

The information era in which we currently live is changing the culture 

of education. The use of information technologies has resulted in new 

opportunities that are rapidly growing to include mobile learning: an 

evolution of distance learning characterized as a paradigm shift from 

d-Iearning (distance) to e-Iearning (electronic) to m-Iearning (mobile). 

Deftnitions and conceptualizations that deftne this form of education in 

terms of technologies and learner experiences can be described as a 

learning environment inclusive of course content and materials, student 

support services, Internet, and communication. Mobile, wireless, and 

handheld technologies are being used to re-enact approaches and solutions 

to teaching and learning used in traditional and web-based formats. 

This book encompasses three distinctive divisions which include: 

(1) detailed deftnitions of mobile learning while providing an analytical 

and theoretical background of distance education; (2) results of pilots, 

projects, and trials relevant to the use of mobile teaching and learning; 

and (3) the assessment and future of mobile education. 

It is my intent that this book will engage university and college educators, 

secondary school administrators and teachers, pre-service teacher 

education candidates, and corporate trainers interested in instructional 

design using technology. The book will take the reader through technologies 

available while "on the move" and will serve as a resource for 

designing and developing the mobile environment for education. 

Dr. Retta Guy 

Associate Professor 

Tennessee State University 

January 2009 

ix 

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Guy, R (Ed.). (2009). 


Santa Rosa, California: Infonning Science Press. (pp. 1-14). 

Chapter 1 

The Evolution of Mobile Learning 

John Traxler 

Introduction 

This is an account of the evolution of mobile learning, an account from 

a long-time protagonist, seen perhaps from a relatively personal and 

partial perspective. Clearly we need to deftne what we mean by 'mobile 

learning', not merely as a way of establishing a shared understanding 

but also as a way of exploring the evolution and direction of mobile 

learning. In discussing how we define mobile learning we address many 

wider issues in terms of explaining, understanding and conceptualizing 

it. 

'M:obile learning' is certainly not merely the conjunction of 'mobile' and 

'learning'. For a start, it has always been automatically taken to mean 

'mobile e-Iearning' and its history and development have to be understood 

as both a continuation of 'conventional' e-Iearning and also a 

reaction to this 'conventional' e-Iearning and to its perceived inadequacies 

and limitations. Over the last ten or so years this 'conventional' e 

learning has been exemplified technologically by the rise of virtual 

learning environments (VLEs) and the demise of CAL (computer assisted 

learning) 'packages' and pedagogically by the rise of social constructivist 

models of learning over the behaviorist ones, by the growth 

of the learning object approach, by expectations of ever increasing 

multi-media interactivity and of ever-increasing power, speed, functionality, 

and bandwidth in networked PC platforms. These are thus some 

of the defining points of departure for mobile learning, though perhaps 

seeing mobile learning in these terms, that is by referring back to 'conventional' 

e-Iearning, is the mark of early 'mobile learning immigrants' 

and not the mark of the growing number of 'mobile learning natives'. 

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This account is of course only really accurate for work in Europe, 

North America, and East Asia. In parts of southern Africa, for example, 

the term 'mobile learning' is recognized but is grafted onto a tradition 

of open and distance learning (ODL) and on to different pedagogic 

traditions, ones that have occasionally been called 'instructivist' 

and have concentrated on didactic approaches, not on discursive ones. 

Mobile learning in these parts of the world is a reaction to different 

challenges and different limitations, usually those of infrastructure, 

poverty, distance, or sparsity, issues to which we return later. 

In either case, we have to recognize that attempts at identifying and 

defining mobile learning grow out of difference, out of attempts by 

emergent communities to separate themselves from some older and 

more established communities and move on from perceived inadequate 

practices. Interestingly, at the first mLearn conference in the spring of 

2002, a workshop for a handful of delegates organized by Professor 

Mike Sharples in Birmingham, a key-note speaker predicted mobile 

learning would have a separate identity for perhaps five years before 

blending into general e-Iearning. This has yet to happen and mobile 

learning continues to gain identity and definition rather than lose them. 

Irrespective of the exact definition, mobile and wireless technologies, 

including handheld computers, personal digital assistants (PDAs), camera-phones, 

smartphones, graphing calculators, personal response systems 

(PRSs), games consoles, and personal media players, are becoming 

ubiquitous in most parts of the world and have led to the development 

of 'mobile learning' as a distinctive but ill-defined entity (see for example 

the reviews by Cobcroft, 2006, and Naismith et al., 2004). 

Easy Definitions 

Early approaches at defining mobile learning focused on technology, 

for example, saying it was "any educational provision where the sole or 

dominant technologies are handheld or palmtop devices" (Traxler, 

2005), or on the mobility of the technology, describing mobile learning 

as "elearning through mobile computational devices: Palms, Windows 

CE machines, even your digital cell phone" (Quinn, 2000). Another 

view of mobile learning says it involves "any sort of learning that happens 

when the learner is not at a fixed, predetermined location, or 

learning that happens when the learner takes advantage of learning 

opportunities offered by mobile technologies" (O'Malley et al., 2003), 

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The Evolution,!! Mobile Learning 

whilst Desmond Keegan took a similar position in 2005, saying, "1 feel 

that in the definition of mobile learning the focus should be on mobility. 

Mobile learning should be restricted to learning on devices which a 

lady can carry in her handbag or a gentleman can carry in his pocket. 1 

therefore define mobile learning as 'the provision of education and 

trammg on PDAs/palmtops/handhelds, smartphones and mobile 

phones.' One of the characteristics of mobile learning is that it uses 

devices: 

• 

• 

• 

• 

which citizens are used to carrying everywhere with them, 

which they regard as friendly and personal devices, 

which are cheap and easy to use, 

which they use constantly in all walks of life and in a variety of 

different settings, except education." (Keegan, 2005:3) 

The MoLeNET initiative, a £6m multi-project initiative across the UK 

vocational sector, still takes this approach, defming mobile learning as 

"exploitation of ubiquitous handheld hardware, wireless networking 

and mobile telephony to enhance and extend the reach of teaching and 

learning" (MoLeNET, 2007). 

These earlier definitions were too technocentric and imprecise. Owing 

to the transience and diversity of the devices, systems, and platforms, 

these defmitions are also highly unstable. They merely put mobile learning 

somewhere on e-Ieaming's spectrum of portability (ending perhaps 

in ubiquitous, pervasive, and wearable learning). Furthermore, whilst 

these attempts at defmition use specific technical attributes to consolidate 

a definition of mobile learning in order to help us reason about it, 

other technical attributes, notably connectivity, usability, and latency, 

have the very opposite effect and disrupt the notion that there is such a 

thing as mobile learning as an artifact of mobile technologies. The uncertainty 

about whether laptops and Tablets deliver mobile learning - 

because of the lack of spontaneity in carrying them and starting them 

up - illustrates the difficulty with this kind of definition. They do however 

hint at the underlying challenge, that of conceptualizing mobile 

learning in a way that recognizes its origins and practices in specific 

technological systems but is abstract enough to be durable and abstract 

enough to act as a stable platform for theorizing about education and 

about learning. 

However, mobile learning, however defmed, is now sufficiently mature 

and varied to have a major textbook (Kukulska-Hulme & Traxler, 

2005) and a second one focusing on a distinctly American perspective 

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(M:etcalf, 2006). It has some newly created journals, including an International 

Journal of Mobile and Blended Learning and a number of 

prestigious international conference series (most obviously, IADIS 

Mobile Learning in Europe, mLearn the global leader, the IEEE's 

WMTE workshop in Asia Pacific and Handheld Learning in Great 

Britain). It has greater clarity about the significant issues (see for example 

Sharples, 2006, defming the 'big issues,), a more sharply defmed 

research agenda (see for example, Arnedillo-Sanchez et al., 2007) and, 

most importantly, has established that the mobile learning community 

can: 

• 

• 

Take learning to individuals, communities and countries that 

were previously too remote, socially or geographically, for 

other types of educational initiative. The m-Iearning project 

in Europe (www.mlearning.org) and now the MobilED 

project m South Africa 

(http://mobiled.uiah.fi/?page_id=2) are two of the best 

examples. 

Enhance and enrich the concept and activity of learning, beyond 

earlier conceptions of learning. The MobiLearn project 

in Europe (www.mobilearn.org) is a good example of 

this achievement. 

There are still the significant challenges of scale, sustainability, inclusion, 

and equity in all their different forms in the future, of context and 

personalization in all their possibilities, of blending with other established 

and emerging educational technologies, and of tracking the 

changes in technology. There is also the challenge of developing the 

substantial and credible evidence-base that will justify further research 

and development. These challenges will further shape our understanding 

of mobile learning. It is probably the case to date that these developments 

in mobile learning have often been driven by pedagogic necessity, 

technological innovation, funding opportunity, and the perceived 

inadequacies of conventional e-Iearning and have perhaps 

worked within relatively narrow educational discourses, those between 

technologists and educationalists. (See Traxler & Kukulska-Hulme, 

2005 and Kukulska-Hulme & Traxler, 2007, for analyses of a sample of 

these developments.) The current book may help a more balanced perspective. 

More recent mobile learning publications (Kukulska-Hulme et al., 2005; 

JISC, 2005), and conference proceedings (for example, Attewell & 

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Savill-Smith, 2004) have put case studies (and their evaluations) into the 

public domain. In looking at these, Kukulska-Hulme and Traxler (2007) 

see emergent categories, and these may attack the problem of what 

constitutes mobile learning from a different direction: 

• Technology-driven mobile learning - a specific technological 

innovation is deployed to demonstrate technical feasibility 

and pedagogic possibility, perhaps the new iPhone. 

• Miniature but portable e-Iearning - mobile, wireless and 

handheld technologies are used to re-enact approaches and 

solutions found in 'conventional' e-Iearning, perhaps porting 

an established e-Iearning technology such as a VLE 

onto mobile devices. 

• Connected classroom learning - the same technologies are 

used in a class-room settings to supported static collaborative 

learning perhaps connected to other classroom technologies; 

personal response systems, graphing calculators, 

PDAs linked to interactive whiteboards. 

• Mobile training and performance support - the technologies 

are used to improve the productivity and efficiency of mobile 

workers by delivering information and support just-intime 

and in context for their immediate priorities, roles, 

and duties. 

• Large-Scale Implementation - the deployment of mobile technologies 

at an institutional or departmental level to learn 

about organizational issues, for example MELaS 

(www.wlv.ac.uk/celt/MELaS) funded by JISC in the UK. 

• Inclusion, assistivity and diversity - using assorted mobile and 

wireless technologies to enhance wider educational access 

and participation, for example personal information management 

for students with dyslexia. 

• Informal, personalized, situated mobile learning - the same 

core technologies are enhanced with additional unique 

functionality, for example, location-awareness or videocapture, 

and deployed to deliver educational experiences 

that would otherwise difficult or impossible; informal context-aware 

information in museum spaces. 

• Remote, rural and development mobile learning - the technologies 

are used to address environmental and infrastructural 

hurdles to delivering and supporting education where 

'conventional' e-Iearning technologies would fail; for ex- 

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ample, SMS forums for trainee pnmary teachers Kenya 

(f raxler, 2006). 

This classification is not purely theoretical or semantic. It has implications 

for the objectives and methods of evaluation and for the techniques 

and objectives for implementation; it may also imply the presence 

or lack of rather different models of pedagogy and learning and it 

is possible that the American 'take' on mobile learning is rather different 

from the European 'take', emphasizing the connected classroom 

and corporate mobile training rather than situated informal learning. 

These may be innovative or conservative technically or pedagogically by 

virtue of their place in the classification. Of course this attempt to define 

mobile learning by making instances - definition by denotation - is 

potentially problematic since in choosing the instances we create a circular 

definition but it is, nevertheless, taking us a bit further forward. 

Niall Winters (2006) provides a similar taxonomy which gives us an 

additional perspective on what might characterize different types of 

mobile learning, saying, "Current perspectives on mobile learning generally 

fall into the following four broad categories: 

• Technocentric. This perspective dominates the literature 

............... 

• Relationship to e-Ieaming. This perspective characterizes mobile 

learning as an extension of e-Ieaming ............ 

• Augmenting formal education ......... . 

• Learner-centered ...." 

And this echoes the earlier points. 

Another classification of mobile learning that might help us towards a 

definition is due to Naismith et al. (2004) who suggest that mobile 

technologies can relate to six types of learning, or "categories of activity": 

namely, behaviorist, constructivist, situated, collaborative, informal/lifelong, 

and support/coordination. The mobile learning may be 

manifest in the following ways: 

• For behaviorist-type activity, it is the quick feedback or reinforcement 

element, facilitated by mobile devices, that is 

most notable. 

• For constructivist activity, mobile devices enable immersive 

experiences such as those provided by mobile investigations 

or games. 

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• For situated activity, learners can take a mobile device out into 

an authentic context or use it while moving around a context-aware 

environment in a specially equipped location 

such as a museum. 

• For collaborative learning, mobile devices provide a handy additional 

means of communication and a portable means of 

electronic information sharing. 

• For informal and lifelong learning, mobile devices accompany 

users in their everyday experiences and become a convenient 

source of information or means of communication 

that assists with learning or records it on the go for future 

consultation. 

• Support, or coordination oflearning and resources, can be improved 

by the availability of mobile technologies at all 

times for monitoring attendance or progress, checking 

schedules and dates, reviewing and managing - activities 

that teachers and learners engage in at numerous times 

during the day. 

An attempt by Sharples, Taylor and Vavoula (2005, p.4) suggested that 

a theory of mobile learning should be assessed against the following 

criteria; this was in effect their perspective on the defining characteristics 

of mobile learning: 

• Is it significantly different from current theories of classroom, 

workplace or lifelong learning? 

• Does it account for the mobility oflearners? 

• Does it cover both formal and informal learning? 

• Does it theorize learning as a constructive and social process? 

• Does it analyze learning as a personal and situated activity mediated 

by technology? 

Whilst Ann J ones a ones et aI., 2006) makes a similar contribution 

based on the motivational or affective aspects of mobile learning as 

defining characteristics - these are both important in themselves and 

often cited anecdotally as major factors behind decisions to deploy a 

mobile learning strategy. They are: 

• control (over goals) 

• ownership 

• fun 

• communication 

• learning-in -con text 

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• continuity between contexts 

There have also been attempts to define mobile learning and thus to 

distinguish it from 'conventional' or 'tethered' e-Iearning (to use Gilly 

Salmon's telling phrase) in terms of the learners' experiences. One view 

(Traxler, 2006) in looking at the characterizations of mobile learning 

found in the literature (conference proceedings from mLearn and 

WMTE for example) finds words such as 'personal', 'spontaneous', 

'disruptive' 'opportunistic', 'informal', 'pervasive', 'situated', 'private', 

'context-aware', 'bite-sized', and 'portable'. These are contrasted with 

words from the literature of 'conventional' e-Iearning such as 'structured', 

'media-rich', 'broadband', 'interactive', 'intelligent', and 'usable'. 

We can use these to make a blurred distinction between mobile learning 

and 'conventional' e-Iearning. This distinction is, however, not only 

blurred but in part is also only temporary. Many of the virtues of 'conventional' 

e-Iearning are the virtues of the power of its technology (and 

the investment in it) and these virtues will be accessible to mobile devices 

too as market forces drive improvements in memory size, interface 

design, processor speed, battery life, and connectivity bandwidth. 

Nevertheless, this approach underpins a definition of mobile learning in 

terms of the learners' experiences and an emphasis on 'ownership', 

informality, spontaneity, mobility, and context that will always be inaccessible 

to 'conventional' e-Iearning. We should add that the reported 

learner experience of mobile learning may depend on where the specific 

project fits into the earlier taxonomy. 

Theories of Mobile Learning 

The communities cohering around mobile learning may still feel the 

need for a theory of mobile learning as well as a definition, for example, 

because of the ability of theory to deftne a research agenda or produce 

useful predictions and generalizations (although in a postmodern era, 

the role of theory as an informing construct is under threat). Such a 

theory may however be particularly problematic since mobile learning is 

an inherently 'noisy' phenomenon where context is everything and 

confounding variables abound, and if theory is something generated by 

abstracting upwards from practice and experience, then perhaps mobile 

learning has yet to reach the critical mass of experience and practice 

that justify such abstraction and has been too fragmented to justify 

generalizations. The work of Kuhn (1962) on the structure of intellectual 

change provides some insights into the role of 'theory' in relation 

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to the professional activities of researchers (though not one without its 

critics). 

'Conventional' e-Iearning has certainly gained credibility and status 

from the work of, for example, Laurillard (2002) and Salmon (2000) but 

there is currently insufficient work in mobile learning generally to underpin 

much theory building. Theories of 'conventional' e-Iearning rest 

on the experience of stable technology platforms; the apparently dominant 

and enduring nature of Windows, QWERTY, IP, HTML and 

WWW means that theorizing about 'conventional' e-Iearning can take 

place in a technology environment that is consistent, homogeneous, 

and transparent - the technology no longer gets in the way. The technology 

platform upon which mobile learning theory might rest is by 

comparison volatile, inconsistent, and haphazard and so impedes the 

work of understanding mobile learning itself. 

We should also look at the geographical or cultural spread of mobile 

learning and recognize that any theories that attempt to reason about it 

will grow out of the dominant pedagogic discourses of those societies. 

Tactically, we could argue that the mobile learning community in looking 

for theory is - to over-simplify - faced with three different options 

and dilemmas: 

• 

• 

• 

Import theory from 'conventional' e-Iearning and worry about 

transferability; 

Develop theory ab initio locally and worry about validity; 

Subscribe to some much more general and abstract theory and 

worry about specificity and granularity. 

Diana Laurillard's recognition of the impact of mobility and mobile 

technologies on the Conversational Framework (Laurillard, 2007) is an 

example of taking the first option. She discusses the possibilities of 

increasing interaction between the learner and the environment but also 

how problematic or unproductive this might be in informal learning or 

unsupervised learning (for example, in museum spaces) where a teacher 

is neither in a position to set appropriate tasks nor to provide meaningful 

feedback. This is within more general remarks about the use of the 

Conversational Framework to support "a rigorous approach to working 

out how to support all the component learning activities, in remote 

locations, with learners guided only by the tasks set, the information 

available online, the characteristics of the world they are in, and peer 

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support." This is a case of mobile learning looking to challenge and 

extend an accepted e-Iearning theory. 

The emerging theories of 'connectivism' (Siemens, 2004) and 'navigationism' 

(Brown, 2005) are nearer to the second option. People are now 

learning "through communities of practice, personal networks, and 

through completion of work-related tasks" in an environment in which 

"know-how and know-what is being supplemented with know-where 

(the understanding of where to find knowledge needed)" (Siemens, 

2005). This is nearer to the second option. 

Thirdly, it is fair to say that many of the more theoretically inclined 

members of the mobile learning community (see for example Sharples 

et al., 2005) subscribe to versions ofYrjo Engestrom's 'Activity Theory' 

(1987) and this would be the most obvious example of the third option, 

an analysis of much or all purposive human activity. Engestrom and his 

colleagues refer to Activity Theory as a "commonly accepted name for 

a line of theorizing and research initiated by the founders of the cultural-historical 

school of Russian psychology," whilst others (Er & Kay, 

2005) say that the underlying philosophy of the theory is to explain 

human activity and behavior. Learning is analyzed as a culturalhistorical 

activity system, mediated by tools that constrain and support 

the learners in their goals of transforming their knowledge and skills 

and presented in two separate perspectives, or layers, of tool-mediated 

activity. The semiotic layer describes learning as a semiotic system in 

which the leamer's object-oriented-actions are mediated by cultural 

tools and signs. The technological layer represents learning as an engagement 

with technology, in which tools function as interactive agents 

in the process of coming to know. This is not an attempt to explain or 

assess Activity Theory but merely to position it as a very broad and 

relatively abstract account of much more that just learning and technology. 

Finally, to return to the issue of defmition, Josie Taylor (2006) comes at 

it from a high level, seeing the question as whether 'mobile learning' 

signified: 

• Learning mediated by mobile devices, or 

• Mobility of learners (regardless of their devices), or 

• Mobility of content/resources in the sense that it can be accessed 

from anywhere. 

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In this account her audience preferred the broader concept of learning 

taking place in the 'mobile age', rather than the use of the narrower 

term 'mobile learning'. This is near the position of addressing the learning 

of societies permeated and transformed by mobile systems and 

technologies (Traxler, 2008) rather than letting educational technology 

drive the definition and development of mobile learning. This moves 

on from a definition in terms of devices and technologies and through 

definitions delineating mobile learning from 'other' learning or 'normal' 

learning and takes the position that mobile learning is whatever learning 

is most aligned to progressively more mobile societies. 

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Sharpe, R., Benfield, G., Roberts, G. & Francis, R. (2006). The 

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%20Theory%200f%20Mobile.pdf 

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Age. elearnspace Dec 12th 2004. 

http://www.elearnspace.org/Articles/connectivism.htm 

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Learning, January 2005, 

http://www.itdl.org/Journal/Jan_05/article01.htm. 

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in mobile environments? Evaluating Mobile Learning In M. 

Sharples (Ed), Big Issues in Mobile Learning. Nottingham: 

Kaleidoscope Network of Excellence, Mobile Learning Initiative. 

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Education, International Review of Research in Open and Distance 

Learning. 

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Reflections on Current Practice, Proceedings of mLearn2005: 4th 

World Conference on mLearning, Cape Town, South Africa, 25-28 

October 2005. Online available: 

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Author 

John Traxler is Reader in Mobile Technology for e-Learning and Director 

of the Learning Lab at the University of Wolverhampton. He is a 

Founding Director of the International Association for Mobile Learning, 

Associate Editor of the International Journal of Mobile and 

Blended Learning and Conference Chair of mLearn2008, the world's 

biggest and oldest mobile learning research conference. John has cowritten 

a guide to mobile learning in developing countries and he is coeditor 

of the definitive book on mobile learning: Kukulska-Hulme, A. 

and Traxler, J. (2005) Mobile Learning: A Handbook for Educators and 

Trainers, Routledge. John has written over 10 book chapters and publishes 

regularly on evaluating and embedding mobile learning. He is 

interested in the profound consequences of universal mobile devices on 

our societies. He has been invited to present at the South African national 

science festival at Rhodes University, and invited by Microsoft to 

the Mobile Learning Summit in Seattle. He starts a two-month spell as 

visiting scientist at the Meraka Institute in Pretoria supporting mobile 

technology projects rolling out across South Africa in 2009. 

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Guy, R (Ed.). (2009). 


Santa Rosa, California: Infon:n.ing Science Press. (pp. 15-55). 

Chapter 2 


James Kadirire 

Introduction 

With the proliferation of mobile devices, there is also great potential to 

harness mobile technologies to enhance learning with mobile devices. 

Mobile learning can mean different things to different people. For instance, 

some definitions include aspects which characterize mobile 

services, such as location independence ry avoula and Sharples, 2002). 

Other definitions are based on technology related features such as the 

wireless network infrastructure (Leung and Chan, 2003). We define 

mobile learning as a form of e-Learning, which can take place anytime, 

anywhere with the help of a mobile communication device such as a 

mobile phone, a personal digital assistant (PDA) , iPod or any such 

small portable devices. However, for the purposes of this chapter, we 

concentrate mainly on mobile learning on mobile phones and PDAs 

and any such other small portable devices. There have been many attempts 

to use mobile devices over the past few years with differing 

degrees of success (Attewell, 2004; Kadirire, 2005b). However, in all 

cases, the results have been very encouraging and mobile devices still 

have great untapped potential in education (NESTA FutureLab, 2005; 

Vetter et al., 2005; Kadirire, 2007). It is encouraging to note that the 

use of mobile phones, particularly for text messages, has exceeded the 

operators' wildest expectations, with an estimated 52 billion text messages 

in the UK alone in 2007 (M:obile Data Association, 2007). This 

certainly adds weight to the assertion that given the right applications, 

mobile device users do like to use their mobile devices and this opens 

up huge opportunities to develop applications that can take advantage 

of these mobile devices' ubiquity and pervasiveness. An area which has 

great potential for using mobile devices in education is that of location 

based services, in which a user carrying a mobile device can have their 

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location and context detected and have some reusable learning objects 

streamed to their devices (Roussos, 2002; Korkea-aho, 2002; Benford, 

2005; Hunaiti et aI., 2008). Also podcasting or vodcasting and games 

based learning are beginning to see the light of day in mobile learning. 

This chapter looks at how mobile devices are being used for learning, 

particularly in higher education institutions (HEIs) or universities and if 

indeed we are realizing the much heralded potential of mobile devices 

in education. 

A Brief History of Learning with Mobile Devices 

The first public cellular or mobile systems only began operation in the 

early 1980s. Prior to this, mobile communications had been the preserve 

of the military, public safety or commercial two-way radio operations. 

In a cellular system, the covering area of an operator is divided 

into cells. A cell corresponds to the covering area of one transmitter or 

a small collection of transmitters. The size of a cell is determined by the 

transmitter's power. The concept of cellular systems is the use of low 

power transmitters in order to enable the efficient reuse of the frequencies. 

Analog cellular networks are known as First Generation (1 G) networks, 

an example of which is the adt'anced mobile phone smice (AMPS). 

Advancement in mobile communications has been very rapid and 

within the space of less than a decade, 1G systems have been replaced 

by Second Generation (2G) systems. 2G cellular communications, which 

integrated digital service systems were designed with the aim of going 

digital and are in wide spread use today. They use a technique called 

time ditision multiple access (TDMA) and the main system in use in Europe 

and other parts of the world is the global [Ystem for mobile communications 

(GSM). Digital transmission has several advantages over analog for 

mobile communication. Firstly, voice, data, and facsimile, can be integrated 

into a single system. Secondly, as better speech compression 

algorithms are discovered, less bandwidth is needed per channel. Finally, 

error-correcting codes can be used to improve transmission quality 

and digital signals can be encrypted for security. Third generation 

(3G) systems are intended to provide true global mobility and global 

compatibility for the chosen technology and are in widespread use, 

gradually replacing 2G systems. The aim is to provide a wide range of 

services including telephony, paging, text messaging, multi-media messaging, 

voice messaging, video streaming, and broadband ISDN (B 

ISDN) capability. This is done through generic terminals able to access 

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the network via a range of interfaces, involving different technologies 

and providing multimedia operation. This migration from 2G to 3G 

systems involves the integration of several systems such as fiXed, wireless 

local loop, cellular, cordless and satellite systems. The availability of 

3G systems has been instrumental in the increasing adoption of mobile 

learning as it allows mobile phones to access the internet like normal 

computers via wireless fidelity (Wi-Fi), which uses the IEEE 802.11x 

wireless local area network (WLAN) standards and thereby makes use 

of the vast range of applications being developed for mobile learning. 

3G mobile phones, like the Nokia N95, the iPhone, et cetera, also have 

built in global positioning system (GPS) receivers, which enable the use 

of location-based services in mobile learning. According to Attewell 

(2005), there seems to be a constant stream of new technology breaking 

into the mobile phone market. 

In June 1985, the United States of America (USA) accounted for an 

estimated 200,000 wireless or mobile device subscribers. Ten years later 

(1995), the number of subscribers increased to just over 28 million 

(Cellular Telecommunications Industry Association, 2005). Research 

carried out by Houser and Thornton (2004) showed that the majority 

of university students on campus in Japan carry mobile phones. Many 

of the students tend to be reading their emails and entering information 

into their mobile phones. Up to the beginning of 2004, in China, 335 

million Chinese had mobile phones and this number is increasing by 

25% or more every year (Shudong and Higgins, 2006). In June 2005, 

wireless or mobile device subscriptions rose to just under 195 million in 

the USA, which essentially means that approximately six in ten USA 

citizens had a mobile telephone subscription. Globally, the number of 

mobile phones surpassed 2 billion in mid 2005 (International Telecommunication 

Union, 2005). According to findings by Lenhart, Madden, 

and Hitlin (2005), almost half of teenagers in the USA reported 

owning a mobile phone. The number of mobile phones rose to 3.3 

billion in the world as of November 2007 (Ahonen, 2007) and that 

number is growing year on year. With the establishment of mobile 

learning pedagogical theory (Ogata and Yano, 2004), there are many 

countries, especially in Europe, where open universities have already 

successfully introduced mobile learning into distance education programs, 

and the results have been very positive. Access and ownership 

of mobile devices are expanding among all demographics and cultures 

throughout the world, especially among adolescents and young adults 

(Rheingold, 2002; Roberts, Foehr, and Rideout, 2005). 

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Through regular interaction and personalization, mobile devices become 

more personally meaningful (furkle, 2005) than traditional pedagogical 

tools such as graphing calculators, which are designed for academic 

exercises but not much else (perkins, 1992). Given the pervasiveness 

of mobile devices, educators must understand the strengths 

and limitations of these devices as evocative objects with which to 

think and learn (Dieterle, Dede, and Schrier, 2007). N ascent mobile 

devices introduced in the late 1980s and early 1990s, for example, Apple's 

Newton and Nintendo's Game Bqy, have evolved considerably, gaining 

sophisticated computational and connectivity capabilities, morphing 

into smart phones, PDA-phone hybrids, and next generation handheld 

gaming devices like the Sony's Plt!Jstation Portable and Nintendo DS 

(Dieterle, Dede, and Schrier, 2007). Apart from technical advancements, 

there are also four complementary social trends that make mobile 

devices increasingly important to study (Dieterle and Dede, 2006). 

These are the proliferation of mobile devices, society's movement toward 

ubiquitous computing, mobile devices' facilitation of sophisticated 

instructional designs based on situated and distributed perspectives on 

learning, and mobile devices' fostering of media based learning styles. 

Learning with Mobile Devices 

To date, developments in mobile learning are driven by pedagogic necessity, 

technological innovation, funding opportunities and the perceived 

inadequacies of conventional e-Learning. These developments 

have taken place within relatively narrow educational discourses 

(Salmon and Edirisingha, 2008). O'Malley et al. (2005) developed guidelines 

for implementing mobile learning in which one of the cornerstones 

is to investigate the cost model for infrastructure, technology, 

and services. Although mobile devices are truly ubiquitous and pervasive, 

particularly in the developed world, if HEIs are to successfully 

introduce mobile learning, they may have to help the students buy the 

mobile phones or loan the phones to the students, and this incurs a 

significant initial capital expenditure, which has to be cost and budgeted 

for. Perry (2003) argues that mobile devices are the cheapest way of 

providing students with a computing device that can be taken home 

and through which they can connect to the Internet or the Web to 

access learning resources or content on virtual learning environments 

(VLEs) or learning management systems. Traxler (2004) also suggests 

that using mobile devices for learning may bring some hidden benefits 

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when compared to using other information and communications technologies 

(ICT). The personal and collaborative nature of mobile devices 

can encourage participation and build social capital, which can be 

used to motivate disengaged or at-risk students. An article published in 

NESTA FutureLab (2005) also claims that a mobile phone increases 

the possibilities for informal learning that is not tied to a particular 

physical location. The e-Viva research project at Anglia Ruskin University, 

funded by the Qualifications and Curriculum Authority, enabled its 

Key Stage 3 students (Key Stage 3 covers children aged 11-14 in years 

seven, eight, and nine at schools in England) to take part in assessments 

by answering pre-recorded questions over their mobile phones. This 

research showed that teachers believed that mobile phone usage made 

their pupils much more aware of what they were doing and why they 

were doing it. Knowing that their work was going to be seen by others 

also had a positive effect, in that it increased their motivation and built 

their self confidence (Walton, 2005). Research in mobile learning in 

classrooms by Roibas and Sanchez (2002) also showed that the way 

forward in mobile learning in formal educational settings will be the 

introduction of handheld devices. 

When learners are interested in the technology, it captures their attention 

and makes them more interested in learning, provided that the 

right sort of learning content is introduced to them on the mobile devices. 

This is borne out by some research carried out in the Numina 

project at the University of North Carolina at Wilmington (Vetter, 

Heath, Herman, et aI., 2005) which found that students enjoyed the 

technology and became more active in their learning when handheld 

pocket computers were used in the classroom. Mobile devices can support 

mobile computer supported collaborative learning by providing 

another means of coordination without attempting to replace any human-human 

interactions, as compared to, say, online discussion boards 

which substitute for face-to-face discussions (Zurita, Nussbaum, and 

Sharples, 2003). Mobile learning is increasingly being used in Webbased 

online courses, and there is a large body of evidence to show that 

learning online can have a high attrition rate due to feelings of isolation 

(McInnerney and Roberts, 2004). Isolation can influence a student's 

attitude to online learning and, as such, needs to be given greater consideration 

when designing Web-based courses, of which mobile learning 

plays an increasingly significant part. Wegerif (1998) illustrates the 

frustrations that can so quickly become alienation by quoting from one 

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of the students involved with his study of an asynchronous learning 

network course: 

''It is a cold medium. Unlike face-toface communication you get no instant fiedback. 

You don't know how people responded to your comments; thry just go out into 

silence. This fiels isolating and unnening. It is not warm and supportit'e. " 

In this increasingly competitive market in which universities are fighting 

to recruit students from a limited pool, it is imperative to use technologies 

like mobile learning to get an edge over one's competitors. Mobile 

devices which are an integral part of mobile learning have played a huge 

part in the continued success of social networks, which are increasingly 

being used by university students for their academic work, as well as 

building communities of practice. These social interactions via social 

networks, like MySpace, FaceBook, et cetera, can be used as a building 

block for learning how to effectively communicate online, in terms of 

pedagogy. The m-Learning pan-European mobile learning research 

project (Attewell, 2004; Kadirire, 2005a) showed that learners were 

typically enthusiastic about mobile learning, with 62 per cent reporting 

that they were keen to take part in future learning after trying mobile 

learning. Research on the e-Viva project by McGuire and colleagues 

from Anglia Ruskin University, with mobile devices (as cited in Walton, 

2005) also showed that learning with mobile devices helped reduce the 

formality of the learning experience by engaging reluctant learners 

through raising their self-confidence. 

As the education marketplace becomes increasingly competitive, institutions 

can offer mobile learning opportunities as a competitive edge 

over other institutions. Mobile learning can fit training niches, such as 

in medical training where significant costs are incurred for students 

who drop out or fail (Naismith et al., 2004). Perry (2003) argues that 

the effective implementation of mobile learning requires a clear pedagogical 

approach and identification of specific learning needs/goals and 

teachers to be directly involved in decisions on planning and curriculum 

use. It is therefore important to assess that the technology is suited to 

the learning tasks. This is also borne out by the research carried out by 

Florand (2007) in which she tried to use vodcasting as a means to help 

her students learn French. Although vodcasting, which is a more complex 

form of podcasting (which is explained in a later section), is a perfectly 

viable means of mobile learning, Florand (2007) found that it 

required a lot of technical expertise for editing the video and tended to 

be a distraction to the students, as they seemed to concentrate on the 

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video editing rather than the learning outcomes. Mobile devices can 

also be used and, indeed, are being used, albeit mainly as case studies, 

to support informal and lifelong learning. In their literature review on 

mobile learning, Naismith et aI. (2004) posit that research on informal 

and lifelong learning recognizes that learning happens all of the time 

and is influenced both by our environment and the particular situations 

we are faced with. Informal learning could be realized through acquiring 

information as a result of discussions or conversations, listening to 

the media like the radio or television, et cetera. Naismith et aI. (2004) 

argue that such a broad view of learning takes it outside the classroom 

and, by default, embeds learning in everyday life, thus emphasizing the 

value of mobile technologies in supporting it. It is very useful and opportune 

for students out on field trips to take photos of species, plants, 

rocks, birds, et cetera, about which they are learning, with position 

information detailing the exact location where this was done, plus add a 

commentary of what they were doing, and subsequently email this back 

to their portfolio of web site for analysis when they return on campus. 

They can also take photographs of birds or various species they want to 

study, on their iPods for example, and when they are deep in the forests, 

they can play back the bird songs/sounds and photos in an effort 

to help them identify these species out in the wild. In higher education, 

mobile devices can also provide course material to students, including 

due dates for assignments and information about timetabling and room 

changes. Examples of using mobile technologies in this context include 

a mobile learning organizer which has been developed and tested at the 

University of Birmingham (Holme and Sharples, 2002; Sharples et aI., 

2003; Corlett et aI., 2004), and the use of mobile phone technologies to 

support computing students (Riordan and Traxler, 2003; Traxler and 

Riordan, 2003). 

Learning Theories and Mobile Learning 

Learning is an experience which produces a stable change in someone's 

knowledge or behavior. Change must occur because of experience, 

regardless of whether the learning is intentional or not. There are 3 

main learning theories that underpin how learning (knowledge construction) 

takes place and we want to try and relate these learning theories 

to mobile learning. 

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Behaviorism 

This regards the learner as a black box and the cognitive processes are 

not considered important in the knowledge construction. Skinner's 

brand of behaviorism held that learning involved the simple association 

between a stimulus and a response, enabled by reinforcement (Skinner, 

1968). The method of operant conditioning was used to shape responses 

to particular stimuli. Operant conditioning is the use of consequences 

to modify the occurrence and form of behavior. His assumption 

was that we can never know what goes on inside the mind, which 

was considered as a "black box', so the only things worth studying were 

the observable and measurable aspects of human behavior. Skinner and 

his followers emphasized antecedents and consequences as mechanisms 

for changing behavior. In the behaviorism theory of learning, environmental 

influences, i.e. antecedents and consequences, are supposed to 

shape all behavior, in the "A-B-C" pattern. In this antecedent-behaviorconsequence 

paradigm, antecedent precedes behavior, which is followed 

by a consequence. Consequences of behavior become antecedents 

for the next "A-B-C" sequence. Behavior is changed by changing 

antecedents, consequences, or both. In terms of application to learning 

technologies like mobile learning, the approach has been characterized 

as "drill-and-practice" and ''present-testfeedback''. Typically, the learners are 

given some information or problem and asked to respond to some 

question or questions; then they are given feedback to their responses. 

Learning involves behavior change with reliance upon use of reinforcements 

to encourage learning. For example, a student could be 

asked to respond to a stimulus like (3+2=?) and given feedback on 

their response. Behaviorism is very effective for learning facts and for 

recall, but it is not so effective for explaining problem solving and creativity. 

Naismith et al. (2004) carried out a literature review in mobile 

learning in which they found that in a mobile learning context, classroom 

response systems like 'Classtalk' (Dufresne et aI., 1996) and 

'Qwizdom' (Qwizdom: Assessment for Learning in the Classroom, 

2003) fall into this behaviorism category. They also found that learning 

material delivered via mobile phones using the short message service 

(SMS), which is explained in a later section, also lends itself well to the 

behaviorism learning theory (BBC Bitesize, 2003; Thornton and 

Houser, 2004). 

The first successful classroom response system, Classtalk, was patented 

in 1989 (Abrahamson et aI., 1989). A classroom response system is a 

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special type of software that uses remote control devices like keypads 

and a receiver to give teachers or lecturers the opportunity to receive 

instant feedback from their students. The lecturer displays a multiple 

choice question on a screen, usually via a projector, and students respond 

to that question using their keypads. The system instantly collects 

and aggregates every student's response. Students hold individual 

handheld response units, which can be graphing calculators, infrared 

beaming units, or some other form of handheld mobile device, and 

send their responses anonymously. Although student responses are 

visible to both the teacher and students, student names are not attached 

to responses, but, instead, they are attached to a number or some other 

generic identification code known to the lecturer. The lecturer's machine 

aggregates the students' responses and presents them in a coherent 

form, usually a histogram. From the histogram, the teacher and 

students can observe patterns in the variation of responses readily and 

use this shared point of reference to launch into pedagogical conversations 

(Roschelle, 2003). Important pedagogical uses of this capability 

include monitoring students' evolving understanding of challenging 

domain concepts and driving their small group discussions. This type 

of pedagogy has been described as "Peer Instruction" (M:azur, 1997). 

Formative assessment and timely feedback are known to be very powerful 

tools for aiding learning, and these systems enable students to 

receive much more feedback than normal (Roschelle, 2003). A metaanalysis, 

i.e. an analysis that combines the result of several studies that 

address a set of related research hypotheses, was carried out by Black 

and William (1998) on formative assessment over a 10-year period 

across schools and the higher education sectors. Their research showed 

that where assessments focused on generating feedback and encouraging 

the use of feedback, the learning gains were among the largest ever 

reported for educational interventions. The feedback generated resulted 

in positive benefits on learning and achievement across all content 

areas. Nicol and Macfarlane-Dick (2006) also carried out research 

which shed light on how formative assessment and feedback could be 

used to support the development of learner self-regulation. Early 

adopters of classroom response systems have consistently described the 

technology as a catalyst for a significant, powerful shift in the classroom 

climate, pedagogy, and resulting learning (Dufresne et aI., 1996). Importantly, 

students can see where fellow students share their misunderstandings 

and that they are not alone. Further, because the displayed 

responses are anonymous, embarrassment is reduced (Owens et al., 

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2002). A teacher can consequently engage students in knowledge-rich 

conversations, through peer instruction (M:azur, 1997) or other techniques. 

Davis (2003) posits that the use of classroom response systems, 

which essentially use mobile devices let us not forget, emphasize a cycle 

of changes which maps onto the four factors of successful classrooms 

identified in a groundbreaking summary of learning science research 

(Donovan et al., 1999). The classroom becomes more leamer-centered, 

assessment-centered, knowledge-centered, and community-centered. 

Cognitivism 

This theory is concerned with what actually happens inside the learner's 

mind. It focuses on the mental constructs learners bring to an instructional 

situation and the mental processes that occur during learning. 

Cognitivism assumes that learning is a process of relating new information 

to previously learned information and that individuals are actively 

involved in the learning process. It also assumes that knowledge is organized 

and that learning involves the formation of mental associations 

that are not necessarily reflected in overt behavioral changes. Emphasis 

is on readiness, confidence, feelings, goal setting, mental rehearsal, 

memory, and active participation of the learner through mental engagement 

with the learning environment. Cognitivism focuses on how 

learners think about and rehearse materials in order to learn, i.e., shift 

material from short term to long-term memory. According to Danesh 

et al. (2001), mobile devices' mobility can enhance inter-group collaboration. 

Children can walk around, maintaining the flexibility of interacting 

with many other children rather than limiting their collaboration to 

those on the computer beside them. Also, mobile devices support social 

interactivity, are sensitive to shifts in context, enable individualized 

scaffolding, and facilitate cognition distributed among people, tools, 

and contexts (Klopfer, Squire, and Jenkins, 2003). Research in the 

science of how people learn has recently been focused on the situated 

and distributed nature of cognition as applied to thinking, learning, and 

doing in workplace and community settings (Wenger, McDermott, and 

Snyder, 2002). Cognition is viewed as situated within both a physical 

and a psychosocial context and as distributed between a person and his 

or her tools (Sternberg and Preiss, 2005). The learner's environment is 

essential to the learning process, since the context can alter, improve, 

and support certain types of performances, approaches to problems, or 

learning activities (Dieterle, Dede, and Schrier, 2007). As such, because 

of their mobility, mobile devices are well suited to cognitive learning. 

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Constructivism 

There has been a lot of research done on learning and teaching strategies 

over hundreds of years and over twenty four hundred years ago, 

Confucius (479 BC), a Chinese philosopher and reformer declared: 

''What I hear I forget. 

What I see, I remember. 

What I do, I understand." 

According to Marton and Booth (1997), for learning to be effective, the 

theories of learning and teaching must be based on phenomenography 

and constructivism. Phenomenography is the theory that the leamer's 

perspective defines what is learned and not what the teacher intends 

should be learned. Constructivism is the theory of learning that is 

broad-based and empirically sound and also easily translates into practice, 

with an emphasis on what the learners have to do rather than on 

how they represent knowledge (Ginsburg and Opper, 1987). It is clear 

from this that learning takes place through the active behavior of the 

learner and what the learner does determines what he or she learns, not 

what the teacher does (Tyler, 1949). The underlying principle behind 

constructivism is that knowledge cannot be transmitted to learners. 

Instead, the learners must construct knowledge for themselves. The 

constructivist perspective describes learning as a change in meaning 

constructed from experience, and in this theory knowledge construction 

is the process of thinking about interpreting experience (Piaget, 

1929; Bruner, 1966; Papert, 1980). The "knower' and the "known" cannot 

be separated and, since knowledge construction results from activity, 

knowledge is embedded in activity. Knowledge is anchored in the 

context in which the learning activity occurs. When mobile devices are 

used in conjunction with constructivist learning principles (Brooks and 

Brooks, 1993) and guidelines for differentiating instruction (Tomlinson, 

1999), they have the potential to change both what and how we teach 

and learn. Because of their mobility, mobile devices enable students to 

effectively solve problems in the environment where they occur. As 

Staudt (2005) explains: 

'Teachers will guide student learning experiences and, particularlY in our standardsbased 

emironment, will align learning experiences to meet those standards. " 

Predetermined learning experiences are replaced with students following 

their own trails of interest, scaffolded by teachers, peers, and tools. 

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Instead of receiving piecemeal information, students are supplied with 

relevant conditions and authentic problems to help them focus on large 

ideas while socially constructing deep understandings. As a result, students 

can navigate their own self-defined learning paths, engage with 

multiple modalities with varying degrees of complexity, make new contextually 

relevant connections, reformulate ideas and preconceived 

notions, and create their own conclusions (Dieterle, Dede, and Schrier, 

2007). In the literature survey carried out by Naismith et al. (2004), they 

state that the most compelling examples of the implementation of constructivist 

principles with mobile technologies come from a brand of 

learning experience termed ''participatory simulations", where the learners 

themselves act out key parts in an immersive recreation of a dynamic 

system. An example of this is the Environmental Detectives (Klopfer et 

al., 2003). Environmental Detectives was the first augmented reality 

(AR) game created at the Massachusetts Institute of Technology (MIT). 

It was targeted at high school and university students. The students 

play the role of environmental engineers who are presented with a 

problem of toxins polluting the water. The spread of the toxin is simulated 

on a location-aware Pocket PC, which functions as a tool which 

students can use to investigate the toxic spill. The goal of the game is to 

locate the source of the spill, identify the responsible party, design a 

remediation plan, and brief the president of the university on any health 

and legal risks. At the end of the game, students make a five minute 

presentation to their peers outlining their theory behind the spill. Again, 

mobile devices lend themselves well to the constructivist learning theory, 

particularly when they are used in games based learning (Lepper 

and Cordova, 1992; FutureLab, 2007). 

Context Aware Mobile Learning 

An area which has great potential for using mobile devices in education 

is that of location based services, in which a user carrying a mobile 

device can have their location and context detected and have some 

reusable learning objects (RLOs) streamed to their devices (Roussos, 

2002; Korkea-aho, 2002; Benford, 2005; Hunaiti et al., 2008). A RLO is 

essentially any entity, digital or non-digital, that can be used for learning, 

education, or training (IEEE, 2002). According to Schilit et al. 

(1994), the important aspects of context are: where you are, who you 

are with, and what resources are nearby. They define context to be the 

constantly changing execution environment, which includes the: 

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• Computing em-ironment - available processors, devices accessible 

for user input and display, network capacity, connectivity, and 

costs of computing; 

• User em-ironment - location, collection of nearby people, and the 

social situation; 

• Pf?ysical em-ironment -lighting and noise level. 

Context is all about the whole situation relevant to an application and 

its set of users. We cannot enumerate which aspects of all situations are 

important, as this will change from situation to situation. With this in 

mind, we use the definition of context by Dey and Abowd, (1999), 

which deftnes context as: 

"Context is a'!Y information that can be used to characterize the situation of an 

entiry. An entiry is a person, place, or oiject that is considered relet'ant to the interaction 

between a user and an application, including the user and applications themse/res. 

" 

In their literature review on mobile learning, Naismith et al. (2004) 

posit that mobile devices are especially well suited to context-aware 

applications because they are available in different contexts and, so, can 

draw on those contexts to enhance the learning activity. Examples of 

context aware applications can be found within the museum and gallery 

sectors, which provide additional information about exhibits and displays 

based on the visitor's location within them (Proctor and Burton, 

2003). Some researchers from Anglia Ruskin University carried out a 

limited study with location based services (LBS) using mobile devices 

with very positive results (Hunaiti et al., 2008). The aim of the case 

study was to demonstrate the usability of LBS as a mobile learning 

system in which learning objects could be delivered to the learners' 

mobile devices based on their geographical location calculated from the 

obtained position information from the GPS receiver. The idea was to 

divide the university campus into zones in which each zone represented 

some specific interest. For instance, one could have a zone which consisted 

of a library such that when users with mobile devices that had 

this software installed approached the library zone, they would have 

information pushed to their mobile devices telling them where they 

could find library related material. Alternatively, users could explicitly 

query their mobile devices for the services available within their location 

and context. The users can then choose from a menu what they 

want to find and the system then guides them to the exact location 

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where the material or service is located. Another possible application 

could be, as one approaches some campus building, information about 

what lectures are scheduled in the various lecture theatres or classrooms 

can be pushed to one's mobile device and one can then locate 

where one's lecture is being run. In the case-study conducted by Appear 

Networks (2004), at the University of Geneva, their context aware 

application named Appear IQ, allowed students to smartly access all of 

the information they needed using a context triggered approach that 

anticipated the needs of its users by analyzing their context and automatically 

providing them with tailor-made content and applications. 

Mobile Learning with the Short Message Service (SMS) 

The short message service (SMS) was developed as part of the Global 

System for Mobile Communications (GSM), and it allows mobile systems 

and other network-connected devices to exchange short text messages 

with a maximum length of 160 characters. The length limit is 

caused by the way that SMS is transmitted. It usually rides on the control 

channels, the same frequencies or time slots used for call setup 

information by mobile phones. This means that users can send or receive 

SMS messages while they are making a phone call, though they 

need a hands-free kit to read the screen or type on the keypad (Dornan, 

2000). SMS was commercially introduced in 1992, and in 2001 an estimated 

102.9 billion SMS messages were exchanged worldwide (Le 

Bodic, 2002). There is much to discover about the adoption of mobile 

learning using SMS. Stone and Briggs (2002) have shown that SMS has 

a quicker response time for interactive activities in education than email 

on the web. SMS has been called the 'killer' application of mobile 

phones, as its usage exceeded all expectations and its success was never 

planned as it was originally intended to replace the pager (Mitchell, 

Heppel, and Kadirire, 2002). The pager is a small handheld device that 

allows text messages to be sent to the device, and to respond the user 

of the pager must get to a telephone (landline or mobile/cell phone). It 

is still widely used in hospitals, the military, the police, and industry, 

where use of telephones may not be allowed. According to reports on 

the Mobile Data Association (2007) website, in December 2004, 2.45 

billion SMS/text messages were sent via the UK operators; in October 

2007, 5.3 billion SMS/text messages were sent in the UK, and there 

were an estimated 52 billion SMS/text messages sent in the UK alone 

in the whole of2007. (The terms SMS and text messages are being used 

interchangeably.) Some of the reasons attributed to this unprecedented 

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exponential growth of SMS messaging include low cost and the asynchronous 

nature of the service, which means users can reflect before 

sending and replying to messages (M:itchell, Heppel, and Kadirire, 

2002). Some studies carried out by Divitini, Haugalo, and N orevik 

(2002) on student populations have shown that 80% of students send 

SMS messages every day. This invariably builds a sense of community 

amongst the students, especially when coupled with other phenomena 

like social networking websites, thereby promoting life-long and deep 

learning because of its interactive nature. Interactivity in the classroom 

is reported to promote a more active learning environment, facilitate 

the building of learning communities, provide greater feedback for 

lecturers, and help student motivation (M:arkett et al., 2006). Students 

who took part in this case study reported benefits of participating in 

using SMS for interactive learning. At least 50% of the students found 

that the interactive nature of sending SMSjtexts anonymously to the 

lecturer and getting feedback made the students more interested and 

engaged in the learning process, making them ask more questions. The 

SMSjtext messages were collected by an leT tool which was only visible 

to the lecturer, who could then give immediate feedback openly. 

Also, some SMSjtexts sent within a short space in time of each other 

were very similar in nature, and this allowed the lecturer to see the level 

of understanding in the class as a whole and address the issues. 

Some limited research conducted at Anglia Ruskin University has also 

shown how SMSjtexting can be used in education for interactive learning 

or discussions (Kadirire, 2005b). Students send SMS messages to 

the lecturer or tutor in schools or university seminars or presentations 

or conferences. The lecturer selects each message, which is then displayed 

on a large screen, and interactively deals with the question. An 

example usage of SMSjtext messaging in learning is best illustrated by 

Figure 1. The application receives the SMS(s) and stores them in a database. 

It then adds other formatting information to allow the SMS to 

be displayed on the computer screen as small "post-it notes" (nicknamed 

stickies), which can be tiled, cascaded, or arranged in any order. 

The term "stickie" is derived from the idea of a post-it note, which people 

can scribble a message on and then stick onto someone else's desk, 

computer, wall, notice board, et cetera. The stickies or small frames are 

color coded and fade their colors from a bright yellow to grey, depending 

on how long they have been displayed. They can be saved with state 

information, and when the application is started again, the position, size 

and color of the stickies is preserved. When being used in a classroom or 

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lecture theatre, a projector is connected to the computer or a laptop, 

and then the stickies are projected onto a large screen which everyone 

can see. When the SMS has been displayed, the lecturer can interactively 

deal with each SMS message and give feedback to the students. 

When the lecture is over, the stickies can then be saved, not as stickies 

but as text messages with additional information like the size, color, and 

co-ordinates so that when the application is started the next time, it 

retrieves the previous stickies and preserves their state information as 

well as accept new incoming messages. A good analogy is when one 

puts a computer into hibernation or sleep mode and then restarts it at a 

later time, the computer has preserved all the applications et cetera and 

restores it to its previous state before it was shut down. 

fUt Window Clwost Colour tWlp 

;ONFERENCE/PRESENTATION NAME 

TEXT YOUR CO...::NTS TO: 

07749978835 

PREFIX IlEISAGE WITH KEYWORD; discuss 

!!Dll!rtr"!i!i"'ii!illI.iJjmovt~ngi!ii:c~--~~===========itl~ 

ADDRESS; Imp;llwwvr,Jtltyos.com 

f)()02()()oo1-0S-21 

This is yet 

another test 

message, on 

~ 

An,...., 0004-0J08 

What happens 

to the 

Ultraveslty 

nnn }nC1


sive words from the text message and replace them with asterisks (*), 

and if a text message has more than 2 or 3 swear words it is deleted and 

not displayed. A slight concern is the cost of sending an SMS message 

(about 10p/12p in the UK), but one assumes that everyone who can 

afford to buy a mobile phone can at least afford to spend lOp for a text 

message. 

SMS is also being used in learning to provide revision material as 

shown by the BBC Bitesize (2003, 2004) initiative. Due to the limited 

number of characters that can be transmitted in an SMS message, the 

revision materials are, to all intents and purposes, "byte-sized". This 

initiative has been running since 2003 and has proved to be very popular, 

with an audience of 650 000 General Certificate of Secondary Education 

(GCSE) students, as well as adult learners. GCSE is the name of 

a set of English qualifications, generally taken by secondary school 

students at the ages between 14 and 16 years in the United Kingdom 

(UK). A number of schools and some universities in the UK are using 

SMS for sending alerts and timely information about lectures to the 

students. Riordan et al. (2003) from the University of Wolverhampton 

carried out some research to develop, deliver, and evaluate blending 

learning opportunities that exploited SMS, wireless access protocol 

(WAP) , and virtual learning environment (VLE) technologies. The 

initial research indicated that students used SMS/text messaging 

promptly and effectively, and that they preferred to receive notice 

board information such as room changes, appointments, feedback, and 

examination tips via SMS rather than via e-mail or notice boards. The 

target group was the Higher National Diploma (HND) in computing 

students, whose attendance and performance were considered to be at 

risk due to poor literacy skills exhibited in their coursework. Some of 

the SMS/text messages provided revision tips prior to the examinations. 

The key features of the SMS interventions were timeliness and 

appropriateness, such that 'at risk' learners could be directed as appropriate 

to either WAP-based support, VLE-based support, or in-house 

support before their academic careers were significantly impacted. Following 

the trial, final exam results for the group of students receiving 

SMS interventions were slightly higher than a non-SMS group taking 

the same module at the same time. 

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Mobile Learning with Instant Messaging (1M) 

'Instant Messaging' (1M) and 'Presence,' which is essentially the ability 

of being able to detect if other users are logged-in on the network and 

send them messages in real time, has become one of the most popular 

applications of the Internet. Instant messaging is making people want 

to stay connected to the Internet for an inordinate period of time, a 

phenomenon that is also helping to foster a greater sense of "online 

community" that no other application has done previously (Alvestrand, 

2002; Kadirire, 2007). It is also becoming widespread in universities and 

is now being used for online discussions, chatting, file transfer, library 

access, and so forth. Some of the most common 1M applications are 

AOL Instant Messenger, MSN Messenger, Yahoo Messenger, Coogle Talk, and 

Skype. All 1M systems support avatars (a movable icon representing a 

person in cyberspace or virtual reality graphics), in addition to user 

icons. According to the research conducted by Lenhart and Shiu 

(2004), 42 per cent of Internet users in the United States (about 53 

million people) use instant messaging, and its appeal is apparent 

amongst young adults and technology enthusiasts. Research carried out 

at Wake Forest University (Walker, 2005) has shown that student mobile 

phone usage patterns are moving away from more traditional messaging, 

like email for instance, to newer technologies such as instant 

messaging and SMS. This trend should encourage students to become 

more engaged with course material outside the classroom and help 

them communicate better among themselves. Often students want to 

communicate or locate other people while in indoor environments, for 

instance, in a meeting room, lecture theatre, or inside a large building; 

mobile phones and laptops are ideal devices for this. Unlike in face-toface 

classroom settings, in order for the learning process to be successful 

in online distance education, attention must be paid to developing a 

sense of community amongst participants. Indeed, instant messaging is 

a natural medium for online community building and asynchronous 

peer discussions (Nardi, Whittaker, and Bradner, 2000; Rheingold, 

2000; Quan-Haase, Cothrel, and Wellmann, 2005; Kadirire, 2007). We 

feel this trend should encourage students to be more engaged with 

course material outside the classroom as well as communicate better 

among themselves. Limited research carried out by Sotillo (2006), for 

example, showed evidence of successful learner uptake in a synchronous 

instant messaging environment. Kadirire (2007) argues that while 

no single technology is going to create a complete collaborative learning 

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environment, 1M systems can play an important role in creating interactive 

and collaborative mobile learning environments. For instance, a 

limited pilot study carried out by Sotillo (2006) showed that when corrective 

feedback was embedded in learning activities conducted via 

instant messaging tools, learners were able to expand their linguistic 

competence outside the traditional face-to-face environment. In that 

study, Sotillo (2006) used Yahoo! Messenger, connected to a desktop 

personal computer with speakers, a microphone, and a webcam. This is 

a more flexible and cost-effective alternative to traditional video conferencing 

and is becoming increasingly popular in foreign and second 

language instruction. It is also worthy to note that most 3G mobile 

phones now can do what Sotillo did in her study. They have built in 

Wi-Fi, which allows them fast broadband access to the Web; they have 

two built in megapixel digital cameras to facilitate mobile phone conferencing, 

and it also goes without saying that they have a built in microphone 

and speakers to facilitate audio communications. Instant 

message software providers like Microsoft (MSN Messenger) and Yahoo! 

(Yahoo! Messenger), also make available their 1M chat clients for 

mobile devices for free. That means mobile devices can now take advantage 

of the popularity of 1M systems, albeit with a reduced key entry 

rate on account of the small keyboards. 

Mobile Learning with PodcastsNodcasts 

Podcasting is the process of capturing an audio event, song, speech, or 

mix of sounds and then posting that digital sound object to a website or 

"blog" in a data structure called an RSS 2.0 envelope or "feed". RSS 

stands for Really Simple Syndication and is an agreed specification of 

XML tags used to define objects which can be subscribed to through 

an "RSS news reader" (Meng, 2005; Cheetham, 2007). Podcasts, which 

are essentially digital audio programs recorded on some medium like an 

mp3 digital recorder and uploaded onto a server so that people can 

subscribe and download them via RSS feeds, can be accessed on a variety 

of digital audio devices, including a desktop computer or laptop 

(Learning Circuits, 2005). When a digital audio recording has been 

made, an RSS ftie is created which allows listeners to subscribe and 

download the podcast, and then the podcast is uploaded to a server for 

downloading by the listeners, in this case the students. So how do the 

students know about the podcasts and how do they subscribe to them 

and download them? Well, since this is educational material, most universities 

or HEls will have some virtual learning environment (VLE) 

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that will have other teaching material on it. The podcasts can be uploaded 

there and the students informed of the podcast address on the 

VLE or some other institutional server from which they can logon and 

subscribe to the RSS 2.0 tagged audio (or video files in the case of vodcasting). 

They only have to subscribe once and, because this is push 

technology, they will automatically receive any new podcasts that are 

subsequently uploaded throughout the course of the academic year and 

beyond. Students will need a content aggregator like iTunes to subscribe 

to the podcasts, then by synchronizing their iPods with iTunes, 

the podcasts will be downloaded to their iPods and they can then listen 

to them while on the move or anywhere in the same manner that they 

listen to music (Cheetham, 2007). The portability and on-demand nature 

of podcasting are the key components that allow listeners to catch 

up on audio content, whether its entertainment, news, or learning, 

without having to sit at a computer and while completing other tasks. 

In that sense, podcasting can be viewed as another variant of mobile 

learning (Learning Circuits, 2005). Vodcasting is a very similar technology 

to podcasting except that one is able to record not just audio, but 

also video. For this reason, vodcasting is a bit more complicated because 

of the need to be able to edit the video, which will need some 

technical expertise and also some editing software, which invariably 

makes it a more expensive technology than podcasting (Florand, 2007). 

A vodcast is still downloaded in the same manner as a podcast and can 

be played or viewed on mp3 players like the iPod Video. 

Podcasting in mobile learning provides convenient access to audio 

learning content and also introduces new pedagogies in mobile learning. 

Henriques (2007) uses podcasts for reviewing and expanded 

discussions on lecture material, presenting material that was not 

covered in the lectures. He also uses podcasts for providing content 

that goes beyond course material, for example, recent research. He also 

carried out some limited research on the impact of podcasts on 

examination performance and reported that students that listened to 

podcasts performed better in the exams, compared to those that did 

not listen to podcasts. Florand (2007) also uses podcasts and vodcasts, 

not just as a means to transmit information to her students, but also as 

a way to integrate debate inside as well as outside the classroom. The 

students would make their own podcasts and upload them onto the 

university's server to allow other students to listen to them as well as 

peer review and discuss each other's work in the classroom. This is a 

very effective way to stimulate engagement amongst the students as 

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they not only listen to what their lecturer says, but also what other 

students are saying and getting a chance to discuss it amongst 

themselves. The students also found the podcasts useful for additional 

listening comprehension practice for the French studies. In her 

presentation at the 23rd Annual Conference on Distance Teaching and 

Learning, Cheetham (2007) proposed that, like YouTube and blogging, 

podcasting is a new way of creating and sharing learning content. There 

are also legitimate concerns about using podcasts/vodcasts because this 

might discourage students from attending lectures. However, there is 

no evidence to support this based on the experience of academics like 

Henriques (2007) and Florand (2007). It is nevertheless essential to bear 

this in mind when designing and creating podcasts/vodcasts for 

teaching and to have clear pedagogical motives and learning outcomes. 

Podcast/vodcasts should be used not as a replacement for lectures, but 

as a means to supplement the conventional lectures. Although podcasts 

are becoming very popular, they should not be used without careful 

thought. A pedagogical rationale has to be developed through examining 

the teaching and learning issues that they can address (Salmon and 

Edirisingha, 2008). Salmon and Edirisingha (2008) suggest that some of 

the pedagogical rationale could be: 

a) Limitations in teaching complex and difficult topics; 

b) Limitations of conventional approaches in teaching of software 

tools; 

c) Limitations of conventional feedback approaches; 

d) Issues faced by first time online learners; 

e) Issues faced by distance learners; 

f) Improving the usefulness and attractiveness of teaching and 

learning resources; 

g) Developing competency in collaborative skills, active learning 

skills, presentation skills, essay writing skills, reflective skills, research 

skills, as well as articulation and communication skills. 

Many universities are increasingly taking up podcasting as a means of 

educating their students, for example, the University of Wisconsin, 

Duke University, Open University, MIT, UCL, and Stanford. Apple 

have created iTunes U, an online iTunes Store to work for colleges and 

universities, so users can easily search, download, and play course content 

just like they do music, movies, and TV shows (iTunes U, 2008). 

This has proved to be very popular with over 300 universities in the 

USA, plus top universities like the Open University and University 

College London from England joining and making their lectures and 

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podcasts available for download to the iPod and the iPhone for free 

(Cheetham, 2007; iTunes U, 2008). In 2004, Duke University gave over 

1600 20GB iPods to all their first-year students, together with voice 

recorders as part of an initiative to encourage creative uses of technology 

in education (Duke University, 2004). The Duke iPod First-Year 

Experience, as the program was called, released a report which found 

that the academic uses of the iPods (mobile devices) were a: 

a) Course content dissemination tool which provided portable 

access to content such as lectures, songs, historical speeches, 

and foreign language content distributed in various ways, including 

podcasting; 

b) Classroom recording tool for capturing lectures, class discussions, 

guest speakers, and verbal feedback; 

c) Field recording tool for capturing field notes, interviews, environmental 

sounds, and audio data; 

d) Study support tool for repeated listening and repetition of audio 

content; 

e) File storage and transfer tool. Simple transfer and backup 

mechanism, particularly for large multimedia fties. 

The Duke iPod First-Year Experience also reported on the benefits of 

the iPod use being the convenience of portable digital content, reduced 

dependence on physical materials and lab or library locations and 

hours, greater student engagement and interest, and enhanced support 

for individual learning preferences and needs. 

Podcasts should not be made too long, although there is no definitive 

length for podcasts and different academics who have been using podcasts 

in their teaching recommend different recording lengths. Podcasts 

should not be more than 10 minutes according to the research by 

Salmon and Edirisingha (2008), but Henriques (2007), who also uses 

podcasts in his teaching makes his podcasts between 3 and 16 minutes, 

so 10 minutes seems like a good average length for a podcast. 

Podcasting/vodcasting new pedagogies 

Podcasts or vodcasts will not replace conventional ways of classroom 

learning and teaching like reading, listening to live presentations, or the 

multitude of other ways learners take in information, but it can augment 

those methods. Some of the new pedagogies as a result of podcasting 

according to the Learning Circuits (2005) are listed below. 

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a) Assist auditory learners. Proponents of podcasting point out 

that the medium is perfect for learners who prefer to take in 

information aurally and this helps audio learners to retain the 

information covered. Critics say that students would stop attending 

classes, but evidence from those putting lectures on 

podcasts found that attendance did not in fact decline, because 

students didn't want to miss what was going on. 

b) Provide another channel for material review. Listeners with 

other types of learning styles can benefit from podcasts as well. 

When material is delivered orally, as in university lectures, 

classroom-based training, or in-person presentations, podcasting 

can ease learner worries that they missed key information 

in their note taking. The audio fties can be reviewed at their leisure 

for understanding or before an examination. 

c) Assist non-native speakers. Learners who aren't yet proficient 

in the language may struggle to keep up with lectures or presentations. 

Being able to review recordings of those events as 

many times as necessary for understanding can be of great 

benefit. Podcasting can also be an excellent technology for 

learning a language, not only for listening to speech and pronunciation 

but also, in combination with a recording device, 

for capturing a leamer's own speech for review by themselves 

or a teacher. 

d) Provide feedback to learners. The lecturer or tutor can record 

feedback on his/her students' group presentations. This use 

can apply not only to lecturers, but also to learners, who could 

record and podcast peer feedback. 

e) Enable lecturers to review training or lectures. Lecturers can 

critique their own teaching on the podcast as a method of improving 

their teaching style. 

t) Replace full classroom or online sessions when content simply 

requires delivery. In many cases, learning requires interaction, 

questioning, practice, and so forth. But when what's required is 

simple delivery of information, a full-fledged in-person or 

online course may not be necessary. Podcasting can alert learners 

that there is new material to be accessed and then allow 

them to access it whenever, wherever they want. 

g) Provide supplementary content or be part of a blended solution. 

When a full course is necessary, there may be occasions 

when supplementary material would be helpful to learners. 

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Subject-matter-expert interviews are just one example of this 

type of content. The material could be available for access on a 

voluntary basis, or it could be a required component of a classroom 

or online course in a blended solution. In any case, the 

RSS technology allows lecturers to make the material easily accessible 

to learners and to alert them when new content is in 

the pipeline. 

Mobile Games Based Learning 

Yatim and Masuch (2007) define a game as a system in which players 

interact with a virtual environment governed by game rules and game 

mechanics from which the game play eventually emerges. Let us just 

explore some of the reasons why we need games in mobile learning. 

University student recruitment in the UK has become very competitive 

since all the polytechnics were upgraded to universities. It invariably 

means that there are more universities trying to recruit undergraduate 

students from a limited pool of applicants. As a result, there has been a 

decline in the student numbers in science and engineering subjects. 

Maths in schools is characterized by a traditional, abstract formulation 

that seems readily understood generally by only a small fraction of students. 

This is leading to poor experiences of science and engineering 

education among students in general, impacting on the uptake of these 

subjects (Roberts, 2002). Between 1990/1991 and 1999/2000, the 

number of students in the UK studying Science and Maths dropped. In 

particular, it dropped by 8.5 per cent for mathematics in the same period. 

Computer science as a major declined by 70 per cent between 

2000 and 2005 at the University of California Los Angeles (CRA Bulletin, 

2007). In an effort to try to recruit and retain science and engineering 

students, computer games are being used as tools in education 

(Good and Robertson, 2004). Mitchell (2004) posits that games for 

mobile phones have great potential for supporting cognitive and socioaffective 

learning, i.e., learning relating to moods, feelings, and attitudes. 

Also, playing games can support valuable skill development in 

strategic thinking, planning, communication, application of numbers, 

negotiating skills, group decision-making, and data handling (Kirriemuir 

and McFarlane, 2004). According to Malone and Lepper (1987), there is 

a relationship between learning and intrinsic motivation. Their research 

was based on an investigation of students who played computer games, 

which found seven key factors for creating an intrinsically motivating 

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instructional environment. These factors were challenge, curiosity, control, 

fanta!J, cooperation, competition and recognition. It was also shown by Lepper 

and Cordova (1992) that computer games raise the efficiency of learning 

if they increase the intrinsic motivation and link the goals 'winning the 

game' and 'learning the material'. 

A lot of research has been done in the academic world concerning use 

of games in education and, although it has still not been widely adopted 

for learning as much as other mobile based learning technologies like 

podcasting and SMS; it is making significant inroads into learning. The 

research into mobile games based learning is being funded both commercially 

by companies trying to develop educational games on mobile 

devices and also by the European Commission (MGBL, 2008). The 

mobile Games-Based Learning project (mGBL) is a three-year project 

that began in October 2005 and is supported by the European Community 

under the Information Society Technologies (IST) Programme 

of the Sixth Framework. It consists of 11 partner organisations from 

Austria, Croatia, Great Britain, Italy, and Slovenia working on the development 

of a platform for the presentation of educational content in 

a playful and emotional way (games-based) on mobile devices. The 

overall goal of the project is to improve the effectiveness and efficiency 

of learning in the target group of young people through the development 

of innovative learning models based on mobile games. The specific 

aim of the project is to design, develop, and trial a prototype game 

platform that can be used to efficiently develop games for mobile learning, 

whereby the focus is on the support of decision making in critical 

situations, not only in a cognitive but also in an emotional way. These 

games are meant to directly support learning via opportunities to develop 

knowledge and cognitive skills in an exciting and inspiring way. 

Another European Commission funded project into mobile games 

based learning is the eMapps project (eMapps, 2008). The eMapps 

project focuses on communities of creative, networking children in the 

new European Union (EU) member states and has produced some 

significant breakthroughs related to innovative ways of learning, using 

computer games and mobile learning in schools. 

In the UK, FutureLab (2007) have been carrying out interesting research 

into mobile games based learning, and they claim that games 

offer challenge, feedback, and engagement, although one also has to 

rethink how to plan lessons and what the learning outcomes are, since 

new pedagogies have to be developed. They have also developed a 

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mobile phone based game called "NEWTOON", which students play 

by manipulating the laws of physics and thereby obtain a better understanding 

of physics. It not only allows them to play games, but it also 

allows them to design their own games and play with their peers. In 

their Racing Academy project, FutureLab developed a simulation game 

to help mechanical engineering students learn how cars work (Future 

Lab, 2007). The students race their cars against their opponents and 

look at the telemetry readings. They then modify these readings and 

race the cars again and thereby develop a better understanding of how 

cars work. In one of the largest mobile games based learning projects in 

the UK, the BBC have developed GCSE revision learning material in 

the form of mobile phone games, covering 150 questions in Maths, 

English, and Science ( BBC Bitesize Revision, 2008). Any student with 

a mobile phone can type in the website address, and then choose which 

revision material they want and it will be downloaded to their phone. 

Making games is considered to be one of the most creative activities. 

Many people and especially children love to play games and naturally 

want to design and develop their own ones. Not only playing games, 

but explicitly making games can be beneficial for children in many 

ways. It allows them to express their creativity, implement original 

ideas, and learn structured and logical thinking as well as gain media 

literacy and a deep understanding of computer technology r:r atim and 

Masuch, 2007). 

Limitations of Learning with Mobile Devices 

Although mobile learning has come a long way in leaps and bounds, 

there is one limiting factor that holds back its total acceptance as a 

learning medium when compared to normal sized personal computers 

or laptops. The size of mobile phones, which gives them this instant 

appeal to learners, is also in part responsible for its slow uptake for 

learning. According to Shudong and Higgins (2006), while mobile 

learning has met with some acceptance among educators and is increasingly 

being implemented, it will be necessary to solve the following 

problems if it is to become effective, accepted, and widely used. Due to 

the small screen size and limited resources of mobile phones, in uses of 

mobile phones for learning, there is not sufficient feedback for learners. 

It is difficult to develop content that will run on all mobile devices, 

even if technologies like Java, which are meant to be platform and operating 

system independent, are used. The cost of using mobile devices 

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can be quite significant, although the latest smart phones have built in 

Wi-Fi, which enables them to access content via the local hotspots or 

Wi-Fi access points on university campuses at no extra charge. This is 

particularly significant when it comes to using learning objects that may 

have multimedia content like video and graphics. The ability to acquire 

information about the user and his or her environment presents a 

unique ability to personalize the learning opportunity (Shudong and 

Higgins, 2006). However, there are significant ethical issues associated 

with this according to Lonsdale et al. (2003). Some of these issues are 

that context information needs to be collected with the full consent of 

the users and must be stored securely to prevent misuse by third parties. 

According to Sharples (2003), in terms of mobility, the 'aJ!)time, 

anywhere' capabilities of mobile devices encourage learning experiences 

outside of a teacher-managed classroom environment. Inside the classroom, 

mobile devices provide students with the capabilities to link to 

activities in the outside world that do not correspond with either the 

teacher's agenda or the curriculum. Both of these scenarios present 

significant challenges to conventional teaching practices. Vavoula 

(2004) also makes the point that learning is achieved over time and 

lifelong learners will need effective tools to record, organize, and reflect 

on their mobile learning experiences. The affordances and psychosocial 

limitations of a tool, not just its construction, must be examined critically 

before, during, and after integrating that tool into a learning environment. 

If used improperly, for example, the mobility of mobile devices 

can also be a barrier to learning. The personal nature and small 

size of mobile devices may hinder collaboration by isolating users from 

meaningful social interactions (Mandryk et al., 2001; Dieterle et al., 

2007). 

Health and Safety Issues with Mobile Learning 

The use of mobile phones has caused controversy in terms of the 

health risks it poses, particularly to children. In recent years there has 

been a rapid increase in the use of wireless communications devices, 

which include mobile phones, and a great deal of research has been 

carried out to investigate possible biological or human health effects 

resulting from the use of these devices. The National Research Council 

(2008) commissioned research concluded in their executive summary 

that there is a need for experiments focusing on possible adverse radio 

frequency (RF) effects identified by changes in electroencephalogram 

(measurement and recording of electrical activity in different parts of 

41 

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the brain) activity as well as a need to include an increased number of 

subjects. They also concluded that little or no information is available 

on possible neurophysiological (the physiology of the nervous system) 

effects developing during long-term exposure to RF fields. Risks of 

exposure to RF fields in elderly volunteers are not well explored and 

there is a continuing need for experiments focusing on possible adverse 

RF effects identified by changes in cognitive performance functions. 

There are essentially two camps of researchers with differing "etidence" 

based claims that mobile phone usage is, on one hand, harmful and, on 

the other hand, not harmful. According to an article on the BBC website 

(BBC, 1999a), researchers in Sweden found that just two minutes 

of exposure to energy waves from a handset can disable a defence 

mechanism in the body designed to prevent harmful proteins and toxins 

in the blood from entering the brain. Once the proteins enter brain 

tissue there is a higher risk of brain and nerve diseases such as Alzheimer's, 

Parkinson's and multiple sclerosis developing. Another article, 

again on the BBC website, BBC (1999b), claims that mobile phone 

usage is linked to memory loss and that leading scientists are cutting 

down or modifying their personal use of mobile phones. An article on 

the BBC website (BBC, 1998) claims that one of the national newspapers 

in the UK, the "The Daily Mail", carried a front page splash on a 

study carried out by military scientists at the Defence Evaluation and 

Research Agency that suggested that mobile phone signals disrupt part 

of the brain which controls memory and learning. It also claims that 

recent studies have already found mobile phones can cause a rise in 

blood pressure and may harm pregnant women and that they have been 

linked with brain tumours, cancer, headaches, and tiredness. Although 

the use of mobile phones has already been linked to headaches, fatigue, 

damage to the immune system, and cancer, there is, however, no firm 

evidence yet that mobile phones cause any harm. There is an article on 

the Consumer Affairs (2005) website that claims that a Swedish study 

found that users of digital phones in rural areas may be at greater risk 

of brain cancer. Its authors say the link is troubling, although they acknowledge 

that the amount of data is small and wider research is 

needed to amplify the findings. There is also a related article by Anderson 

(2006) that claims that the use of mobile phones over a long period 

of time can raise the risk of brain tumours, according to a Swedish 

study. According to this report, researchers at the Swedish National 

Institute for Working Life looked at mobile phone usage of 2,200 cancer 

patients and an equal number of healthy control cases. Of the can- 

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cer patients, aged between 20 and 80 years, 905 had a malignant brain 

tumour and about a tenth of them (85 patients) were also heavy users 

of mobile phones. This research, which was published in the International 

Archives of Occupational and Environmental Health, defined 

heavy use as 2000 plus hours, which corresponds to 10 years use in the 

work place for one hour per day. Early use was defmed as having begun 

to use a mobile phone before the age of 20 years. There was also 

shown to be a marked increase in the risk of a tumour developing on 

the side of the head where the telephone was generally used, said the 

study, which took into account factors such as smoking habits, working 

history, and exposure to other agents. Kjell Mild, who led the study, 

said the figures meant that heavy users of mobile phones had a 240 

percent increased risk of a malignant tumour on the side of the head 

the phone is used. He said his study was the biggest yet to look at longterm 

users of the mobile phone, which has been around in Sweden in a 

portable form since 1984, longer than in many other countries. 

According to the Institute of Engineering and Technology (2008), the 

balance of scientific evidence to date still does not indicate that harmful 

effects occur in humans due to low-level exposure to electric and magnetic 

fields (EMF). This conclusion remains the same as that reached in 

its previous position statements, the last being in May 2006, and has 

not been substantially altered by the peer-reviewed literature published 

in the past two years. Krewski et al. (2003), from the Royal Society of 

Canada's (RSC) Expert Panel on potential health risks of radiofrequency 

fields from wireless telecommunication devices, reviewed various 

research fmdings on new data on dosimetry (measure of ionizing 

radiation) and exposure assessment, thermoregulation, biological effects 

such as enzyme induction, and toxicological effects, including genotoxicity 

(deleterious action on a cell genetic material affecting its integrity), 

carcinogenicity (potential to cause cancer), and testicular and reproductive 

outcomes. Epidemiological (medical studies concerned with the 

incidence and distribution of diseases and other factors relating to 

health) studies of mobile phone users and occupationally exposed 

populations were examined, along with human and animal studies of 

neurological and behavioral effects. All of the authoritative reviews 

completed within the last two years of their report concluded that there 

was no clear evidence of adverse health effects associated with RF 

fields. At the same time, these same reviews supported the need for 

further research to clarify the possible associations between RF fields 

and adverse health outcomes that have appeared in some reports. In 

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the past five years, the mobile phone health issue has been subject to 

no less than 30 scientific reviews carried out within the UK and overseas. 

In all cases, these reviews have come to similar conclusions, that 

"There have been no adverse health consequences established from 

exposure to RF fields at levels below the international guidelines on 

exposure limits published by the International Commission on Non 

Ionizing Radiation Protection." Despite this some local residents remain 

very concerned about perceived health effects when mobile 

phone base stations are built close to their homes or near their children's 

schools. 

Summary 

Mobile learning has come a long way and is beginning to make significant 

inroads into main stream learning using technologies like SMS and 

games in programmes like the BBC Bytesize used by GCSE students 

for revision using games. It is also evident that podcasting is becoming 

very popular with hundreds of universities joining iTunes U, an Apple 

online shop for downloading free content supplied by universities. 

Games based learning; SMS and IM are also areas with significant 

promise in the adoption of mobile learning. Mobile technologies can 

effectively support a wide range of activities for learners of all ages 

(Naismith et aI., 2004). Mobile technologies provide for each student to 

have a personal interaction with the technology in an authentic and 

appropriate context of use. All the research that has been done with 

mobile learning has been on the whole very positive, and researchers 

and academics agree that if used appropriately, in games based learning, 

for example, they can encourage interest in learning as the students find 

them to be fun and engaging. There are however many concerns about 

the use of mobile devices in learning, ranging from the size of the devices' 

screens, the cost, the new pedagogies which need to be developed, 

and the health scares like cancer, memory loss and brain tumors 

attributed to the use of mobile devices. It is likely that the use of mobile 

learning will follow the same patterns as that of e-Learning, with some 

HEIs adopting it readily, while others still prevaricate when it comes to 

fully adopting it. I think that if it can be proved that introducing mobile 

learning is guaranteed to raise and retain student numbers, then almost 

all recruitment universities, as opposed to selection universities, will 

readily adopt mobile learning. It has already been shown that students 

love to use new technologies in their learning and are very agreeable to 

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the use of SMS for sending them alerts about time tabling, course work 

deadlines, change of lecture rooms, et cetera, rather than alerts by email 

or notice boards. 

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Mobile Learning DeMystifled 

Author 

Dr James Kadirire read Computer Science at the 

University of Cambridge, Fitzwilliam College, in 

1992. He then got a PhD in Computer Science from 

University College London in 1996, on Dynamic 

Multicast Routing in the Asynchronous Transfer 

Mode (ATM) Environment. James then worked in 

the commercial world, mainly in software design and development, 

including 2 years from 1999 to 2001 at BT Adastral Park, where he 

worked as a software scientist/research engineer in distributed systems. 

He joined Anglia Ruskin University, in Cambridge, England, in 2002, 

where he is employed full time, as a senior lecturer. James' research 

interests include: 

• ATM/IP Multicasting/Routing 

• Mobile systems/GSM/GPRS/UMTS 

• Wireless LANS 

• Service/Resource Discovery 

• Digital communications/computer networking 

• Distributed systems and security 

• e-Learning and m-Learning 

• Web/Internet technologies and protocols 

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Guy, R (Ed.). (2009). 



Chapter 3 

Selecting Appropriate Technologies for 

Mobile Teaching and Learning 

Jeremy Dickerson and J. B. Browning 

Introduction 

Mobile handheld technologies are pervasive throughout most of the 

world. Take a quick glance across an airport terminal, coffee shop, or 

student lounge in nearly any country and you will see a myriad of models, 

applications, and people using these devices. Mobile technologies 

have become an integral part of businesses and of personal lives, freeing 

users from the constraints and limitations of conventional computing 

technologies such as desktops and laptops. Many people choose to 

complement their home computers with mobile technologies, owning a 

mobile device, a laptop and/or desktop. Size, weight, reliability, battery 

power, Internet accessibility, reasonable costs, and reliable ubiquitous 

networks have made mobile devices the technology of choice for people 

who need quick and easy anywhere, anytime communication. There 

are numerous of mobile device options for a society on the move. 

In his book Technological Change (1970), Harvard University Professor of 

Technology E. G. Mesthene asked if the advancement of computers 

means the end of freedom or a bold new beginning. Nearly forty years 

later, this question has a variety of answers and perspectives. For education, 

computer technologies have allowed teaching and learning to 

transcend many limitations and barriers. Picciano (2001) describes distance 

education as a way to overcome problems with time and space - 

two overarching categories which have historically divided students and 

knowledge. The work 'desk' for many students and members of the 

adult workforce has become a virtual place thanks to increased mobility 

and decreased costs of information technologies (Baldauf & Stair, 

2008) . Web-based distance education has shown to be as effective as 

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face-to-face instruction in a wide array of instructional settings (Browning, 

1999). In 2006, it was reported that approximately 3.5 million students 

took at least one online course during fall 2005. It is estimated 

that twenty percent of all U.S. higher education students were taking at 

least one online course in the fall of 2006 (Allen & Seaman, 2006). With 

the apparent success and popularity of online delivery, distance education 

via mobile technologies is yet another revolution in the attempt at 

diminishing conventional constraints without compromising quality. 

Educators have integrated electronic media, communication and information 

technologies for many years. From 16mm ftlms of the ftrst 

part of the 20th century to the web-based courses and online degrees of 

today, appropriate and innovative selection of content delivery technologies 

have been vital in education. The last decade of the twentieth 

century was marked by the evolution of the World Wide Web and the 

personal computer, and the ftrst decade of the twenty-ftrst century is 

being dramatically shaped by global networking and the exponential 

growth of mobile technologies (Shelly, Cashman, Gunter, & Gunter, 

2008). In the 1980s and 1990s, education was transformed though the 

evolution of instructional technologies focusing on modernizing educational 

content delivery around the use of computer technologies and 

software applications. In the 2000s, the fteld of education began teaching 

and learning in online environments and focused through the use of 

static, hand-crafted instructional web sites as well as the integration of 

fully-online course management systems such as BlackBoard, MoodIe 

& Sakai. This 'instruction-forward' progression with technology in 

education has been an asset for insuring the evolution of teaching and 

learning and has helped the fteld of education grow in unanticipated 

ways. 

The learners of tomorrow will continue to seek the most flexible and 

easily accessible methods for receiving instruction. A recent study by 

Schmidt, Hodge, Dickerson, and Ellis (2008) suggests that traditional 

college students who were not encumbered by distance selected online 

courses because of the flexibility the format provides, even if they lived 

on or near a college campus where face-to-face classes were available. 

Flexibility is achieved via distance-defying and time-defying technologies 

and instructional methods. The term "synchronicity" refers to 

whether or not communication is occurring in real-time (Cheng, Lehman, 

& Reynolds, 1991). Students want and/or need the ability to learn 

asynchronously even if they are not inhibited by distance so that they 

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Selecting Appropriate Technologies for Mobile Teaching and Learning 

may match their time to their opportunity to learn. Mobile technologies 

provide further educational solutions to the issues of both time and 

distance. 

Given Prensky's (2004) proposition that, in many parts of the world, 

mobile communication device ownership outweighs that of personal 

computers sometimes by as much as five or ten to one (especially in 

less developed areas), it is sensible to begin teaching educators about 

the use of mobile technology learning environments. Many believe that 

mobile technology instruction will soon become as common as online 

instruction delivered via a PC and that handheld devices will become an 

inextricable component in secondary, post-secondary, adult learning, 

and corporate training environments. This immediately conjures several 

questions: 

1. What does an educator need to know about mobile technology 

instruction? 

2. How does the thought process change through the use of a mobile 

technology delivery? 

3. Where does the mobile technology instructor begin in his/her 

analysis? 

4. With so many technologies and capabilities on the market, how 

does one go about selecting a mobile technology? 

Those who design and deliver traditional web-based courses are often 

referred to as 'online instructors' so perhaps those who teach using mobile 

technologies may be referred to in the future as 'mobile technology instructors.' 

It is significant to make some delineation early in this chapter. The 

authors recognize the apparent mobility of laptop computers and tablet 

PCs. Even though these are mobile devices, this chapter serves as 

springboard for designers and educators seeking the extreme mobility 

of handheld technologies. For this chapter, the term hlobile' technology 

device will imply small-screen handheld technologies, such as smart 

phones, PDAs, and MP3 players, and the wide array of functionalities 

these devices may utilize in addition to the integration of the World 

Wide Web and various software applications. 

This chapter provides a brief outline of various mobile technologies 

and stresses the analysis phase of the instructional design process. Additionally, 

the chapter concludes by providing a method for assessing 

mobile technologies for teaching and learning. 

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Brief Overview of Content Delivery Technologies 

Campbell and Oblinger (2007) suggest that selecting models and strategies 

for e-Iearning is one of the top five issues in higher education. 

There are a wide variety of models, features, software, hardware, and 

networking options available that may be used in any personal or educational 

mobile environment. In order for the material in this chapter 

to transcend specific brands, this section overviews types of techniques 

used in mobile technology instruction and provides information that 

would help an educator understand if a technique would be effective 

and feasible. Generally, mobile instruction consists of a variety of 

video, audio, and/or text into a format in which a student could receive 

and respond on a mobile device. Small screen size is a design limitation 

for content requiring visual display such as video and text; therefore, 

content must be adapted for delivery on mobile devices. An instructor 

must consider the nature of the mobile learner and the delivery constraints 

of small technology devices and design instruction into smaller 

chunks of material. 

Commercial and open source software is available for designing, developing, 

and delivering content for use on small-screen mobile devices. 

Such software packages allow an instructor to create content into mobile-ready 

(mobilized) format. Many commercial vendors of mobile 

technologies offer implementation strategies for teaching and learning 

in a mobile environment. Additionally, open-source tools can be found 

by searching the Internet. Video, audio, and text-based content delivery 

technologies can be described in numerous ways. Please refer to the list 

in the Appendix for examples of websites which offer information and 

products on mobile instruction technologies. The technologies discussed 

in this chapter are not all inclusive, and the discussion is meant 

to provide an overview to serve as a departure point for mobile technology 

instructors to begin their investigation, design, and delivery of 

mobilized content. 

Video Delivery Technologies 

Video technologies have the ability to enhance and bring to life theories 

and personalities. From displaying a picture or graphic of a concept, to 

showing the facial expressions of a student during a conversation, few 

can dispute the impact of the use of video. Table 1 summarizes com- 

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mon video-based techniques which are staples of mobile instruction 

environments. 

Table 1: Video delivery technologies for mobile instruction 

Video Delivery Technologies 

Video pod casting 

(Vodcasti ng) 

Screen recordings 

Screen casti ng 

Video files runni ng from a 

website 

Still image display 

Video conferencing 

Video Mail 

Brief Overv iew 

Pre-recording of video andlor audio for 

playback on computers. portable MP3 

players, and other handheld devices 

Recording what IS on your screen for later 

viewing (as video, flash, etc.) and displayed 

to demonstrate a computer-based example 

Displaying in real-time what is on your 

screen to other comp uters 

Conversion of video to flash video or similar 

"web-sized" format 

Motionless digital images which enhance 

instruction and are fomnatted for small 

screen display 

Fully interactive video, two-way or multipoint 

conference 

Sending video communications via email 

systems to another user or group 

Audio Delivery Technologies 

The audio delivery technologies section overviews the use of audio fties 

and audio communication tools. These technologies include a variety of 

both synchronous and asynchronous capabilities. From traditional 

point-to-point calling with mobile phones to setting up an instructional 

audio stream, audio technologies have tremendous potential to impact 

the mobile technology instruction environment. 

Table 2' Audio delivery technologies for mobile instruction 

Audio Delivery Technologies 

Point-to-poi nt calling 

Confere nce ca IIi ng 

Internet Protocol calling 

Audio pod casting 

I nternet Protocol streami ng of 

content delivery 

Audio mail 

Brief Overview 

One audio-capable device to another in 

real-time 

More tha n two a udi o-capable devi ces in 

si multa neous use 

Calling from computerto computer or 

computer to phone using Internet protocol 

instead of phone networks 

Pre-recordi ng of a udi 0 fo r down loadable 

playback on computers, portable MP3 

players and other handheld devices 

Audio "streamed" to the user over a 

network po rt, vi a a p layer. Content ca n be 

pre-recorded or Ii ve-streamed to users 

Broadcast audi 0 messages to others 

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Text Delivery Technologies 

The electronic display of text in both static form and for conversational 

purposes or information sharing is common in online and mobile technology 

environments. Posting static text is a staple for any distance 

education format as is sending/receiving email. Mobile technology 

instructors can take advantage of simple uses of text to supplement 

instruction and capitalize on students' familiarity with text messaging, 

blogs, micro-blogs, wikis, and instant messaging. 

Table 3: Text delivery technologies for mobile instruction 

Text Delivery 

Technologies 

Text-based content via web pages 

Text-based content via email 

Text messaging 

Instant messaging 

Wikis 

Blogs/microblogs 

Brief Overv iew 

Website formatted for small-screen use 

Email designed for small screen device. 

perhaps in an abbreviated format and 

kept brief for mobile consumption and 

quick loadi ng for delivery via an Internet 

email client 

Messages sent. generally using 

shortcut notation based on limitations of 

mobile phone keypad. Sent and 

received via phone technology instead 

of Internet email 

Person to person and mUlti-person text, 

audio, and video are options. but this 

item generally is text only. Real time 

text transfer between users 

Website where multiple authors can 

change and adapt page content. Can 

be password protected or open 

Non-sequential in nature, anything the 

user has riQhts to can be chanQed 

Website where a specific author (or 

authors) creates sequential posts. 

Posts are shown by date 

(microblogs are based on limited 

characters - ex. texti nQ) 

Most of the aforementioned technologies cannot stand alone as a sole 

medium for content delivery. The authors recommend a multitechnology 

approach for instructors seeking to mobilize their content. 

While using a multi-technology approach compounds issues of technical 

sophistication and literacy, it is through the combination of multiple 

delivery technologies and methods that students will receive the greatest 

impact from the instruction. Fortunately, we live in a time where 

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many of these technologies are commonly used for personal communication 

and leisure. Texts, emails, wikis, blogs, and phone calls are all 

extremely ordinary communication tools. The task is now to make use 

of these existing tools, perhaps add more sophisticated technologies, 

and adapt our instructional design to effectively teach. 

Selecting Mobile Technologies for Instruction 

Analysis of Mobile 

Technologies for 

Instructional Purposes 

Developing Instruction 

for Mobile Technology 

Envi ron ments 

Figure 1. Components for Instructional Det'elopment 

"Instructional design theory offers explicit guidance on how to better 

help people learn and develop" (Reigeluth, 1999, p. 5). As indicated in 

Figure 1, by examining the learners, the type of learning, and the technologies 

involved we can analyze and improve the process of developing 

instruction for mobile technology environments. There are many 

common components to an instructional design system. Instructional 

design models typically involve analysis, strategy, evaluation, and reflection. 

Smith and Ragan (1993) discuss the analysis phase of instructional 

design at length, describing front-end analysis as containing analysis of 

the instructional context, the learners, and the learning task. Further, 

Smith and Ragan add that front-end analysis is often underutilized or 

under appreciated by designers of instruction. Planning instruction for 

mobile technology instruction should be preceded by front-end analysis 

of several key components of the instructional environment: the learner 

characteristics, the variety of learning and the mobile technologies 

which could be used for instruction. These three components have the 

potential to provide a mobile technology instructor information that 

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can shape an effective learning environment and assist in the instructional 

decision making process. This section asks: 

1. Who is the learner and what do they bring to the instructional environment? 

2. What needs to be learned as a result of the instruction and how 

does that affect mobile technology selection? 

3. Which mobile technology is suitable for the instructional delivery 

and/ or assessment needed for learning to occur? 

Learner Analysis 

Recently, while presenting at an international educational technology 

conference, one of the authors was speaking on the topic of distance 

education and the use of course management systems. A professor in 

the audience from South Africa came up after the talk, eager to discuss 

the topic at length. Intrigued, the South African Professor stated that 

he wanted to help schools in his country use course management systems 

to deliver content, but he felt that the lack of computer ownership 

and home Internet connections would be a barrier. He believed the 

most common technology among his students was mobile phones and 

that 'texting' educational content might have a greater impact on those 

students than web-based courses. This real-life scenario is a testament 

to the potential of mobile education and to the value of knowing the 

learners in the instructional context. 

Mobile technology instruction is extremely sensitive to the conditions 

of the learner. Creating an effective learning experience begins with 

understanding the learner and the characteristics they possess before 

entering the learning scenario. Smith and Ragan (1993) suggest that 

some of the elements that could be helpful for in understanding learners 

include psychosocial, cognitive, and physiological characteristics. 

1. Psychosocial Characteristics. Knowing who you are teaching can 

provide important data for consideration. What are the social 

demographics that could influence their performance during instruction? 

Age, work experiences, educational experiences, socioeconomic 

status, gender, and cultural backgrounds are examples of 

demographics which may impact your instructional design of instruction. 

Does the learner use mobile technologies at work? Are 

they in an age range where mobile technology use is popular and 

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socially expected? Is wealth-level a factor in technology ownership? 

Do learners live in rural areas where mobile technologjesl 

connectivity may not be accessible? 

2. Cognitive Characteristics. What knowledge, skills and dispositions 

do students bring into the learning environment? What developmental 

level are they at relevant to the suggested curricula? What 

aptitudes or abilities do they possess which could influence how or 

what you teach? Do they have technical skills such as sending or 

receiving audio, video, or text? Do they have the aptitude necessary 

to learn such tasks? 

3. Physiologjcal Characteristics. What health conditions might impact 

learning? How might these health conditions factor into the physical 

aspects of the learning environment or into the assessment 

methods used? With mobile technologjes, vision, hearing ability, 

and dexterity can influence learning. Does the learner have problems 

seeing small interfaces? Do they have the finger dexterity to 

use small keyboards? Can they hear well enough while using a mobile 

technology device to be able to listen to audio lectures? 

Instructors should consider the wide range of psychosocial, cognitive, 

and physiologjcal characteristics which can influence the mobile technology 

instructional environment. Without invading privacy, instructors 

should develop surveys or questionnaires that allow learners to anonymously 

volunteer personal information that could assist instructional 

development. The design of instruments and collection of data can take 

time, but will reward the instructor through student success and translate 

into a more customized learning experience. 

Learning styles and preferences are also aspects that should be considered 

when designing instruction in a mobile technology learning environment. 

Instructors should evaluate how the selection of different 

technologjes can enhance or inhibit student achievement within the 

context of learning styles or preferences. This consideration should 

occur before integrating technology into instruction. While some technologjes 

naturally incorporate multiple learning modalities (such as 

smart phones - visual, auditory, etc.), others may have limitations that 

can affect student achievement. For example, using pre-recorded audio 

clips of lectures that learners may download on an MP3 player as a sole 

means of instructional delivery would clearly create a deficit for many 

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learners who need other means of input (such as visual stimulation) and 

interaction (such as discussion). 

There are many learning style assessment methods in the research literature. 

Fleming (1995) proposes the 'VARK' method of analyzing 

learning preferences based on brain research in the areas of visual, aural, 

read/write & kinesthetic learning. Kolb (1981) discusses learning 

styles and describes them within the general framework of doing, thinking, 

feeling, and watching. These, as well as others, can provide insight 

into learner preferences for receiving instruction. Planning for differences 

in learning styles during the design and development stages of 

instructional planning promotes better decision making concerning 

technology selection. Improved decision making typically translates into 

higher student success because of an instructor's ability to better meet 

the needs learners. 

Analysis of Types of Learning 

In their book Principles of Instructional Design, Gagne, Briggs, and Wagner 

(1992) pose the question, ''What is to be learned?" Simple, but many 

instructors fill lessons full of student activities each day without concretely 

defining what exactly is supposed to be learned as a result of the 

instruction. Instructional theorists suggest that all learning can be categorized 

as one of several common types. Gagne, Briggs, and Wager, 

states that there are five categories of learning: 

1. Intellectual Skills 

2. Cognitive Strategies 

3. Verbal Information/Knowledge 

4. Motor Skills 

5. Attitudes 

In The Systemic Design ojInstruction, Dick and Carey (1996) describe these 

categories oflearning as: 

1. Psychomotor Skills 

2. Intellectual Skills 

3. Verbal Information/Knowledge 

4. Attitudes 

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These lists are similar with the exception of the combination of intellectual 

skills with cognitive strategies. A basic synopsis of these types of 

learning follows: 

1. Psychomotor skill learning involves physical and mental activity to 

perform a physical action or undertaking. 

2. Intellectual skill learning involves various levels of problem solving, 

developing concrete and abstract concepts, and applying rules (or 

other cognitive strategies). 

3. Verbal information is the recitation, listing, or individual stating of 

specific defined information at the presence of a stimulus without 

problem solving or critical thinking. 

4. Attitudes are emotion-driven human dispositions resulting in decision 

making beliefs and judgments about situations, people, places, 

or things. 

Mobile technology instructors must determine both what is to be 

learned and whether or not the desired learning outcome can be successfully 

achieved in a mobile technology environment. What instruction, 

interaction, communication, and assessment should to occur to 

effectively teach an intellectual skill, attitude, psychomotor skills, or 

verbal information? Can traditional instructional methods for a learning 

outcome be used, not used, or minimally modified for use in a mobile 

technology environment? 

Content which is to be taught via mobile technologies should be categorized 

as one of these types of learning. Instruction can then be designed 

and developed to effectively teach the learning objectives. The 

four varieties/types of learning have distinctions between one another 

that set the stage for appropriate media selection - especially within the 

context of mobile technologies. Consider and compare the differences 

found in the following examples; 

o 

o 

o 

Teaching the memorization of the periodic table (verbal information) 

Teaching how to diagram sentences (cognitive strategy) 

Teaching how to correctly perform a push-up (psychomotor skill) 

Which of these examples could be effectively and adequately taught via 

mobile technologies? Which technologies would be appropriate and 

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how would that affect your instructional methods and assessment strategy? 

Analysis of Mobile Technologies for Instructional 

Purposes 

Selecting technologies without consideration for all of the factors 

surrounding their implementation can result in frustration, 

disappointment, and most critically, low student performance and 

achievement. Selecting inappropriate technologies can also lead to poor 

student and teacher dispositions towards a technology because of 

failure or misuse. Successful implementation and integration of technology 

begins with informed decision making. Having lead and/or 

assisted in dozens of technology integration projects, the authors cannot 

stress enough the importance of conducting a thorough investigation 

of the people, policies, and logistical issues concerning technology 

enhanced instruction. Obviously, unexpected problems will occur no 

matter how much work is done, but many pitfalls will be averted if the 

right questions are asked in the beginning. 

Instructors should seek answers to many questions prior to implementation 

of mobile instruction. When well-informed, a mobile technology 

instructor can understand exactly what will be required to successfully 

implement mobile technologies into their instruction. Asking the right 

questions will yield a current state vs. desired state framework, informing 

the instructor of what is needed for success mobile technology 

integration. 

Asking the Right Questions: An Assessment Rubric 

The issues surrounding mobile technologies can be overwhelming for 

an instructor in the beginning stages of their planning process. Understanding 

student, instructor, and organizational variables is significant 

for instructional planning and can provide data that can direct training, 

budget development, funding, grant writing, and project timelines, 

among other important issues. 

Table four is a tool which can be used as a worksheet for analyzing and 

selecting mobile technologies for instruction. Consideration of the 

concepts in Table four will help determine if a technological delivery 

method is viable, reasonable, and appropriate for the instructor, student, 

and curriculum. This one-page document is designed to be a sim- 

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pIe check-list style tool which covers key topics and informs the user of 

the instructional scenario. Intended for use by a wide scope of individuals, 

the use of Table four may also lead to more questions, further 

illuminating the options and issues involved in the selection process. 

This table includes all individual issues discussed earlier in the chapter 

and allows the reader to compare each technology to the others based 

on the reader's individual scenario. The areas of consideration are 

grouped by 'personal' and 'instructional' headings so that the reader 

may quickly understand the general state of the issues surrounding the 

technology. 

Instructions for Using Table Four (Assessment Rubric For 

Mobile Technology Selection And Readiness): 

When using the table, an instructor should rate each area as necessary. 

1. Is the desired technology available? (yes/no/need data) 

2. Is there instructor and student proficiency with the desired technology? 

(yes/no/need data) 

3. Is technical support available for the instructor and student? 


4. Are there costs or service plans necessary which will be a problem? 


5. Is the learning variety suitable and feasible for the mobile technology 

which has been chosen? (yes/no/need data) 

6. What learning styles are addressed? (as per adopted method and 

theory) 

7. Will communication be synchronous, asynchronous, or combination? 

8. What is the communication flow and direction? (teacher to students, 

student to teacher, student to student, combination) 

This table should be used as a readiness inventory for each mobile 

technology that is an option for the instructor, allowing a quick understanding 

of the current conditions vs. desired conditions as well as the 

deficiencies which need to be addressed in order to implement a selected 

technology. 

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o 

cC" 

"" N" 

~ 

~ 

CJ 

o 

~ ...... 

rv 

~ Table 4: Assessment Rubric for Mobile Technology Selection and Readiness v 1.0 Dickerson & Browning 2008 

Areas fo r Consideration 

Personal Concerns 

Instructional Concerns 

Mobile Availa bility" Technical Technical Costl Appropri ate for Learning Styles Synchronicity 

Tecbnologlf Proficie ncy* Support Service Type of Addressed 

.. Availa bility" Prohi bitive" Learning 

Video p odcasting 

Screen casting 

Screen recordin gs 

Website based 

video files 

Display of still 

images 

Video 

confere ncing 

Video mail 

Poi nt-t 0- poi nt 

calling 

Conference 

calling 

IP calling 

Audio p odcasting 

IP ra dio streami ng 

content delive rv 

Audio mail 

Text-based 

content via 

webpages 

Text-based 

content vi a Email 

Text messaging 

Instant messagi ng 

Wikis 

Blogs 

Micro-blogs 

.. = Instructor a nd/o r student 

Communication 

Direction 8. Flow 

:;l 

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Example Use of Assessment Rubric: Teacher In-Service 

Training Delivered Via Mobile Technologies Scenario 

The scenario for the following example is based around designing and 

delivering an in-service class for licensed teachers. Teachers will receive 

renewal credit for 10 contact hours over the duration of the course. 

The format of the course will be hybrid in nature and consist of "lecture" 

and new information received by the students via mobile phone 

or small screen device. Work products that students produce and some, 

but not all, teacher to student and student to class interactions will be 

via mobile phone, but lager products will be via traditional PC (hybrid 

format). 

The following questions 1-8 and Table five are an example of use of 

the Assessment Rubric for Mobile Technology Selection and Readiness 

in a teacher in-service scenario. 

When using the table, an instructor should rate each area as necessary. 

1. Is the technology available? (yes, teachers who participate must 

have a web-enabled cell phone or PDA with wifi and daily wifi access) 

2. Is there instructor and student proficiency? (yes) 

3. Is technical support available for the instructor and student? (yes) 

4. Are there costs or service plans necessary which will be a problem? 

(yes, plans are available) 

5. Is the learning variety suitable and feasible for the mobile technology 

which has been chosen? (yes) 

6. What learning styles are addressed? (Visual, Aural, and Read/write) 

7. Will communication be synchronous, asynchronous, or combination? 

(combo) 

8. What is the communication flow and direction? (combination) 

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~ Table 5: Example use of Assessment Rubric for Mobile Technology Selection and Readiness v 1_u Dickerson & Browning 2uu8 

- Teacber In-Service Training Scenario 

Areas fo r Consideration 

Person al Co ncerns 

Instructional Concerns 

!!!!.obile Availability* Technical Technical Costl Appropriate Lea rni ng Styles Synchronicity Communication 

Technologlt Proficie ncy* Support Service for Type of Addressed Direction 8. Flow 

.. Availa bility* Prohibitive* Learning 

Video p odcasting Yes Yes No No Yes Visuall Aural No One-way 

Screen casting Need data Need data Need data No Need data Need data Need data Need data 

Screen recordings Yes Yes No No Yes Visual No One-way 

Website based Yes Need data Need data No Need data Need data Need data Need data 

video files 

Display of still Yes Yes No No Yes Visual No One-way 

imaQes 

Video No N/A N/A N/A N/A NlA N/A N/A 

confere ncing 

Video mail No N/A N/A N/A N/A NlA N/A N/A 

Point-to-point No N/A N/A N/A N/A Aural Yes N/A 

calling 

Conference No N/A N/A N/A N/A Aural Yes N/A 

callinQ 

IP calling No N/A N/A N/A N/A NlA N/A N/A 

Audio p odcasting Yes Yes Yes No Yes Aural No One-way 

IP radio streaming No N/A N/A N/A N/A NlA N/A N/A 

content de live ry 

Audio mail Yes Need data Yes No Need data Aural No Two-way 

Text-based Yes Yes Yes No Yes Visual No One-way 

content via 

WebPages 

Text-based Yes Need data Yes No No NlA N/A N/A 

content via Email 

Text messaging No Need data Yes No No Visual Yes N/A 

Instant messaging No Need data Yes No No NlA N/A N/A 

Wikis Yes Yes Yes No Yes Visual Yes Two-way 

Blogs Yes Need data Yes No N/A Visual No One-Way 

Micro-blogs Yes Yes Yes No Yes Visual No Two-way 

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By examining the results of ftndings from the course developer in Table 

five, a user could define areas for potential problems and identify 

areas that might not have been addressed properly (such as levels of 

support for some technologies or limited variety in addressing learning 

styles.). When properly completed, the table can provide a quick snapshot 

of strengths and weaknesses such that an implementer of mobile 

learning can further reftne the course for greater potential success. 

Review of Key Questions Discussed in Chapter 

Addressing the Learner 

1. What psychological characteristics of the learner could affect the 

use of mobile technologies? 

2. What physiological characteristics of the learner could affect the 

use of mobile technologies? 

3. What cognitive characteristics of the learner could affect the use of 

mobile technologies? 

4. What learning styles are being incorporated with the use of this 

technology? 

Content Appropriateness 

1. What variety of learning is trying to be conveyed via mobile technology? 

2. Is the material suitable for via mobile format delivery? 

3. Can I assess this variety oflearning via the mobile format? 

4. Can the technology do what is necessary for effective instruction? 

5. Are their advantages or disadvantages to delivering the content? 

6. Can the given capabilities of the technology enhance or encumber 

the learning process? 

Mobile Technological Capabilities 

1. Which mobile technological capabilities are available? 

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2. Which mobile technological capabilities are needed for effective 

instruction? 

3. Does the mobile technology you desire to use have the synchronicity 

aspects you need to be effective? 

4. Does the technology provide the flow and direction of communication 

necessary for effective delivery and assessment? 

A vai/abi/ity of Resources 

1. Does the instructor have the necessary hardware and/or software? 

2. If not, are there funds available to purchase software or equipment? 

3. Does the instructor have easy access or is the process cumbersome? 

4. Is there sufficient bandwidth for running any necessary websites, 

video, or audio fties? 

5. Are security policies too restrictive for the delivery method? 

6. Are their support personnel (internal and/or outsourced) available 

to assist in inevitable technological problems? 

7. Will the instructor or the students be on their own in the event of a 

technical problem? 

8. Can instruction be made flexible around support problems? 

Technological Proficiency of the Instructor & Students 

1. Do the instructor & students have the technological competence to 

work with the delivery technology? 

2. Are the instructor & students familiar with using mobile learning 

technologies? 

3. Is training required before implementation? 

4. Are the instructors & students versed enough to solve (at least 

minimal) problems commonly associated with consumer-grade 

technologies? 

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Conclusion 

It is interesting to note how far technology has come in just a few years 

in terms of size, cost, power, and availability. Additionally, it is equally 

amazing how far society has advanced in technical skills, general literacy, 

daily use, and ownership. Inarguably, mobile technologies have 

changed the way we live and work. We are on only the cusp of seeing 

how mobile technologies will change the way we teach and learn. Mobile 

learning devices are expected to continue expanding in functionality 

and shrinking in physical size. There will also be more techniques 

used for designing and delivering instruction, and these must be studied 

and will require experimentation in order to determine ways to legitimize 

the field and ensure learner success and achievement. As students 

and employers demand flexible learning options, there will be more 

integration of mobile learning throughout secondary, post-secondary, 

and adult education environments. Those of us interested in this field 

should be mindful these propositions: 

1. Technology constantly changes 

2. Successful implementation requires being well read on 

trends / techniques 

3. Successful implementation requires being actively engaged with the 

tools 

4. Successful implementation requires networking with other professionals 

It is exciting to consider what education and training will look like in 

twenty years. Certainly we can expect it to be less place dependant, 

more flexible, more media rich, and perhaps better delivered in terms 

of how people best acquire knowledge. For example, if smaller chunks 

of information, delivered more frequently, are more effective as a 

teaching method than students sitting down for two hours of class, 

twice a week, then perhaps mobile learning offers as much in terms of 

improving delivery as it offers in terms of improving effectiveness. 

Revisiting the work of Mesthene (1970), the question still remains unanswered; 

will the advancement of computers mean the end of freedom 

or a bold new beginning? Has freedom been increased or decreased if 

we can tote the classroom around in our pocket? Has freedom increased 

or decreased if we can take classes while standing in line at a 

store? Has freedom increased or decreased if we get a call, text, or in- 

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stant message from our instructor at eight o'clock at night? These questions 

and many more must be answered as we face the unique problems 

and amazing opportunities of mobile teaching and learning. 

References 

Allen, E., & Seaman, J., (2006). Making the grade: Online education in the 

United States 2006. Needham, Massachusetts. Retrieved April 20th, 

2008 from http://www.sloan-c.org/publications/ survey /index.asp 

Baldauf, K., & Stair, R., (2008). Succeeding with technology, computer [Ystem 

concepts for real lift. Massachusetts: Thomson. 

Browning,]., (1999). Analysis of Concepts and Skills Acquisition 

Differences Between Web-delivered and Classroom-delivered 

Undergraduate Instructional Technology Courses. North Carolina 

State University, Raleigh, NC. 

Campbell,]. & Oblinger, D., (2007). Top ten teaching and learning 

issues, 2007. Educause QuarterlY. 30(3), 15-21. 

Dick, W. & Carey, L., (1996). The Systemic Design of Instruction 4th Edition. 

New York: Longman. 

Cheng, H., Lehman,]., & Reynolds, A. (1992). What do we know about 

asynchronous group computer-based distance learning? Educational 

Technology, 31(11), 16-19. 

Fleming, N. D. (1995). I'm different; not dumb. Modes oj presentation 

(V ARK) in the tertiary classroom, in Zelmer, A., (ed.) Research and 

Development in Higher Education, Proceedings of the 1995 

Annual Conference of the Higher Education and Research 

Development Society of Australasia (HERDSA). Volume 18, pp. 

308 - 313. 

Gagne, R., Briggs, L., & Wagner, W., (1992). Principles oJinstructional 

design. Orlando: Harcourt Brace. 

Kolb, D. (1981). Learning styles and disciplinary differences. In 

Chickering, A., (ed.) Modern American College. San Francisco: Jossey 

Bass. 

Mesthene, E. (1970). Technological change: Its impact on man and sociery. New 

York: New American Library. 

Picciano, A. (2001). Distance Learning: making connections across time and 

space. Upper Saddle River, NJ: Merrill, Prentice Hall. 

Prensky, M. (2004). What Can You Learn From A Cell Phone? - Almost 

Airy thing! Retrieved April 25th, 2008 from 

http://www.marcprensky.com/writing/Prensky- 

Whac Can_ Y ou_Learn_F rom_a_ Cell_Phone-FIN AL.pdf. 

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Reigeluth, C. (1999). Instructional design theories and models: A new paradigm 

of instructional theory, Volume II. New Jersey: Lawrence Erlbaum. 

Smith, P. & Ragan, T. (1993). Instructional design 1st ed. New Jersey: 

Merrill Prentice Hall. 

Schmidt, S., Hodge, E., Dickerson, J., & Ellis, M. (2008). The Shrinking 

Face-to-Face College Classroom: Local Students, Distance 

Learners. (In Review). 

Shelly, G., Cashman, T., Gunter, G., & Gunter, R. (2008) Integrating 

technology and digital media in the classroom. Boston: Thomson. 

Appendix: Links to Additional Resources 

and Video, Audio, and Text Development Tools 

as of May 2008 

www.nchsoftware.com/screen 

/index.html 

www.camtasia.com 

www.debugmode.com/wink 

www.camstudio.org 

www.jumpcut.com 

www.eyespot.com 

www.moviemasher.com 

www.youtube.com 

www.blip.tv 

www.teachertube.com 

www.gtmp.org 

www.ivisit.com 

www.skype.com 

www.audacity.sourceforge.net/ 

www.winamp.com/ 

www.shoutcast.com/ 

www.icecast.org/ 

www.hotlava.com 

www.palm.com/ 

www.txt2day.com/ 

www.dashboard.aim.com/aim 

www.messenger.yahoo.com/ 

www.seedwiki.com 

www.wikipedia.com 

www.pbwiki.com 

www.blogger.com 

www.vlogblog.com/ 

www.twitter.com 

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Authors 

J. Burton Browning received his doctoral degree in 

Technology Education from North Carolina State 

University in 1999 and has been working since the 

late 1980's in the technology field on many innovative 

projects, such as the North Carolina Information 

Highway, The Odyssey Project, and several 

distance learning initiatives. In addition to these 

experiences, his scholarship activities include being a 

full-time professor and author. Dr. Browning teaches graduate and 

undergraduate courses in many subjects, including computer programming, 

computer security, computer networking, educational robotics, 

and systems design & analysis. His published works include several 

articles, and a book in its second edition, on computer programming - 

Design, Logic, and Programming with Python: A hands-on approach. 

He lives in Eastern North Carolina with his wife and six Siamese cats. 

Jeremy Dickerson is an assistant professor in the 

Department of Business and Information Technologies 

Education in the College of Education at 

East Carolina University. Dr. Dickerson has a doctoral 

degree in Technology Education with a focus 

on training and development and has over 10 years 

experience managing information technology systems 

and providing technical support. His current teaching, research 

and private consulting interests include computer applications training 

and integrating instructional design into technical courses to improve 

human performance in post-secondary and adult workforce education. 

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Guy, R (Ed.). (2009). 


Santa Rosa, California.: Infonning Science Press. (pp. 79-102). 

Chapter 4 

From Classical Mobile Learning to Mobile 

Web 2.0 Learning 

Chaka Chaka 

Introduction 

This chapter explores the evolution of mobile-based learning (M:BL) 

from classical mobile learning (m-Iearning) to Mobile Web 2.0 (m-Web 

2.0) learning in the context of informal leaning. Classical m-Iearning 

refers to the period when m-Iearning emerged as both a learning paradigm 

and a delivery mode. M-Web 2.0 learning is the era in which m 

learning incorporates and is influenced by Web 2.0 technologies. It is 

characterized by both mobility and Web 2.0 as part of its delivery and 

learning platform. On this basis, the chapter provides, first, a brief 

overview of classical m-Iearning and m-Web 2.0 learning. Second, it 

argues that both classical m-Iearning and m-Web 2.0 learning represent 

evolving technologies for teaching and learning in varying degrees. 

Third, it maintains that with the advent of classical m-Iearning and m 

Web 2.0 learning, there have emerged changing learners and changing 

learning approaches. Fourth and last, the chapter outlines future trends 

for, especially, m-Web 2.0 learning. 

Over the years d-Iearning (distance learning) has witnessed two major 

evolutionary developments: from d-Iearning to e-Iearning (electronic 

learning); and from e-Iearning to m-Iearning. Each evolutionary move 

has also represented a paradigm shift. In some cases, each evolutionary 

stage has re-enacted traditional and web-based approaches, while in 

others, it has led to both the reconceptualization of old approaches and 

the rise of new ones. 

In the last two decades the evolution that has attracted a lot of attention 

is the one taking place within mobile education. Within this paradigm, 

two different but complementary processes have since emerged. 

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The first is classical m-leaming while the second is m-Web 2.0 learning. 

Each of these processes represents evolving teaching and learning 

technologies that are specific to each process. In addition, both processes 

embody changing learners and changing learning approaches. 

This chapter, then, characterizes the evolution from classical m-leaming 

to m-Web 2.0 learning through mobile device development and mobile 

social software (M:oSoSo) applications respectively. The reason for this 

kind of characterization is that mobile devices are critical enablers for 

classical m-leaming while MoSoSo applications serve as critical drivers 

for m-Web 2.0 learning. 

Classical M-Learning and Mobile Web 2.0 Learning: 

An Overview 

This section offers a brief overview of both classical m-leaming and m 

Web 2.0 learning by locating them within their relevant evolutionary 

trajectories. 

M-leaming as a concept is ill-defmed. This is despite concerted attempts 

to defme it. Defmitions are intended to clarify, and not to cloud, 

concepts. Thus, for them to do so, they need to demonstrate conceptual 

precision and clarity. In relation to m-leaming this is, however, not 

always the case as the concept tends to mean different things to different 

people. Added to this, is the tendency to define m-leaming according 

to the experiences, views, and perspectives of those defming it. This 

scenario of multiple definitional perspectives is, nonetheless, to be 

welcomed rather than being decried. This is particularly so since, as a 

nascent learning enterprise, m-leaming need not be tied to one grand 

theory and one universal defmition. 

In terms of its evolution m-leaming is an upshot of d-leaming and e 

learning. Within this evolutionary path, it has also transitioned into 

MALL (mobile assisted language learning) (see Chinnery, 2006; Kukulska-Hulme 

& Shield, 2007). In both cases, it is part of both flexible 

learning and m-technology (mobile technology). That is, it is a subset of 

d-leaming and e-leaming, both of which are also instances of flexible 

learning (peters, 2005). Most importantly, m-leaming constitutes the 

4th Wave of e-leaming in the evolution of computer and technology 

mediated learning. This evolutionary trajectory can be plotted as follows: 

1st Ware - 1970-1979 (Number Crunching - Main Frames/One detice, 

ma'!Y users) '* 2nd Watl? - 1980-1989 (Desktop Publishing - Personal Com- 

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From Classical Mobile Learning to Mobile Web 2.0 Learning 

puters (pCs)/One detice, one user) 4 3rd Wat'e - 1990-1999 (Communication, 

Creation & Collaboration - Internet & Telecommunications/Ma'!Y detices, one 

user (e.g. combination of smartphone, MP3 pZt!Yer, the Web, etc)) 44th Watl? - 

2000- (A'!Yone, A'!Ytime, A'!Ywhere Information - Mobile Technology / Ma'!Y 

detices, ma'!Y users (pemasitl? computing [Ystems with wirelessfy interconnected 

detices) (Yuen, 2004). 

In this regard, there are eight categories (some of which do overlap) 

into which current conceptualizations of m-Ieaming fall: 

• Technology-mediated m-Ieaming - Here technological innovations 

are deployed in academic settings to drive m-Ieaming. 

• Miniature but portable e-Ieaming - This relates to mobile, wireless, 

and handheld technologies that are used to re-enact approaches 

employed in conventional e-Ieaming. 

• Informal, personalized, situated m-Ieaming - Technologies with 

additional functionalities (e.g. location-aware or GPS (Global Positioning 

System) devices) are deployed to deliver educational experiences. 

• Mobile training/performance support - Technologies are used to 

enhance the productivity and efficiency of mobile workers through 

providing just-in-time information and support. 

• Remote/rural/development m-Ieaming - Technologies are deployed 

to address infrastructural and environmental challenges related 

to delivering and supporting education which cannot be provided 

by conventional e-Ieaming. 

• CSML (Computer supported mobile learning) - This is computer 

mediated m-Ieaming which promotes hands-on/minds-on learning 

or situated and authentic learning. 

• LOCH (Language-learning Outside the Classroom with Handhelds) 

- M-Ieaming environment in which students are assigned 

field activities to do on their handheld devices outside the classroom. 

• MALL (mobile assisted language learning) - M-Ieaming related 

specifically to language learning which serves as a better option 

than CALL (computer assisted language learning). 

Thus, m-Ieaming has the following inherent characteristics: always-on 

connectivity; ubiquity; networked communication; situated, networked 

and collaborative learning; blended learning; and personalization or 

individualization. In this context, its main drivers are users' social 

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demographics and behaviors, m-technologies, and globalization (see 

Peters, 2005). The characterization and conceptualization of m-Iearning 

provided in the preceding paragraphs represents m-Iearning in its classical 

form. 

For its part, m-Web 2.0 learning has evolved from both m-Iearning and 

Web 2.0 learning. In particular, it adapts Web 2.0 technologies to mobile 

technologies (Coppola, Lomuscio, Mizzaro, & Nazzi, 2008). In this 

context, it encompasses a number of variables. First, it is both a concept 

and a process. As a concept m-Web 2.0 learning refers to the 

manner in which the second generation m-Web 2.0 is structured and 

deployed as a learning platform. It is a read/ think/ write/ talk and infotainment/ 

edutainment platform on-the-go. The process conception of m 

Web 2.0 learning underlines that this form of learning is in a constant 

state of flux. 

Second, it refers, on one hand, to technologies, services, learners, practices, 

and approaches involved in learning. On the other hand, it concerns 

a medium, space, culture, and mindset related learning. As an 

instance of technologies, m-Web 2.0 learning subsumes a set of hybrid 

and collaborative MoSoSo technologies for learning (e.g. moblogs (mobile 

blogs), mowikis (mobile wikis), podcasts, mobile social networks 

(MSNs), social bookmarks, instant messaging (1M), mashups, RSS 

(Really Simple Syndication)) and m-VoIP (mobile voice over Internet 

protocol). All of these technologies act as a platform, on one hand, and 

as applications and resources, on the other hand. These composite 

technologies enable mobile learners to generate their own content and 

to engage in multiple participatory social learning services and practices. 

Thus, the main drivers for m-Web 2.0 learning are learners, services, 

and content. 

The approach view of m-Web 2.0 learning relates to a series of approaches 

(individual, collaborative, and participatory) learners can 

adopt in generating, disseminating, and sharing content (see J aokar & 

Fish, 2007). Most significantly, m-Web 2.0 learning operates as a multimodal 

mobile medium and space for learning, communicating, socializing, 

and networking. In this way, it reflects the specific culture and 

mindset learners embrace towards learning as an enterprise. 

Third, m-Web 2.0 learning is evolutionary and emergent. It is evolutionary 

in that its technologies and the learning deployed from them are 

in a perpetual beta. And it is emergent since it involves learning prac- 

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tices and approaches that are evolving. Moreover, m-Web 2.0 learning 

entails miniature and digital data and content that has to be packaged 

and delivered in nano-formats. Thus, micro-data and micro-content are 

some of the critical elements underpinning m-Web 2.0 learning. In this 

regard, critical drivers for m-Web 2.0 learning are ubiquity and alwayson 

connectivity, on one hand, and learners, micro-data, micro-content 

and participation, on the other hand. 

Evolving Classical M-Learning and M-Web 2.0 

Learning Technologies 

This part of the chapter contends that both classical m-Iearning and m 

Web 2.0 learning are instances of evolving technologies for teaching 

and learning. To this effect, it provides specific and relevant scenarios 

typifying these two forms oflearning to support this contention. 

Classical M-Leaming Technologies 

There are many evolving technologies that are part of classical m 

learning. Among them are the following which constitute the focus of 

this chapter: mobile phones; PDAs (personal digital assistants); iPods; 

and games consoles. 

Mobile phones 

Mobile phones are among the first mobile devices to be deployed for 

m-Iearning purposes. Since their inception, mobile phones have 

evolved from being single purpose devices into being multi-functional 

devices. For example, they have been employed in teaching and learning 

a variety of subject areas: language, journalism, geography, mathematics, 

medicine, etc. In their early adoption and deployment as classical 

m-Iearning devices, mobile phones relied mainly on SMSs (short 

messaging services) or text messaging to mount teaching and learning 

(Yuen, 2004). These were chiefly first generation mobile phones. Studies 

focusing on the use of SMSs for both teaching and learning are 

reported by, for instance, Levy and Kennedy (2005) and Thornton and 

Houser (2005). Such studies concentrated on learning language aspects 

ranging from vocabulary words and definitions to idioms and example 

sentences. Some of the learners involved in these studies were Japanese 

and Italian university students. Additionally, SMSs have been employed 

in micro-economics experiments. Moreover, other instances of the 

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SMS uses in other subject areas have been reported. One typical example 

is the StudyTXT which allows students to access SMS information 

about any subject through their mobile phones at Auckland University 

of Technology (AUT) (Mellow, 2005). 

In their current use, mobile phones are multi-purpose teaching and 

learning devices with added capabilities and functionalities. Smartphones 

and most current generations of mobile phones fall into this 

category. Based on this, current mobile phones are deployed for various 

modes of integrated m-teaching (mobile teaching) and m-Iearning. For 

example, they leverage emerging mobile technologies (e.g. GPS, games 

consoles, 3G (third generation technology), and mobile broadband 

Internet technology) and are also part of location-based and contextaware 

learning (Greenfield, 2008), mobile Internet learning or mobile 

game-based learning. 

In the case of location-based and context-aware m-Iearning, for instance, 

mobile phones with positioning sensors (e.g. GPS devices) and 

fitted with other location/environmental sensors (Greenfield, 2008) 

allow students to search and identify the location of both their learning 

environments and their learning objects (LOs). Students can then rework 

their LOs or embed them in other LOs for purposes of customizing 

and personalizing them. 

Most importantly, the advent of the latest generation of e-texts (electronic 

texts) has added value to the evolving uses of mobile phones - 

especially smartphones - as e-book readers (electronic book readers). 

The new e-book readers feature additional file storage through SD 

(Secure Digital) cards. As such, a library of several titles can be loaded 

into and made available from smartphones. For example, Opera mini - a 

mobile Web browser - enables users to have a browsing and reading 

experience closer to that of a Pc. It renders pages easier to read at reasonably 

higher speeds. There are other mobile reading browsers such as 

Deepfish (Microsoft), Minimo (Mozilla), S60 browser (Symbian OS), and 

Sqfari browser (Apple) (Godwin-Jones, 2007). With all this, m-Iearners 

can use their mobile phones for reading and studying purposes and as 

m-library resources. 

PDAs 

PDAs - handheld devices combining both Palm and Pocket PC operating 

systems - have a variety of uses for both m-teaching and m- 

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learning. They are known for their value-added ubiquitous mobile 

computing and for their synchronization with both PCs and laptops. 

They boast many applications and functionalities that PCs and laptops 

(and in some instances mobile phones) have: word processor, spreadsheet, 

Excel, database, organizer, etc. As such, they serve as hybrid 

devices (see Yuen, 2004). 

PDAs have had many and varied uses in the area of second and foreign 

language teaching and learning. In most cases they are deployed in conjunction 

with other mobile devices (e.g. mobile phones, laptops, or 

Pocket PCs) or with other mobile applications such as Java-enabled 

applications. Even though they have a cross-disciplinary deployment, 

one of the uses of PDAs in their early adoption has been in the teaching 

and learning oflanguages such as English, French, Spanish, Danish, 

Norwegian, Chinese, Japanese, and Filipino, (Chinnery, 2006; Ogata & 

Yano, 2004). For instance, Thornton and Houser's (2005) study requiredJapanese 

students learning English idioms to use either PDAs or 

video phones or mobile web so as to access a web site containing English 

idioms and assess their usability. While scores for both media were 

positive and similar, PDA users rated their video quality higher than the 

mobile phone users. 

As in the case of mobile phones, the current usage of PDAs is largely 

influenced by most of the emerging mobile technologies. As such, they 

too are deployed for various modes of integrated m-teaching and m 

learning. To this effect, they have been used in location-based and context-aware 

m-Iearning. For example, Huang and Chang (n.d.) report 

about their study which involved the use of PDAs, GPS devices, GIS 

(Geographic Information Systems) interface, and a desktop computer 

by their students in a field trip to a zoo. The study required the students 

to gather information about the location of animals at the zoo using 

latitude and longitude coordinates. Two of its purposes were to generate 

a learning path diagram and to establish the students' individual 

interests in animals. Most recently, PDAs are used in augmented reality 

learning environments to track students' movements as they meet virtual 

characters, take photo and video clips, and gather and read documents 

(Dede, 2008). Thus, PDAs can be used for geo-information 

purposes: searching, identifying, checking, locating and navigating objects, 

events, persons, etc. 

Moreover, as Ogata and Yano (2004) point out, PDAs are valuable 

devices for the right time and right place learning (RTRPL) purposes. They 

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can be utilized by students (e.g. medical students, dental students, or 

ecotourism students) for writing down patients' responses/writing 

down annotations about the environment, recording questions, taking 

pictures and communicating with other students or teachers. 

iPods 

iPods are, undoubtedly, among the leading mobile devices of choice for 

the so-called Generation Y or Millennium Generation. The latter is a generation 

of learners raised in a media-rich and information-centric world. 

iPods are digital MP3/MP4 players with both audio and video functionalities; 

they do allow users to store and play music files wherever 

they are and whenever they want to. They are primarily leveraged in the 

field of m-Iearning for recording, storing, and listening purposes. 

Figure 1: A ChinesePod (S oum: http:/ / blog.praxislanguage.mm / 

2007/06/29/ learn-spanish-and-chinese-with-the-iphone) 

Most initiatives highlighting the educational uses of iPods have been in 

the area of language learning. Two of the earliest of such initiatives 

took place in 2002 and 2004 at Georgia College and State University 

(US) and Osaka Jogakuin College (Japan) respectively. In the former 

initiative, 50 iPods were distributed to students; in the latter 15GB 

(gigabyte) iPods were disseminated to 210 incoming freshmen (Thomas, 

2006). Recent initiatives include learning aspects of Spanish and 

Chinese (e.g. vocabulary, sentences, dialogues, conversations, etc) 

through SpanishPod and ChinesePod respectively. Figure 1 exemplifies the 

latter. 

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These initiatives emphasize the importance iPods have as classroom 

recording, course content storage and dissemination, study support, 

course content revision and review, and field recording tools. iPods 

also act as tools for mounting oral comprehension exercises and for 

improving pronunciation and enhancing listening skills. Above all, deployed 

in conjunction with the podcasting technology, iPods serve as 

alternative instruments for student assessment and self-assessment in 

various disciplines. This last aspect is indicative of how much iPods 

have evolved from being music playing devices into being m-Iearning 

assessment tools. In this context, they are rapidly replacing traditional 

audio devices (e.g. CD-ROMs and DVDs) in most HEIs (higher education 

institutions), thereby effectively underlining the iPodification of such 

institutions. 

Games Consoles: Nintendo OS Lite and Sony's PSP 

For some time, there has been a growing interest in the potential uses 

of handheld computer and console games for m-teaching and m 

learning. At the same time, some doubts have been expressed regarding 

the application of games to learning. Thus, this section of the chapter 

embraces the first view and briefly describes the educational benefits of 

Nintendo DS (Dual Screen) Lite and Sony's PSP (playStation Portable). 

These two games consoles - and others such as Microsoft's Xbox 360 - 

underscore two important aspects: how games consoles have evolved 

into potential m-Iearning platforms; and how computer games have 

evolved into a serious learning approach. 

Nintendo DS Lite is to handheld console gaming what Apple's iPod is 

to music players. One of its flagship games is Dr Kawashima's Brain 

Training: How Is Your Brain? It is based on Ryuta Kawashima's book 

entitled Train Your Brain: 60 Dqys to a Better Brain and challenges players 

to spend 10 minutes performing and learning words and simple arithmetic. 

The console also has a Sudoku game. The main idea behind 

Nintendo's games is to facilitate concentration and enhance both the 

reading comprehension and mental capacity of learners. Nintendo DS 

Lite's counterpart, Nintendo Wii also offers game classics (e.g. Nintedogs) 

and avatars (e.g. Miis). Nintendo Wii's success story is dubbed a 

true Wiiw/ution (Kelly, 2008). In this regard, Nintendo DS Lite games 

consoles have been introduced to some schools in Japan (e.g. Juntor 

high schools in Yawata) for language learning purposes. 

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One of the popular games deployed on the Sony's PSP handheld platform 

is Talkman. This voice-activated translation software has been 

released in languages such as Japanese, traditional Chinese, Spanish, 

German, French, and English. The software allows young and old players 

to have direct translation between languages it supports. It simultaneously 

combines entertainment, mini-games, and language learning, 

thereby resulting in both infotainment and edutainment. It challenges 

players to replicate pronunciation or choose words matching relevant 

foreign language definitions. In addition, it teaches users slang and 

travel phrases. 

Overall, games such as role-playing games, puzzle games, massively 

multi-player online games (MMOGs), simulation games, collaborative 

games, social games, and strategy games have significant educational 

implications. They help students develop and enhance their roleplaying, 

problem-solving, critical, and strategic thinking skills. They also 

hone students' social, interpersonal, negotiating, and decision-making 

skills and foster their multiple literacies. These are the skills and literacies 

needed for the 21st century. 

M-Web 2.0 Learning Technologies 

There are many evolving MoSoSo technologies that are part of m-Web 

2.0 learning. Of these, the following are the main focus of this chapter: 

moblogs; podcasts; mobile social networks; mashups; and RSS. 

Moblogs 

Moblogs represent the first social participation applications in a series 

of evolving m-Web 2.0 social software technologies. Like their traditional 

counterparts, moblogs allow users to make instant and spontaneous 

comments on mobile web pages. They can be structured in audio 

and video formats in which case they become audioblogs and vlogs 

respectively. Often they range from personal diaries to public knowledge 

resources (see Klamma, Chatti, Duval, Hummel, Hvannberg, 

Kravcik et al., 2007). 

Often mob logs are deployed on various mobile handheld computing 

devices such as mobile phones, Pocket PCs, palmtops and PDAs. In 

this case, they require mobile software applications such as S hoZu, mobileBlogger, 

Coogle Reader, Iitefleds and Open mini browser to run on such 

devices. For example, ShoZu is compatible with Web 2.0 applications 

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like Blogger, Flickr, YouTube and VOx. It can also run mobile RSS feeds. 

Most moblogs have publishing and editing web tools that allow for 

instant publishing and editing. In addition, they enable users to retrieve, 

archive, tag, hyperlink, blog-roll, and filter content. These features facilitate 

cross-referencing and collaborative filtering of content in the 

moblogosphere. 

Against this background, moblogs have many educational uses. These 

include the following: 

• Moblogs serve as both social writing platforms and read/ think/ write 

tools. They enable students to read, think, and write individually 

and collectively, thereby enhancing their relevant skills in these 

given areas. In particular they promote writing as an evolving activity 

- which is in a perpetual beta. 

• Most often, they facilitate free expression of opinions or views on 

the part of students. They help the latter free-write their ideas, 

thereby affording them a forum for their authentic individual and 

collaborative voices. 

• They act as value-added platforms for self-publishing/ copublishing, 

self-editing/ co-editing, and citizen journalism. 

• As they elicit comments and feedback from diverse students, they 

serve as spontaneous mechanisms for collaborative dialogue, peer 

review/criticism, and communities of inquiry. 

• They can be employed as progress monitoring tools by both students 

and teachers. 

• They promote collaborative learning and knowledge dissemination 

and sharing between students. 

• In particular, mob logs serve as personal knowledge management 

(PKM) tools. In addition, they support knowledge capturing, archiving 

and retrieval. 

• They enable teachers to post lecture notes, instructional tips, newsletters, 

course announcements and readings, assignment reviews, 

and annotated links to students. At the same time, they allow students 

to post their assignments, e-folios, and inquiries to their 

teachers. 

• In certain instances, moblogs can be employed as a stand-alone or 

integrated teaching and learning approach such as BALL (Blog Assisted 

Language Learning). 

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• Finally, mob logs are convenient tools for formative, summative 

and global forms of assessment (cf. Klamma et al., 2007). 

Pocasts 

Podcasting is a blend derived from iPod and broadcasting. It can be characterized 

thus: podcasting = Web syndication (RSS, Atom) + audio 

content (learning material, news, music, talk shows, etc) + mobile devices 

(iPod, mobile phones, PDAs, etc). It is a term referring to a set of 

technologies used for automatically distributing audio and video fties 

over the Internet through the publish, subscribe, and listen model. It enables 

users to create self-published and syndicated audio fties that anyone 

can subscribe to or freely access. Some podcasting has video files 

and becomes vodcasting. All these factors indicate how podcasting has 

evolved from traditional mobile broadcasting and classical CD 

ROM/DVD technology. 

Podcasts have two valuable characteristics: they are device-independent 

and platform-convergent; and they are time- and location-independent. 

They, thus, have the following educational benefits: 

• They blend learning with social activities. That is, students can 

listen to them while doing other activities (e.g. reading, writing, 

talking, walking, exercising, driving, eating, shopping, etc). Thus, 

they promote multitasking and multi-literacy skills. 

• They are handy tools for recording coursecasts (parts of lectures or 

whole lectures), live lectures, and demonstration lectures for students 

to listen to, watch (in the case of vodcasts), and review in 

their own convenient time. 

• In media studies they can be used as devices for recording broadcast 

shows. 

• They can be employed as supplementary material for lectures. 

• In some instances, they can be used for reflecting on or reviewing 

lectures or for recording fieldwork by teachers and students. 

• Students can podcast their individual or group projects, or their 

demonstration or practice lessons and submit them for evaluation 

purposes. 

• Faculties can produce podcasts of their academic offerings for 

new/prospective students. Likewise, universities or colleges can 

create podcasts providing brief roadmaps of their campuses to new 

students and new staff members. 

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• Podcasts may serve as handy resources for use by students in various 

academic disciplines. 

• Second and foreign language departments can create podcasts 

meant to improve language and literacy skills of their target students. 

• Podcasts can be customized to cater for individual learner preferences 

and learning styles. 

• Above all, they serve as useful resources for sight-impaired learners 

(cf. Dieu & Stevens, 2007) . 

Mobile Social Networks 

MSN s (mobile social networks) are mobile social collaborative and 

participation software applications enabling users (e.g. individuals, 

friends, friends of friends (FOFs), or groups) to connect, interact, and 

socialize with each other. At their core is social network theory which 

views social relations as expressed through nodes and links representing 

individuals. They also refer to a peer-to-peer (P2P) communication 

between two or more mobile devices that facilitate networking. Based 

on this theoretical construct, MSNs foster relations determined by 

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Figure 2: MocoSpace: (Soum: http://JlJJlJJI).mo~vspaa!.(om/) 

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common interests such as friendships, dating, hobbies, careers, skills, 

knowledge, and research goals (Kim, 2007). 

There is a growing raft of MSNs and MSN start-ups. This list includes 

Radar, MocoSpace, Twitter, Jaiku, Zanne~ Dodgeball, Zyb, Meep, ParrySync, 

6thSense, Zingku, loopt, (yWorld, MyNuMo, Helio, and TheGTID (beta 

version). For example, Radar even allows users to post their photos 

directly from their mobile phones, while Zannel is a closed MSN (Kim, 

2007). Meep enables simultaneous private group chats to multiple 

friends, whereas TheGRID has a location-based feature and allows users 

to blog, chat via instant messaging (IM), and send photos and video 

clips (Alfers, 2008). In this regard, Figure 2 provides a screens hot of 

MocoSpace. On the same score, traditional online social networking giants 

such as Facebook and MySpace and Internet heavyweights, like 

Google, Microsoft, and Yahoo, are beginning to roll out their MSN applications 

(Kim, 2007). 

One key principle underscores MSNs: the network iffoct. This enables 

them to leverage the cumulative participation value of individual and 

collective users. To this effect, MSNs have various educational uses: 

• They serve as a mobile platform for socializing, fun, entertainment, 

and gaming. Here browsing, reading, writing, thinking, profiling, 

listing, and ordering skills, and sharing ideas, views, and information 

are some of the learning activities integrated into socializing. 

• They facilitate social networking, interpersonal, and people skills, 

all of which are part of social skills. 

• Thus, they promote multitasking, multi-literacies, trans-literacy, and 

distributed cognition especially among young learners who are perceived 

as digital natives and as part of Generation C (Generation Conten~. 

• They are mobile spaces where participatory and collaborative learning 

and group- and project-based learning - encoded through 

communities of learners (CoLs), communities of interests (CoIs) 

and virtual communities of practice (VCoPs) - take place. 

• In addition, they are classic examples of networked/distributed 

learning and knowledge 

• As such, they foster the practice of learning from others and tapping 

into others' knowledge. This ties in with the m-Web 2.0 practice 

of sourcing collective intelligence (CI) and harvesting the wisdom 

of the crowd (WoC). 

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• In e-Marketing, in particular, MSNs can be used as part of the attention 

economy and as prime spaces for viral marketing. 

• Above all, when moblogs, podcasts, media sharing tools, 1M, m 

VoIP, IPTV (Internet protocol television), mashups and RSS are 

integrated into MSNs, students are able to source data from multiple 

sources. This ensures multiple data meshing and aggregation. 

Mashups 

Mashups, in this case, refer to any LOs (learning objects) - textual, audio, 

or video artifacts - remixed, reused, or repurposed and shared by 

students for purposes of m-Iearning using m-Web 2.0 applications. 

They are an instance of knowledge and information repositories recreated 

by students in the m-Web 2.0 environment to add value to their 

learning material (Dieu & Stevens, 2007). Mashups (e.g. Coogle Maps, 

Coogle Earth, Coogle's Mashup Editor, Podesk, Bluepulse) are user- or 

leamer-driven and dovetail with the notion of leamer-created context 

(LCC). On this basis, their educational benefits are many and varied: 

• They facilitate the remixing, repurposing, or reusing of knowledge 

repositories and LOs (e.g. FOSS (Free and Open Source Software), 

OER (Open Educational Resources), Creative Commons, Connexions, 

Science Commons). 

• They provide a medium for platform and application convergence 

and for integrating web interfaces. 

• They allow students to appropriate others' voices and others' 

sources of knowledge and information. Therefore, they are ideal 

mechanisms for leveraging CI and the WoC by students. 

• They enable students (through services like GPS and Coogle Maps) 

to overlay mapping mashups on or blend them with one or more 

data feeds from other sources, resulting in new leamer-created interactive 

maps. 

• Above all, with the help of their GPS built-in mobile phones and 

the web, both geography teachers and students can harness the 

benefits of geo-tagging. For instance, they can blend their current 

longitude and latitude coordinates with different types of multimedia 

content and information concerning the locations and places 

they are navigating. 

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Really Simple Syndication 

RSS (Really Simple Syndication/Rich Site Summary) is a standardized 

XML format used for representing information on the web. It allows 

web content additions or updates - organized into feeds - to be distributed, 

republished, syndicated, shared, and received/retrieved by users. 

The content can be news, press releases, announcements, articles, Slideshare 

fties, blog posts, podcasts, photos, or audio and video files. RSS 

works in conjunction with aggregators. The latter are feed readers or 

tools that aggregate, centralize, and display feeds from various sources 

and websites. Users/Students can then access content feeds (RSS feeds) 

by subscribing to them individually or collectively through RSS aggregators. 

Overall, RSS tools are instances of push, notification or harvesting 

technologies (Duffy & Bruns, 2006; D'Souza, 2006). 

RSS and aggregation tools have wide-ranging educational advantages. 

Of these the following are but a few examples: 

• RSS tools are an ideal virtual platform for harvesting, harnessing, 

and aggregating multiple information sources by teachers and students. 

All this can be deployed on multiple and hybrid devices and 

platforms (e.g. Pocket pes, mobile phones, PDAs) and various applications 

(e.g. moblogs, mowikis, podcasts, MNSs, 1M, Vo1P, 

1PTV, mashups, and RSS). 

• Aggregating feeds on a single topic or on a set of related topics 

selected by diverse students from multiple sources centralized in 

one common location enables individual students to have access to 

a collective memory of others, thereby exposing them to multiple 

perspectives. 

• Students may choose to lodge their queries with their teachers 

using RSS feeds. Likewise, teachers may opt to track and monitor 

students' progress, and update students' records using RSS feeds. 

• RSS feeds can serve as shared notice boards or calendars (e.g. 

Coogle Calendars and 30 Boxes) or as shared reminders for faculty, 

course, lecture, class, project, and assignment information. 

• RSS feeds are handy notification tools for academic research and 

journal alerts and updates for faculty staff and students (Duffy & 

Bruns, 2006; D'Souza, 2006). 

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Changing Students and Changing Learning 

Approaches 

As m-technology changes so do students, learning approaches, and 

related literacies. Thus, this section briefly delineates these three aspects 

under the sub-headings: changing students; and changing learning approaches. 

Changing Students 

Today's students have not only changed but also keep changing in 

terms of their real-life and real-time profiles, expectations, and learning 

preferences. One of the key drivers of this change is m-technology. In 

this case, students embrace different mobile information and communication 

technologies (m-ICTs) and integrate them into their everyday 

lives better than their teachers and parents do. They grow up in a digital 

world and hooked to mobile gadgets. Hence, they are referred to as 

digital natives who are either Generation Y or Millennials (peters, 2005; 

Oblinger, 2008). As such, some of their critical differentiators are: 

• 24/7 mobile connectivity and networking 

• Everyday personal and social learning (creating, sharing, distributing, 

and aggregating knowledge) 

• Multitasking, multiprocessing, experimental, & risk-taking behavior 

• Preference for digital tools/content over print 

• Swarming or tribal behavior (working in affiliations, CoLs, CoIs or 

VCoPs that are geographically dispersed and demographically diverse) 

• Multi-modal, poly-focal, and poly-contextual inclination (preference 

for multiple modes of communication using diverse devices 

and platforms, and ability to simultaneously focus on many tasks 

and to operate in different contexts) 

• Love for virtual gaming, play, fun, and entertainment (McMahon & 

Pospisil, 2005; Peters, 2005). 

Changing Learning Approaches 

The change in m-ICTs and in students who use them results in a corresponding 

change in learning approaches. Moreover, it leads to old 

learning approaches being re-envisioned. Four such approaches that are 

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the focus of this chapter are: nano-Iearning, distributed learning; deictic 

and meta-learning; and hybrid learning. 

Nano-Learning 

Nano refers to something small or miniature in quantity. Thus, nanolearning 

is learning comprising and offered in small chunks of material. 

It is packaged in customized bite-sized snippets of content (e.g. information, 

knowledge, or data) and presented in chunks of time spans 

ranging from 90 seconds to 10 minutes. The content segment offerings 

can be delivered repetitively over given intervals and personalized to 

students' needs and contexts. The counterpart of nano-Iearning is micro-learning. 

The latter refers to a learning broken into micro-contents 

and short-term learning activities with which students can interact over 

shorter periods of time (few seconds to 15 minutes) (Lindner, 2006). 

Both nano-Iearning and micro-learning are critical to the m-Web 2.0 

contexts since the latter deal with small chunks of micro-content and 

micro-data. For example, students can be offered LOs in any module in 

micro- or nano-chunks via any m-Web 2.0 application. This could be 2- 

minute snippets, video clips or RSS feeds about selected segments of 

modules, or about vocabulary items (foreign languages), laboratory or 

clinical research results (medicine), samples of advertisements (business 

management), statistics problems, etc. The case in point is the Chinese 

Pod and SpanishPod approach through which foreign language learners 

are offered chunks of vocabulary items or of sentences in English and 

Chinese and in English and Spanish. Here learning becomes truly atomized. 

All this results in the acquiring of micro-knowledge by learners as 

nano- or micro-learners. 

Distributed Learning 

Distributed learning (DL) harnesses principles underscoring the network 

effect, chaos, complexity, and self-organizing theories. It is about 

the distributed connections and networks individuals have. It contends 

that learning needs to focus on diverse networks of information and 

knowledge as networks between elements are more important than the 

knowledge possessed by individuals. Thus, DL posits learning embedded 

in distributed networks. 

In the context of m-Web 2.0, DL is exemplified by a distributed network 

of collaborative and participatory MoSoSo technologies (e.g. 

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moblogs, mowikis, MNSs, 1M, RSS) and distributed networks of students 

who leverage these technologies for m-Ieaming purposes. It is 

also illustrated by CoLs who tap the CI of the networked crowd. In this 

way, students are able to both source each others' diverse views and 

leverage knowledge and information from multiple sources (humans 

and technologies). Thus, DL facilitates learning and cognition connected 

to and distributed among students, technologies and contexts, 

and learning and cognition distributed across space and time boundaries. 

This results in distributed and networked communication. 

Deictic and Meta-Learning 

M-Web 2.0 learning also entails deictic and meta-learning. Deictic learning 

is a contextual, dynamic, and transient learning. This highlights its 

constantly changing and evolving nature (see Leu, Kinzer, Coiro, & 

Cammack, 2004). Meta-learning is a self-referential learning - learning 

about learning. In another version, it involves vicarious learning - learning 

by observing others learn. In relation to m-Web 2.0, learning is 

deictic in that the participatory technologies used for learning are contextual 

(they are specific to the m-Web 2.0 learning context), constantly 

evolving and transitory. The same applies to the content, knowledge, 

and information leveraged through these technologies. 

Meta-learning in m-Web 2.0 comes into play when learners learn how 

to learn to navigate the web and how to use the different complementary 

m-Web 2.0 tools and applications. It also comes into play when 

they learn how others learn by using these tools and applications. Metalearning 

in this sense results in learning meta-literacies and meta-skills 

as well. The former refer to literacies one acquires when learning literacies 

(e.g. navigational literacy, digital literacy) necessary for accessing 

and using m-Web 2.0 technologies. The latter are skills acquired when 

one learns skills (e.g. navigational skills, mob logging skills) required for 

appropriating m-Web 2.0 technologies. 

Hybrid Learning 

Hybrid learning (HL) is a re-conceptualization of blended learning. It 

refers, in this chapter, to a situation within the m-Web 2.0 environment, 

in which students leverage hybrid m-Web 2.0 technologies and applications, 

on one hand, and hybrid learning content, on the other hand, 

simultaneously and instantaneously. It also refers to a convergence of 

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hybrid platforms (e.g. m-Web, mobile devices, games consoles, m 

VoIP, IPTV) students deploy for learning, socializing, entertainment, 

and gaming purposes. One of the products of this type of learning 

scenario is infotainment, edutainment, and communitainment (students 

simultaneously communicating and participating in entertainment). 

Moreover, HL relates to a context in which students and teachers engage 

in revolving multiple roles as peers, mentors, coaches, and facilitators. 

Future Trends 

Key trends likely to be critical drivers of the evolutionary process in the 

area of m-Web 2.0 learning include the following: mainstreaming m 

Web 2.0 learning; ubiquitous mobility and connectivity; widgetization; 

user interface and browser technologies; and hybrid applications and 

convergent devices. 

Mainstreaming m-Web 2.0 learning entails formalizing this form of 

learning and granting it the same status as traditional learning. It also 

involves making m-Web 2.0 an interface between conventional e 

learning and traditional m-Iearning. In addition, it is about blending 

formal and informal learning with everyday student lifestyles. This 

means that m-Web 2.0 learning marks a meta-trend towards lifestyle 

learning or Learning Lifestyle 2.0. On the other hand, ubiquitous mobility 

and connectivity refers to alwqys-on and pervasive mobility and 

connectivity. This trend is largely dependent on the availability of mobile 

broadband and wireless technologies such as, for example, 3G/4G, 

WiFi and WiMax technologies. 

Widgetization is about making the m-Web function seamlessly like a 

desktop by utilizing intelligent and smart ready-to-use widgets. It is also 

related to enabling m-Web applications to function like operating systems 

(OSs). This will result in the m-Web being populated by widgets, 

user interfaces (UIs), micro-data, micro-texts, micro-blogs, etc. Closely 

related to widgetization are user interface and browser technologies. 

UIs are part of rich Internet applications (RIAs) that users/students 

leverage so as to interface with the mobile Internet. Brower technologies 

are applications used to browse the m-Web. 

Finally are hybrid applications and convergent devices. The former are 

m-Web 2.0 applications that have the functionalities of other applications. 

They are all-in-one applications. The latter are mobile devices 

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that combine different platforms. They are one-stop multi-purpose 

mobile devices. 

Conclusion 

This chapter has characterized the evolution of both classical m 

learning and m-Web 2.0 learning. The former represents traditional m 

learning as it is currently practiced. Its prime enablers are mobile devices 

such as those delineated earlier on. These devices serve as both its 

deployment tools and its delivery platforms. The latter is a mobile offshoot 

of Web 2.0 learning. Its critical drivers are MoSoSo technologies 

such as discussed in this chapter. As such, these two forms of learning 

are part of the emerging mobile education paradigm which falls within 

the broader spectrum of e-Iearning. 

Key Terms and Their Concise Definitions 

Generation Y: This is a generation of the youth born in the 1980s and 

1990s. 

Leamer-created context (LCC): Borrowed from user-created content 

(ueC), Lee is a context collaboratively created by learners so as to 

leverage learning resources. 

Learning oijects (LOs): These are digital resources - uniquely metatagged - 

that are used or reused to support learning. 

IJJcation-based learning. This refers to context-aware and locationsensitive 

learning as enabled by location-mapping technologies such as 

GPS. 

Massif-'eIY multi-plqyer online games (MMOGs): These are Internet-based 

computer games involving many players simultaneously. 

Millennium Generation (the Millennials): The Millennials are children born 

in the late 1990s and early 2000s. 

Virtual communities of practice (VCOPs): These refer to technologymediated 

communities in which people with common interests participate 

in activities around a subject, event, problem, etc. 

Widgets: Widgets are portable and reusable pieces of software code that 

can be embedded in web pages. 

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N. Unrau (Eds.), Theoretical models and processes of reading (pp. 1568- 

1611). Newark, DE: International Reading Association. 

Levy, M., & Kennedy, C. (2005). Learning Italian via SMS. In A. 

Kukulska-Hulme & J. Traxler, (Eds.), Mobile learning: A handbookfor 

educators and trainers (pp. 76-83). London: Taylor and Francis. 

Lindner, M. (2006). Use these tools, your mind will follow: Learning in 

immersive micromedia & microknowledge environments. 

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http://www.microlearning.org/ micropapers/ ALT -C- 

2006_lindner_micromedia.pdf 

McMahon, M., & Pospisil, R (2005). Laptops for a digital lifestyle: The 

role of ubiquitous mobile technology in supporting the needs of 

millennial students. Retrieved April 21, 2008, from 

http://www.educause2005.auckland.ac.nz/interactive/papers/C2. 

pdf 

Mellow, P. (2005). The media generation: Maximise learning by getting 

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blogs / proceedings/ 53_Mellow.pdf 

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Oblinger, D. (2008). Growing up with Google: What it means to 

education. Retrieved April 11, 2008, from 

http://partners.becta.org.uk/upload-dirldownloads/page 

documents / research/ emerging_Jechnologies08_chapterl.pdf 

Ogata, H., & Yano, Y. (2004). Knowledge awareness for a computerassisted 

language learning using handhelds. Intl J. Cont. Engineering 

Education and Lifelong Learning, 14(4/5),435-449. 

Peters, K. (2005). Learning on the move: Mobile technologies in 

business and education. Retrieved April 01, 2008, from 

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/ResourceCentre/141_LOM.pdf 

Thomas, M. (2006). iPod education: Innovations in the implementation 

of mobile learning. Retrieved February 22, 2007, from 

http://kt.flexiblelearning.net.au/wpcontent/uploads 

/2006 / 08 / thomas.pdf 

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Yuen, S. C. (2004). Mobile learning with PDAs: Part One. Retrieved 

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http:// dragon.ep. usm.edu/ -yuen/ present/ others/ china04a.pdf 

Author 

Dr. Chaka Chaka is a senior lecturer in the Department of English at 

Walter Sisulu University for Technology and Science (Eastern Cape, 

South Africa). His research interests include: computer mediated communication 

(CMC); electronic learning (e-Iearning); computer assisted 

language learning (CALL); mobile learning (m-Iearning); mobile assisted 

language learning (MALL); Web 2.0 learning/Mobile Web 2.0 learning; 

Web 3.0/Mobile Web 3.0; Semantic Web/Mobile Semantic Web; 

knowledge management (KM); and learning organization (LO). 

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Guy, R (Ed.). (2009). 



Chapter 5 

M-Learning Adoption in Brazil 

Amarolinda I. C.z. Saccol, Eliane Schlemmer, Jorge L. V. 

Barbosa, Nicolau Reinhard, and Carolina Sarmento 

Introduction 

The development and application of Mobile and Wireless Information 

and Communication Technologies (MWICT) in Brazil is remarkable. 

There are some 102 million mobile phones in the country (ITWEB, 

2007), far more than the number of personal computers. 

This chapter discusses the concept of mobile learning (m-Iearning) 

(Sharples, 2000; Trifonova, 2003; Koschembahr, 2005; Naismith et aI., 

2004) within Brazil's context. M-Iearning is taken here as meaning those 

learning processes that depend on using MWICT and that involve the 

mobility of the learners, who may be physically or geographically distant 

from each other or from the physical arenas of formal education, 

such as classrooms, training rooms, or work places. 

The growing use of MWICTs raises new teaching and learning possibilities, 

particularly for the professional education of mobile workers 

(Kristoffersen & Ljungberg, 2000). Koschembahr (2005) indicates that 

the information and communication technology currently used in the 

automation of mobile workers' activities can also be used for on-thejob 

learning. Edwards (2005, p. 50) states that m-Iearning contributes to 

informal and practical learning, as opposed to traditional training activities 

in formal educational settings, which are often inefficient, as they 

cannot ensure that "the right person takes the right course at the right 

time." With m-Iearning practices, mobile workers can spend more time 

where they need to be - in the field, with clients, doing business. According 

to Sharples (2000), mobile technologies can help encourage 

lifelong learning, of an individualized, learner-centered, situated, collaborative, 

cooperative and ubiquitous nature. 

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However, we must also consider the dubious character of the technology 

(Ciborra, 2002). If, on one hand, MWICT makes new learning 

practices possible, on the other hand, these technologies have their 

drawbacks, such as creating an information overload, generating greater 

complexity of interactions at different places and points in time, and 

breaking down the boundaries between personal and professional life, 

with an adverse impact on quality of life, etc. (Sorensen & Gibson, 

2003). One must also question how much workers can actually learn 

through m-Iearning, or whether it should be limited to the informationallevel. 

These issues raise many questions that demand an answer. 

This chapter covers the first stage of research that is currently under 

way and that is being carried out by Management, Education and Computer 

Science researchers. Its overall objective is to identify the main 

elements of the process of adopting m-Iearning in organizations in 

Brazil. This segment of the research consists of an exploratory study 

designed to identify pioneering m-Iearning initiatives and practices in 

this country. 

The method adopted resorted, first, to a web-based documental survey. 

Then, once m-Iearning applications in Brazil had been identified, the 

researchers contacted and interviewed people involved in these projects, 

to better understand their practices and the main challenges facing 

m-Iearning in Brazil. 

The chapter is structured as follows: first, the theoretical references that 

were taken into account are presented; second, the methodology of the 

exploratory study is described; and third, research results are presented 

and discussed. A fmal thoughts section closes the chapter. 

M-Learning 

This study's notion of Mobile Learning or m-Iearning leans toward the 

concept of pervasive learning (Siobhan, 2005) as ever-present education, 

expanding the concepts of collaborative learning, of constructivism, 

of environments rich in information for learning, and of selforganized, 

adaptive, multimodal learning. We define m-Iearning as a 

learning process that takes place with the aid of mobile and wireless 

technology (using mobile devices such as mobile phones, PDAs (personal 

Digital Assistants), or laptops connected to a wireless network) in 

situations in which people are highly mobile, as a result of which they 

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M-Learning Adoption in Broil' 

may be far from a stationary learning area such as a classroom, a training 

center or their workplace. 

The research project of which this exploratory study is a part aims at 

testing the proposition that MWICT offers new possibilities for the 

development of individual competences; these possibilities presumably 

extend beyond what current e-Iearning practices offer. This notion is 

based on the view that competences, i.e., the capacity to take effective 

action under specific circumstances on the basis of one's knowledge, 

skills, and attitudes, are developed in situated action (perrenoud, 1997). 

Thus, workers have to activate several cognitive resources while performing 

their professional activities. This is particularly true of mobile 

workers. Within a dynamic context, and in the face of uncertainty, they 

must access information, interact, and collaborate, in order to learn and 

to solve problems. As a result, their competencies are developed, not 

only within formal training environments, but especially in the situated 

context in which these skills are needed. This justifies testing the 

proposition that MWICT can contribute more to the development of 

individual competences than the currently available e-Iearning tools. 

However, to implement m-Iearning effectively, a set of complex elements 

must be considered. First, the concept of learning itself must be 

revisited. According to Hardless, Lundin, & Nulden (2001), to develop 

the skills of nomadic workers one must have an educational model 

based on an interactionist epistemological conception. Considering the 

design of m-Iearning solutions in the technological field, an analysis 

must be conducted of which type of services and tools will be offered 

to aid learning. The criteria of usability, accessibility, mobility, collaboration, 

cooperation, and location awareness must also be considered 

(frifonova, 2003; Ogata & Yano, 2004). At the same time, the limitations 

of currently available MWICT, ranging from the ergonomic limitations 

of mobile devices to the lack of telecom systems standardization, 

must also be taken into account. 

As learners use MWICT within a mobility context, a range of new issues 

arise with regard to several factors other than physical mobility, 

such as temporal and contextual mobility (Kakihara & Sorensen, 2002). 

The use of MWICT, for instance, can increase polychronicity or multitasking, 

i.e., dealing with several tasks simultaneously. There is also 

contextual mobility - the use of MWICT for m-Iearning can occur 

within different contexts, not only physical, but also social. The latter 

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include different cultural backgrounds, situations and moods, degrees 

of proximity, and mutual recognition among people. 

Thus, a mobile learner's context is defined dynamically; it emerges from 

his/her activities within his/her social context. It also involves motivations, 

as well as planned and unplanned actions. What is considered 

"normal" or appropriate within a given context (including learning) is 

socially negotiated (Dourish, 2004). 

Therefore, it is important to understand what are the possibilities and 

the constraints that might apply to m-Iearning within each physical, 

social, economic, and cultural context, which, in this case, is the Brazilian 

context. 

Research Methodology 

This is an exploratory research study (Collis & Hussey, 2005). The first 

step of the research technique was web-based documental survey 

(Bauer & Gaskell, 2000), conducted from January to March 2007, using 

the Goggle search engine. A set of key words related to m-Iearning was 

employed and only Brazilian web pages were visited, as the study focused 

on m-Iearning only in Brazil. 

Based on this wide-ranging search (for example, the expression "mlearning" 

alone produced some 900 results, explored one by one), 

projects, papers, articles, and web sites were found that discussed m 

learning cases, research studies, applications, and solutions. All this 

material was then analyzed, for selection of the most significant instances 

of m-Iearning and identification of the key people who might 

be able to provide references, discuss their experiences, and answer the 

study's questions. 

Overall, thirty-one relevant m-Iearning references, projects, or initiatives 

were identified, mostly in academic settings, very few projects or 

applications having been found in the corporate world. The criteria for 

screening the findings were: (1) concrete cases of m-Iearning deployment 

or application; (2) projects or references developed by wellknown 

institutions; and (3) references, projects, or initiatives recognized 

externally (quoted by other sources). 

After this screening, people involved with the selected initiatives were 

contacted (one person from each). Additionally, two academic experts 

in e-Iearning and MWICT development were asked to respond to the 

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study's interview because of their broad understanding of the Brazilian 

context regarding the technologies of interest to this study and their 

use; this enabled the experts to refer to cases where m-Iearning had 

been adopted and to analyze the challenges that hinder the dissemination 

of m-Iearning in this country. 

These thirty-three people were first contacted through an e-mail that 

presented the project, the team, and the objectives, and suggested 

scheduling phone or personal interviews. As it drew a low level of response, 

a new message was sent, suggesting the possibility of responding 

to the study's questionnaire (five open-ended questions) via e-mail. 

Fifteen out of the thirty-three people contacted answered the questions 

(six through phone interviews, one through a personal interview and 

eight bye-mail). The interviewees were from different parts of Brazil: 

most were from the southwest (the country's most industrialized area) 

and mainly from the cities of Rio de Janeiro and Sao Paulo; there were 

a few from the south and one from the northeast. 

One of the study's limitations was that the e-mail responses were far 

more brief than those provided in the personal or telephone interviews. 

To offset this limitation, we analyzed the documents about the projects 

or initiatives with which the e-mail interviewees were involved. Another 

limitation was that there might be m-Iearning references, projects, or 

initiatives not yet available on the web at the time, or not listed in such 

a way as to surface through this study's key words. Therefore, the researchers 

are open to contact from companies, institutions and other 

people who may wish to include their projects in the list identified. As 

it focuses on emerging technologies and practices, this study does not 

aim at being conclusive or definitive. To the contrary, it would be ideal 

for it to continue expanding, in keeping with the evolution of m 

learning in Brazil. 

Research Results 

The research results are presented in two parts: an overview of the 

thirty-one references, cases, or projects found via the web-based documental 

survey described above (next section), followed by a description 

and analysis of the results of the aforementioned interviews. 

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Results of Documental Web-based Research 

Out of the thirty-one projects or references on m-Iearning identified 

through our documental web-based survey, we found that most (seventeen) 

referred to m-Iearning applications in the educational world, 

mainly at institutions of higher education. They included: 

• Proposing a framework for the development of educational 

applications for m-Iearning (one case); 

• Adapting e-Iearning software for mobile devices (pDAs and 

mobile phones), with reports of practical application experiences 

(two cases); 

• Using PDAs (one case) and a mobile portal (one case) in undergraduate 

disciplines; 

• Developing M-Iearning software to be used by hearing and 

visually impaired individuals (one case each); 

• Creating a Virtual Learning Environment specific for m 

learning (five cases); 

• Discussing the possibilities of m-Iearning in the healthcare sector 

(one case) and m-Iearning scenarios (two cases); and 

• Creating different tools (software) for m-Iearning (two cases). 

Of the references and projects found in academia, eight either concern 

models, frameworks, or software prototypes with no real applications, 

or provide a generic discussion of m-Iearning. Among the references 

that concerned development and testing of m-Iearning solutions in real 

contexts, the applications generally involve the use of few functionalities 

and resources; none point to the actual incorporation of routine m 

learning practices into teaching practices. This indicates that m-Iearning 

in the Brazilian academic world is still at an embryonic stage. 

Another potential conclusion is that most of the references and projects 

found in academia have a technological perspective. Only a few 

focus on pedagogical issues, management issues, or the social aspects of 

adopting m-Iearning technologies and practices. 

Out of the thirty-one projects or references found through our webbased 

survey, ten regarded commercial software solutions for m 

learning. One of the firms offering this type of solution was also a user 

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of m-Iearning in its own corporate training activities (Intel, see case 

below). Six of the ten software providers that offered these solutions 

where contacted, but did not answer the research questionnaire. 

Regarding the use of m-Iearning among companies or non-academic 

organizations, only the following cases were found: 

• Santos et al. (2002) describe the Brazilian Navy's Marine Corps 

use of software and mobile devices in war games and field exercises. 

A System of Exercise Evaluation was adapted 10 a 

W AP protocol to be accessed via mobile phones. 

• Neves (2005) reports the case of Telemig Celular (a regional 

wireless telephone services company), which used W AP and 

SMS technology to create a forum for its employees to discuss 

problems and exchange ideas. 

• The Bradesco Foundation, which belongs to Bradesco, one of 

Brazil's biggest banks, provides free education at schools attended 

by about one hundred thousand students across Brazil. 

The foundation has been using mobile technologies in its education 

projects for youths and adults, including the use of 

Pocket PCs and Wi-Fi networks in the classroom. Although 

these m-Iearning initiatives do not target corporate training, 

this case is interesting in that it shows a major organization using 

m-Iearning in its social welfare activities. 

• Intel Brazil, as part of its global Intel Corporate University, offers 

corporate training to the personnel of its Brazilian subsidiary 

through mobile devices such as laptops, tablet PCs, PDAs 

and smartphones. The company virtually abolished desktops, 

so its employees use laptops or smartphones as their basic 

work tools and can take m-Iearning courses on various subjects 

and fields through them. The courses are based on multimedia 

presentations and flash animations. Intel, which has roughly 

one hundred thousand employees worldwide, considers this an 

effective training strategy. 

As the data above show, most m-Iearning references and projects in 

Brazil are in academia, corporate m-Iearning cases being rare. The interviews 

carried out corroborate this perception (see below). 

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Results of Interviews with People Involved with M-/earning 

As the methodology section mentioned, based on the identification of 

m-Ieaming references, projects, cases, and experts, the people involved 

in these initiatives were contacted, which led to fifteen interviews. 

Out of the fifteen respondents, two were executives in large IT companies, 

one was an executive in a foundation, and the other twelve were 

professors or researchers, mainly in Computer Sciences or Education, 

with nine out of twelve academics directly involved in the development 

and application of m-Ieaming technologies. 

Below, we analyze each of the five interview questions, also discussing 

and analyzing their answers. 

Potential users of m-Ieaming in the organizational context 

in Brazil 

The first interview question was: ''In your opinion, what are the sectors, companies, 

organizations or rypes of profissionals that can benifit from m-leaming?" 

Most interviewees clearly stated that m-Ieaming is particularly useful for 

"mobile" or "field" professionals in general, i.e., those who are constantly 

traveling or on the move outside the organization. Similarly, six 

of the fifteen respondents felt that any sector, company, or professional 

can benefit from m-Ieaming in some way. 

The types of professionals that the respondents mentioned the most 

were: salespeople; health workers; field technicians; professionals who 

constantly need to update their skills and knowledge; executives, managers 

and supervisors; IT professionals; and administrative personnel. 

The following also got one mention each: engineers, lawyers, and logistics 

workers. Organizations dealing with health or insurance, multinationals 

in general and the public sector were mentioned as types of 

institutions or sectors with potential for using m-Ieaming, as well as 

companies with several branches or subsidiaries. 

Corporate or Organizational m-Learning Cases in Brazil 

The second question was: "Do you know or can you mention any successful 

cases of m-leaming deployed in companies or organizations in Brazjl?" 

Five of the fifteen respondents were unaware of any such applications, 

whereas three mentioned cases of its being used in courses and educa- 

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tional activities in higher education institutions. Two respondents mentioned 

m-Iearning cases that concerned training health workers in hospitals. 

One respondent mentioned one case of m-Iearning used in the 

training of a multinational's sales staff, employing the same mobile 

devices that the company's salespeople used in their work (PDAs). 

Another respondent mentioned an identical case (sales staff training 

based on devices also used in other processes) in a large wholesale 

company. One respondent reported being familiar with the use of 

MWICT to access the corporate Intranet to search for information on 

procedures and products or to interact with colleagues at the company's 

headquarters. Three cases of m-Iearning applications in large IT 

multinationals were also mentioned (including the aforementioned Intel 

case), as well as the Bradesco Foundation case. 

The m-Iearning cases within organizations that the interviewees reported 

primarily concerned specific applications within multinationals, 

mainly involving content access via mobile devices, to download training 

materials and read them off-line, for instance. The initiatives were 

incipient in the Brazilian market as a whole, because, according to two 

of the interviewees, it is still difficult to measure the return and results 

of m-Iearning implementation. 

m-Learning Technology (hardware) 

The third question was: ''In your opinion, what is the most suitable technology 

for m-leaming (e.g., mobile phones, PDAs, smartphones, tablet pes, etc.) and 

wf?y?" 

There was no consensus among the respondents regarding the most 

suitable device for m-Iearning activities. Smartphones and laptops were 

the devices mentioned most often. 

The argument in favor of smartphones was the convergence of the 

different tools available in PDAs and mobile phone connectivity. 

Three respondents mentioned laptops because they have far bigger 

screens than PDAs, smartphones, and mobile phones, and also because 

the personnel of many firms has used laptops for a long time. Two 

other respondents mentioned light and inexpensive computers (along 

the lines of the "hundred-dollar laptop") as the most appropriate de 

Vices. 

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Three respondents mentioned mobile phones because of their popularity, 

as they are more commonly owned by Brazilians than any of the 

other devices; they are also the type of device with which we are generally 

most familiar. On the other hand, some respondents argued that 

mobile phones are the most limited device for ergonomic reasons. 

Three respondents made the additional comment that the ideal device 

ought to be light and portable like a mobile phone, PDA, or smart 

phone, but with the ergonomics of a laptop. 

Yet another comment was that the tablet PC, though mentioned by two 

respondents, is still regarded by the others as a heavy and fragile device 

with no specific advantages. 

Two respondents stated that all available devices could be suitable, 

depending on the objectives of the training program and on the context 

in which they would be used. 

Another comment was that those tools used routinely by the organization 

in other processes (e.g., for sales force automation) should also be 

used for m-Ieaming activities. 

m-Learning Technology (software) 

The fourth interview question was: ''Do you know of a'!Y m-leaming software 

or platforms? In your opinion, which fiatures should thry hat'e?" 

Eight of the fifteen respondents said that they were unaware of any 

specific m-Ieaming software solution (such as courseware). However, 

several solutions were mentioned. Some were adaptations of earlier e 

learning solutions, such as Teleduc (http://www.teleduc.org.br/) and 

AulaNet (http://aulanet.les.inf.puc-rio.br/ aulanet/). Others were software 

created in specific m-Ieaming projects at universities (for example, 

a mobile portal). 

The most frequently mentioned software programs for use in m 

learning were fundamentally those that generated presentations for 

access through mobile devices, or tutorials based on presentations with 

some degree of "question-answer" interactivity, applied in short 

courses. Other m-Ieaming solutions mentioned were PDA software 

programs, such as Hands® or AvantGo®, as well as collaboration tools 

now adapted for mobile devices, such as Lotus Notes® and Everyplace®. 

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Regarding features that m-Iearning software programs ought to have, 

answers differed. What respondents mentioned the most was that m 

learning software must take into account the ergonomic limitations of 

the current mobile devices (e.g., limited screen and keypad size) as well 

as connectivity issues (bandwidth and connection costs). 

Flexibility, simplicity, speed, minimalism (few tools, just those needed 

to achieve the goals of each educational activity), low purchase and 

maintenance costs, and being able to operate both online and offline 

were associated features. Being a multi-platform device and multidevice 

(four mentions) was also a valued feature. 

Another stream of responses concerned usability issues. Some interviewees 

recommended using visual and audio resources, (minimizing 

the manual input of data), as well as games and simulations (more fun 

resources). Interactivity and using mobile devices with which users are 

already familiar (e.g., MP3 players) were also some of the possibilities 

for increasing users' acceptance. 

One should note that only one respondent directly mentioned the issue 

of educational methodologies being taken into account by m-Iearning 

software, and also that only one respondent mentioned the importance 

of systems being sensitive to users' location and context (one of the 

main differences between m-Iearning and e-Iearning). 

Challenges for the Dissemination of m-Learning in Brazil 

The last interview question was: ''In your opinion and experience, what are the 

main challenges to be ot'ercome in order to disseminate m-learning in Brazil, especialfy 

within the corporate context? (Taking into account,for instance, technological, 

cultural or pedagogical issues, etc.). " 

The responses to this question showed that several challenges must be 

overcome in order to disseminate m-Iearning in Brazil. We grouped 

them as follows (though we must consider that the categories are 

closely interwoven): 

• Technological and economic challenges - According to five respondents, 

further progress must be achieved in order to incorporate 

a range of new technologies (voice, digital TV, etc.) into 

m-Iearning, systems should become increasingly user-friendly, 

and the ergonomic limitations of mobile devices (e.g., screen 

size, data entering), mentioned by two respondents, must be 

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overcome. Three respondents mentioned the technicallimitations 

of the wireless networks, as well as the lack of standards 

in the devices and operational systems, not to speak of the nationwide 

inadequacy of the wireless infrastructure. The issue of 

mobile devices' connectivity costs was also mentioned by five 

interviewees, while two stated that m-Iearning is yet to become 

financially viable. Keeping a system permanently up-to-date 

(one mention) and the fast obsolescence of mobile devices 

(one mention) are added challenges to be taken into account. 

• Challenges regarding deployment of new technologies and new learning 

practices - According to five respondents there is a lack of culture, 

familiarity, or habit regarding the use of mobile devices. 

Three respondents stressed that, in general, people only use 

mobile phones, and mainly for talking, the devices' other functions, 

such as SMS or computing resources, being unexplored. 

Another two respondents also mentioned that there is still resistance 

to e-Iearning, which in turn affects m-Iearning. The 

lack of "digital literacy" in Brazil was also mentioned by two 

interviewees, while one talked about the lack of confidence in 

MWICT capacities. 

• Pedagogical challenges - An interesting statement voiced by five of 

the fifteen respondents is that, though MWICT has its limitations 

(as mentioned above), "teaching practices are lagging behind 

technology", i.e., pedagogical practices regarding m 

learning are still incipient as compared to the rate of technological 

development. The following points also concur with 

this statement: the need to foster collaboration in the learning 

process (five mentions); the idea that we are still learning from 

e-Iearning practices (three mentions); and the lack of a true 

learning culture, a culture of learning autonomy, etc. It is also 

necessary to create interesting courses using MWICT technology 

(two mentions), to train professionals in the use of these 

technologies (one mention), to consider different cognitive 

styles when developing m-Iearning activities, and to develop a 

specific pedagogical model for those practices (one mention 

each). 

• Social and contextual challenges - Another stream of answers 

(though less frequent) concerned the context surrounding m- 

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learning which involves broader social issues, such as the limitations 

to using mobile devices in public spaces in Brazil due to 

fear of being robbed (three mentions), and the viability of onthe-move 

learning in the absence of comfort and of the physical 

surroundings that might encourage learning. Two respondents 

mentioned the need to change the mental and working 

models (from "fixed" work to "mobile", flexible work). The 

quality of life issue and the possible invasion of privacy resulting 

from m-Ieaming were also mentioned by respondents. It is 

interesting to note that only one respondent referred to the 

challenge of using m-Ieaming as a way to promote digital inclusion 

in Brazil. 

Final Thoughts and Future Research 

This study allowed us to investigate which m-Ieaming practices were 

being deployed in Brazil. We found that the corporate m-Ieaming cases 

are rare. In academia, most of the projects involve software prototypes, 

models, and frameworks that are yet to be applied. In the cases in 

which m-Ieaming practices and solutions were tested in real contexts, 

we found that few functionalities and resources were being used, and 

no routine practices. This indicates that m-Ieaming is at a very early 

development stage even in academia. One should also note that most 

of these references and academic projects have a technological slant. 

Only a few concern economic or management elements, pedagogical 

issues or contextual and social factors related to the deployment of m 

learning. 

We also found, based on the experience of people involved with m 

learning in Brazil, that there are several elements to be taken into account 

when it comes to disseminating m-Ieaming practices, including 

the possibility of using it within an educational context, the use of suitable 

m-Ieaming technologies, and the challenges inherent to these practices. 

These challenges encompass several different elements and fields 

of knowledge: technological and economic barriers, resistance to the 

adoption of new learning practices and technologies, pedagogical difficulties, 

and contextual and social challenges. Considering these results, 

the following topics are proposed for future research: 

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• A study of the few existing cases of corporate m-Iearning in 

order to understand their dynamics, goals, facilitators and hindering 

factors, consequences, etc.; 

• A study of the contextual and social issues that surround m 

learning in Brazil; 

• The development of specific educational m-Iearning methodologies, 

in line with MWICT idiosyncrasies and the Brazilian 

context, also taking into account the specific features of pedagogic 

mediation for this form of teaching and learning; 

• The development of more sophisticated m-Iearning software, 

focusing on an interdisciplinary and systemic perspective 

(views from the areas of Education, Management, Computer 

Science, Design, etc.), for application to empirical cases; 

• The development of studies concerned with the ftnancial aspects 

(cost-benefit) of m-Iearning (particularly from an organizational 

point of view); 

• A study of the use of location-aware services that also consider 

the user's profile, as applied to m-Iearning (extending beyond 

e-Iearning) in Brazil; 

• A study of the use of m-Iearning as a way of promoting digital 

inclusion in Brazil. 

We hope that the results of this exploratory study may contribute to the 

work of researchers from different areas connected with m-Iearning as 

well as to the work of people in the human resources management area 

and of developers of mobile solutions and services. 

This study shows that there are many challenges, but also many different 

possibilities, for the development of m-Iearning in Brazil. 


The authors wish to thank CNPq (the Brazilian Council for the Development 

of Science and Technology) for funding the research project 

"Mobile Learning in the Organizational Context", of which this study is 

a part. 

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References 


Bauer, M. & Gaskell, G. (eds.) (2000). Qualitatit'e Researching with text, 

image and sound: a practical handbook. London: Sage. 

Ciborra, C. (2002). The laf?yrinths ofinformation. London: Oxford Press. 

Collis, J. & Hussey, R. (2005). Pesquisa em Administrafao: urn guia pratico 

para alunos de gradua


Perrenoud, P. (1999). Construir as competencias desde a escola. Porto Alegre: 

Artmed. 

Santos, F. M. A., Casanova, M. A. & Seixas, R. B. (2002). Jogos de Guerra 

em Platqformas MrJt"eis. Retrieved February 5, 2007, from 

http://w3.impa.br/-rbs/pdf/wcsf2002.pdf 

Sharples, M. (2000). The design of personal mobile technologies for 

lifelong learning. Computers & Education, 34 (3), 177-193. 

Siobhan, T. (2005) Pervasive, persuasive e-Leaming: modeling the 

pervasive learning space. In Proceedings of the 3rd International 

Conference on Pen-asire Computing and Communications Workshop, Hawaii. 

Sorensen, C. & Gibson, D. (2003). Ubiquitous tisions and opaque realities: 

profissionals talking about mobile technologies. Retrieved January 11, 

2005, from http://mobility.lse.ac.uk 

Authors 

Amarolinda I. C. Zane1a Sacco! is Ph. D. in Business Administration 

at School of Economics, Business Administration and Accounting 

(FEA-USP), Brazil. Professor and Researcher of Management and 

Information Systems in the University of Vale do Rio dos Sinos 

(UNISINOS), Brazil. E-mail: aczanela@unisinos.br 

Eliane Schlemmer is PhD in Computer Science applied to Education 

at Federal University of Rio Grande do SuI (UFRGS), Brazil. Professor 

and researcher of Education in the University of Vale do Rio dos Sinos 

(UNISINOS) - Brazil. E-mail: elianes@unisinos.br 

Jorge Luis V. Barbosa is PhD in Computer Science at Federal University 

of Rio Grande do SuI (UFRGS), Brazil. Professor and researcher of 

Computer Science in the University of Vale do Rio dos Sinos 

(UNISINOS), Brazil. Email: barbosa@unisinos.br 

Nicolau Reinhard is Ph. D. in Business Administration at School of 

Economics, Business Administration and Accounting (FEA-USP) and 

Post-Doctor at A. P. Sloan School of Management from the Massachusetts 

Institute of Technology (MIT). Professor and researcher of Informatics 

and Information Systems in the Business Administration Department 

at FEA/USP. E-mail: reinhard@usp.br 

Carolina Sannento is nearing completion of the Bachelor of Business 

Administration at University of Vale do Rio dos Sinos (UNISINOS), 

Brazil. E-mail: carolina.sarmento@gmail.com 

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Guy, R (Ed.). (2009). 



Chapter 6 

Mobile and Pervasive Computing in a 

Computer Engineering Undergraduate 

Course 

Jorge Barbosa, Rodrigo Hahn, 

Debora Barbosa, and William Segato 

Introduction 

Nowadays, studies about mobility in distributed systems are being 

stimulated by the proliferation of portable electronic devices (for example, 

cell phones, handheld computers, tablet pes, and notebooks) 

and the use of new interconnection technologies based on wireless 

communication (like WiFi and Bluetooth). This new mobile and distributed 

paradigm is called Mobile Computing (Augustin, Yamin, Barbosa, 

& Geyer, 2002; Satyanarayanan, 1996). Moreover, mobility allied with 

the diffusion of wireless communication enabled the availability of 

computational services in specific contexts - Context-aware Computing 

(Augustin et al., 2004). Adaptation related research brought the possibility 

of continuous computational support, anytime, anywhere - Pen'asit'e 

Computing (defmed and well discussed in the works of Weiser, 1991, 

and Satyanarayanan, 2001). In tum, IJJcation Systems (Hightower & 

Gaetano, 2001; Hightower, LaMarca, & Smith, 2006) are enabling the 

use of this kind of computing in accordance with the physical location 

of users. Recently, the application of these technologies in the improvement 

of education strategies created a new research front called 

Mobile and Pen'asit'e Learning. This concept is deeply discussed in the 

works of Barbosa, Geyer, & Barbosa (2005), Barbosa et al. (2006), 

Ogata and Yano (2003), Rogers, Price, Randell, Fraser, Weal, and Fitzpatrick 

(2005) and Yau, Gupta, Karim, Ahamed, Wang, and Wang 

(2003). 

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In 2002, a southern Brazilian university proposed a new pedagogical 

approach to undergraduate courses. This approach is called Undergraduate 

Course of Riference (nicknamed GRefe). GRefes are based on: (1) 

Learning Programs: a new kind of academic structure aimed at the 

integration between the course's knowledge areas; (2) Learning Projects: 

long duration activities that consolidate the knowledge created in 

the different knowledge areas. 

Currently, there are six GRefes in our university. In this chapter, we 

describe our experiences with the application of mobile and pervasive 

computing technologies to improve our academic practices in a specific 

course of reference, called Computer Engineering GRefe (nicknamed 

ComGRefe) . The chapter is organized in six sections. The second 

section describes the GRefe pedagogical proposal. ComGRefe is used 

to illustrate the main ideas behind our approach. The third section 

presents our experiences applying mobile and pervasive computing in 

ComGRefe. The fourth section presents the specific application of 

mobile computing resources in several areas of the Computer 

Engineering Grefe, focusing on the use of mobile computing to 

support a new way of teaching. The fifth section presents two 

educational projects developed in ComGRefe. One of them is a 

pervasive game called MoBIO Threat. It is an innovative, educative 

project. The game takes advantage of our mobile computing 

infrastructure to present a rich learning experience. The second project 

is related to the construction of mobile robots. These robots employ 

devices such as pocket PCs and wireless cameras. Finally, the sixth 

section draws some conclusions and presents future work. 

Course of Reference 

Undergraduate Course of Riference (nicknamed GRefe) is a new kind of 

academic approach, based on Learning Programs. Each Learning Program 

area has a professor and is composed of a group of pedagogical activities. 

These activities can be thematic workshops, lectures, lab experiments, 

and standard classes. For instance, the aforementioned Computer 

Engineering GRife (nicknamed ComGRefe) is one of six GRefes created 

by our university during the past years. This GRefe is organized in four 

Learning Programs, namely: (1) Bases; (2) Methods; (3) Challenges; 

(4) Solutions. 

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Mobile and Pervasive Computing 

Each Learning Program has a period of one year and is divided into six 

knowledge areas: (1) Computer Science; (2) Electronics; 

(3) Mathematics; (4) Physics; (5) Philosophy; (6) Linguistics (portuguese, 

English, etc). 

Each Learning Program has a special kind of activity called a Learning 

Project. Learning Projects are the main activities of the GRefes because 

they integrate all areas in a practical framework, where all professors 

and students participate. For example, two projects currently in development 

can be underlined: (1) the construction of mobile robots; (2) 

the creation of pervasive games. Both projects are using handhelds and 

wireless technology to monitor and control several aspects, such as 

location, energy consumption, and the robots themselves. 

Other interesting characteristics of ComGRefe are: (1) there are approximately 

20 students and 5 professors in each of the four Learning 

Programs. This gives a total of about 80 students and 20 professors 

involved in all the course; (2) each student has an appointed tutor - a 

professor that advises all of his/her pedagogical activities during the 

program; (3) each Learning Program conducts periodic meetings where 

the professors of each knowledge area share their experiences. In the 

same meeting, each Learning Project coordinator shares information 

about the evolution of project activities. 

Mobile and Pervasive Computing in ComGRefe 

The Computer Engineering GRefe is a pilot project. It is the first 

community in our university to use mobile computing in daily academic 

practices. After we gather more experience, other GRefes will be integrated. 

Currently, our mobile computing infrastructure in ComGrefe is 

composed of the following devices: 

• 45 HP iPAQ hx4700 pocket PCs. This model is powered by an 

Intel XScale PXA270 624Mhz CPU. It has 64MB RAM and 

128MB ROM. The device also has a VGA display and integrated 

WLAN, Bluetooth 1.2, and IrDA. All pocket PCs come 

with SD expansion memory cards. The devices weigh very little 

and are ideal for outdoor lessons; 

• 20 HP TCll00 tablet PCs. They are powered by an Intel Pentium 

M 1.00Ghz processor and have 512MB RAM and a 

40GB hard drive. The screen is a lOA" XGA (1024x768) TFT 

display. It has an integrated 32MB n Vidia G-Force4 Go 420 

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• 

• 

and HP Wlan 802.11a. The device runs Windows XP Tablet 

PC Edition. The differentiated input method allows the operation 

of the device with a digital pen, instead of the keyboard. 

Also, the form factor, battery life (two and a half hours), and 

integrated wireless network offer a more mobile way of interaction 

than standard notebooks; 

14 docking stations for the TC1100 tablet Pc. They have 3 extra 

USB ports, 1 externally accessible multi-bay (for plugging a 

CD-ROM drive, for example), a VGA connector, and wired 

network. The dock stations are used in order to save the time 

of having to plug peripheral devices when returning to a more 

traditional classroom environment; 

4 Cisco Aironet 1100 wireless access points. They have 16 MB 

RAM, 8MB flash memory, 54Mbps transmission speed, and 

support both 802.11g and 802.11b clients. The circa 200 meters 

coverage radius enables us to easily deploy mobile devices 

all o_v~~ S=.?~~~e_f:, _~i!hout significant loss of signal. 

lAI 

216 

I ' 

206 ~ ~ 

, 

212 213 214 

1- ____________ _ 

Figure 1. ComGRefe (dashed in the pi?"ture) 

Our scenario encloses nine rooms, covered by four wireless access 

points (see Figure 1). This coverage is needed for our location 

technology research, where we use the access points for WiFi signal 

triangulation. With the mobile and pervasive computing support in 

ComGrefe, we are looking for two main pedagogical goals. First of all, 

we are interested in supporting the specific activities of each knowledge 

area, leveraging our current technology in order to make learning a 

more engaging experience. As for the second goal, we are interested in 

applying wireless and mobile technology in the improvement of our 

Learning Projects. In order to satisfy the first objective, all teachers 

involved into each of the four ComGRefe Learning Programs are takmg 

advantage of tablet PCs, iP AQs, wireless network, and location 

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technologies in their daily practices, where applicable. With motivated 

teachers, this new way of learning becomes quicker to accept and easier 

to adapt to. The fourth section deals with the applications of computing 

in each knowledge area. 

--....... - 

(aj Creatioll of mobile robots 

(bj Remote cOlltrol of a mobile robot 

Figure 2. Learning Project - Mobile Robots 

In order to satisfy our second objective, we have introduced mobile 

computing into several Learning Projects, for example: (1) creation of 

several kinds of mobile robots (see Figure 2); (2) industrial and home 

automation (controlling doors, video cameras and energy consumption); 

(3) integration between mobile technology and RFIDs to automate 

parking control; (4) determination of the physical location of devices 

and exploration of location based services (LBS); (5) development 

of multiplayer and pervasive games for mobile devices (see Figure 3). 

The fifth section details two specific learning projects developed in this 

context. 

(aj Use of tllobile devices ill pervasive gattleS 

(bj PI,!]ers of pervasive games dllrillg a match 

Figure 3. Learning Proje?t- Pen-asit'e Gaming 

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Mobile Computing In Knowledge Areas 

In this section we aim to present an objective review of the impacts of 

using mobile computing technology in ComGRefe. In order to do this, 

we have interviewed teachers involved in all of the different knowledge 

areas. Our main interest is the evaluation of mobile computing applications 

for teaching in several ComGRefe knowledge areas. The results 

were the following: 

Computing Ana: Students of this area are using mobile computing in 

several projects. For example, many applications developed in Java and 

Embedded C++ are being deployed to the pocket PCs for testing, 

instead of using the emulators provided in the SDKs. This provides a 

more accurate debugging experience. The mobile computing infrastructure 

is also used in the creation of distributed applications, using several 

pocket PCs connected via WiFi and/or Bluetooth. Network programming 

concepts (such as client/server architectures and sockets) are 

being explored, and different operating systems are being deployed to 

the pocket PCs; 

Electronics Ana: In this area many applications were found for mobile 

devices. In laboratory activities, for example, pocket PCs are being used 

to visualize electronic component blueprints and circuit schematics, to 

update experiment implementation schemes and to view photos/movies 

of prototypes in development. In classroom activities, students 

use their pocket PCs for real-time projection and discussion of 

solutions (see Figure 4a); 

Pf?ysics Ana: This area found a wide range of utilities for the mobile 

devices. For example, sensors can be connected to a mobile device. 

This provides learners with mobile systems adapted to a remote data 

collection scheme. These sensors can be used both in and out of the 

classroom. In the classroom, a student lab station usually consists of a 

tablet or pocket PC, a sensor, and a LabPro interface (or other A/D 

converter). When outside the classroom, a pocket PC device connected 

to a sensor and an A/D converter provides the necessary equipment 

for collecting sample data anywhere; 

Mathematics Ana: In this area, mobile devices are mostly being used to 

access mathematics software via the web. The mobile devices are also 

used in a support role - students are introducing computational vision 

to the robots used in other learning projects; 

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Linguistic Area: In this area, devices are being used mainly for convenience. 

The way of interaction presented by mobile devices allows taking 

quick notes anywhere, be they text or voice recordings. Many tasks 

benefit from this added convenience, such as recording oral exercises, 

communication in different languages and accessing dictionaries, writing 

content for personal homepages, practicing English grammar, chatting 

with chatbots, such as Alice (http://alicebot.org), and playing language 

games, such as 20q.net (http://www.20q.net). Figure 4b shows a 

Linguistics thematic workshop employing tablet PCs in classroom activities; 

Philosopf?y Area: In this area, as in the linguistics area, mobile devices are 

being used mostly for convenience. With tablet PCs, learners can use 

digital libraries to access online e-books and maintain a site created by 

the course (Candido, 2008) . The ethical and and social impacts of mobile 

computing are also being researched. Some aspects of these impacts 

can be measured in specific social groups, like the users of Learning 

Programs in ComGRefe. 

(fI) Electrollics 'I'orkshop 

(0) Lillgllisfics workshop 

Figure 4. Mobile equipments being used in thematic workshops 

Two ComGRefe Learning Projects 

The following sections present two Learning Projects conducted in 

ComGRefe. The first is an innovative pervasive game, created to teach 

notions of biology (specifically, epidemics and disease control). 

It focuses on player interaction in order to achieve a common goal. The 

game employs location tracking and was planned to be very forgiving 

about the necessary technologies, that is, it can be set up with the 

minimum of a WiFi network and wireless-enabled devices. The second 

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project describes the creation of mobile robots controlled via wireless 

cameras and computational vision. 

moBIO Threat: Pervasive Gaming in Com GRefe 

Pervasive games are an emerging genre of gaming in which players 

must move physically to specific places in order to perform tasks within 

the game. Users can interact with each other and with the environment 

around them. To accomplish such interactions, location technologies 

can be used to allow learners to interact with real objects. Pervasive 

games are a challenging domain because they deal with networking 

protocols, game design, game planning, and social interaction and collaboration. 

The most notable aspect of a pervasive game is, without 

doubt, the social interaction and collaboration. 

There are a few pervasive games already developed, such as CatchBob! 

(Girardin, 2005), Uncle RID' All Around You (Benford et aI., 2003), Human 

PacMan (Cheok et al., 2003; Knight, 2004) and, most recently, 

Plundr (http://plundr.playareacode.com /). 

The main goal of the moBIO Threat Learning Project was to create an innovative 

game with improved gaming experience on both interaction 

and location tracking. The game is meant to be an educative experience 

- its main goal being to teach players about epidemics and disease 

control. During the game, the players have to work with concepts such 

as pathological agents and chemical reactions, for example. In other 

words, players must gather information about game elements by learning 

how domain-specific subjects work. The areas of chemistry and 

biology are the most related to the game's educational objectives. Mo 

BIO Threat features a different, engaging playstyle, supported by realworld 

interaction. Many times during the game players must look for 

specific objects or places. They have to walk and explore the game area 

to gather resources, which are always real objects. This way, users can 

interact with the game elements (such as trees and rooms) in a concrete 

way. 

Game Plot and Features 

The game can be played by up to eight players. It takes place right after 

a terrorist attack in a university. Most of the facilities were destroyed, 

and the communication with the rest of the world has been lost. The 

terrorists (TR) stole ten years of research data from the local biology 

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lab. Their goal is to use the research data to develop a deadly toxin and 

launch a missile to disseminate it. A team of military scientists - the 

counter-terrorists (CT) - remained in the university. The CT mission is 

to prevent the enemy from utilizing a pathological agent from the stolen 

research data. This can be done by either neutralizing the enemy 

force or by synthesizing an antidote for the agent being developed. 

As players interact with objects or other players, their position on the 

game map is updated. This way, others always know the precise location 

of their team members. The game provides automatic virtual feedback 

for actions being taken in the real world, such as walking or interacting 

with objects. For example, players can see (in the in-game map) 

the trees where the needed agents can be collected (either to make an 

antidote or to create a pathological agent). 

(flj cr flttemptillg fo {Jllfhesize fill fllltidofe 

(b j A felTorisf seflrches his oppollet/fs 

Figure 5. Players at a moBIO Threat matd} 

Figure 5 shows players at a moBIO Threat match. During the match, 

players can activate the enemy seard) button, which triggers a scan for 

players nearby and creates a combat opportunity if at least one of them 

is found. The battle is fought based on items the player collects or buys 

in a structure named Armory. Since each team's players have the same 

goals, they are constantly talking to each other, setting up strategies, 

and trading information about items and enemies, creating a strong 

sense of collaboration. 

Technology Used in moBIO Threat 

Location tracking is a very important aspect of the pervasive gaming 

area. There are a lot of tools that can help to improve tracking accuracy, 

such as multiple WiFi antennas and ultra-sound or ra- 

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dio-frequency sensors, to name a few. The problem with these tools is 

that they demand complex installations and location training and that 

they depend on specific and relatively expensive hardware to be installed. 

The GPS system was also discarded because it does not cover 

indoor locations - a possible scenario we wanted to experiment with in 

this game. Since the project was designed to be portable, location tracking 

in itself was simplified; position changes are detected only when the 

user interacts with objects and rooms, which are already mapped and 

registered. 

(a) Gatlle tlIaili screell 

(b) IPiFi coverage alld Access Poillt placetllCllt 

Figure 6. moBIO Threat 

Each player carries an HP Compaq TCll00 tablet Pc. Players can 

detach the tablet PC removable keyboard after typing their names and 

login information, when the match is about to start. To ease input, 

players utilize the tablet PC pen to interact with the game software. The 

game was developed in Java, conforming to the J2SE vS.O libraries and 

specifications. 

Figure 6a shows the game main screen. The game interface consists of 

four main sections. The left column (Number 1 on the figure 6a) shows 

the player rank, the items being carried in the personal bag and the wanted 

items for the current mission. The lower left corner (Number 2) has 

information about the player, such as name, team and health. The health 

level is presented in a graphical percentage-based bar. The bottom of 

the screen (Number 3) has information about the events and warnings 

of the game and gives feedback about the status of the connected interaction 

devices, such as RFID and Bluetooth. It also features a "searchfor-opponents" 

button, which scans for opponents in order to initiate 

combat between the players. The bigger section (Number 4) contains 

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the map of the game area, which shows information about the location 

of friends, places and items in general. The location of each game item 

in this map is updated whenever its real-life equivalent changes location. 

This is done via a coordinate-based module. 

WiFi is the main method of communication in the game, because the 

users are mostly always within the coverage range (shown in Figure 6b). 

Localization and messaging events are sent through WiFi connection. 

Players communicate with the server via an IEEE 802.11 network. To 

provide maximum range and coverage, the access point (AP) was 

placed in the corner of the building marked 'B' - the AP (pointed to in 

the Figure 6b) covers an area of about 7000 square meters. The trees 

and the walls of buildings may cause players to eventually enter a "dead 

spot". This may cause the connection to terminate. However, a reconnection 

module was developed to guarantee reconnection as soon as 

the user leaves the "dead spot". When the signal is lost, the map becomes 

unavailable, and a "static signal" animation takes its place in the 

game client instead. This acts as a visual feedback to the player. 

Bluetooth technology is employed to provide interaction between players 

when they become physically close to each other. The At'etana 

(2008) library was used to interact with the built-in Bluetooth card. 

The game also supports infrared technology - tablet PCs have built-in 

IrDA ports, so no additional hardware is necessary. 

RFID (Radio Frequency Identification) is another technology present 

on moBIO Threat. RFID tags were implanted into game objects such 

as trees and rooms. To read the tags, players must be carrying a USB 

RFID reader and place it close to the tag. The RFID reader used was 

the Texas S4100 MFR (Multi-Function Reader) Evaluation kit. Plastic 

tags were used, as shown in Figure 7a. The tags are passive, so the 

reader must be very close. Figure 7b shows the main goals CT players 

should pursue to thwart the terrorists' plans (by synthesizing an antidote 

to the biological agent). Each goal is implemented with a RFID 

and indicated in the main screen with a green T. 

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(a) RFID tag 011 a tree 

• 

(b) Goal map 011 the cliellt sereell 

Figure 7. Mapping of game elements 

A "field item" module with support for all of these connection technologies 

at once is still under development. Its final form will be a boxshaped 

hardware component with a QR Code tag on the outside; a 

RFID tag inside it with a indicative marker of its position on the outside; 

and a embedded IrDA module and battery with the infrared LED 

partially outside and a indicative marker of the LED position. The alphanumeric 

code for typing is printed together with the QR Code tag. 

~ 

(a) Readillg all RFID tag vin tablet PC 

(b) Close-Itp viell' '!! tablet PC sereell 

Figure 8. Interaction with rooms 

When an item is detected, its hardware components activate the listeners 

on the game software. The identification numbers are obtained, and 

the event message is transmitted to the server, which queries the database 

for the item that corresponds to the unique code sent. The item is 

then dispatched to the client, and a confirmation screen appears, as can 

be seen on Figure 8, where the message "Do you want to enter room 

202?" is presented to the player. 

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Mobile Robots in Com GRefe 

In ComGRefe, robotics is conducted as a multidisciplinary research 

area - the creation of mobile robots allows for great interaction opportunities. 

For this Learning Project, there are two main areas. For mobile 

robots, the goal is to develop robots capable of sensing the environment 

and moving through it, avoiding obstacles. This is achieved by 

equipping the robots with devices such as sensors, mobile computers 

and cameras. For manipulative robots, the goal is to create fiXed-base 

robots with the capability to manipulate objects - such as robotic arms. 

In this section, we chose to name both kinds of robots as mobile robots, 

for simplicity purposes. The following two subsections detail 

experiments conducted in the area of mobile robots. These experiments 

are presented in order to show the pedagogical impact of the 

application of mobile and pervasive technology in our Learning Programs. 

Mobile Robot Research 

This Learning Project aims to integrate several knowledge areas by the 

way of a common practical project. Depending on the availability of 

resources, the robots can be either built with ready-made kits - such as 

Lego Mindstorms (Knudsen, 1999) and ROBIX 

(http://www.robix.com) - or simulated in virtual environments - such 

as SimRob3D (Heinen, 2002). 

Figures 9a and 9b present examples of both mobile and manipulative 

robots, as developed in ComGRefe. Figure 9a shows a mobile robot 

controlled via software. Two pocket PCs were used: one of them acts 

as the "mind" of the robot; the other acts as the control interface. The 

two pocket PCs communicate via Bluetooth. Figure 9b shows an example 

of a robotic arm. The arm control is powered by PC software. 

The arm is accessed via parallel port interface. 

In this Learning Project, the construction of mobile robots is divided 

into four incremental steps, as follows: 

Step 1: Develop/build/model a simple mobile robot capable of basic 

movement and use sensors to detect collisions; 

Step 2: Add more advanced sensor equipment to the robot. This presents 

exciting new possibilities, such as creating robots that can follow 

determined paths or using location technology, via WiFi, Bluetooth, 

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The E volution of Mobile Teaching and Learning 

RFID, or others. Figure 9c presents an example of a line-following 

robot (Kwon & Lee, 1995); 

Step 3: Add enhanced perception (computational vision) to the robot. 

With a wireless camera, the robot can see the environment and is capable, 

for example, of actively avoiding collisions; 

Step 4: Equip the robot with tools (either software or new hardware 

parts) in order to allow it to perform more complex tasks (like finding 

heat sources, play soccer, or identify and manipulate objects of a certain 

color). These tasks, in general, should change the environment in some 

way. Figure 9d presents examples of an experience in this Learning 

Project (in this case, the construction of small, battery-powered robotic 

forklifts) . 

(a) Mobile robot 

(b) Malliplflative robot (ROBIX) 

(c) Sophisticated (Iillefollowillg) tllobile robot 

(d) Combillillg the hl'o approaches: Robotic forklifts 

Figure 9. Examples of robots dmloped in ComGRife 

After each step, the new modules are integrated with previously developed 

ones. This way, learners build new features on top of a wellknown, 

familiar structure. The incremental approach has been working 

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exceptionally well in this Learning Project. After the robots are built, 

the learners' teams compete in small tournaments where the robots 

built by each are evaluated according to the knowledge areas involved. 

For instance, knowledge of concepts such as Euclidian geometry, programming 

logic, algorithms, and matrixes all contribute to the development 

of electronic sensors. Due to our multidisciplinary approach, 

this mixed evaluation method has been giving satisfactory results . 

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(a) Rl0Dl0 ill GlobaTech 2007 

(b) Rl0Dl0 cOlltrol illterface 

Figure 10. R10D10 

Another interesting project regarding mobile robots can be seen in 

Figure 10. RI0DI0 is a 1 meter high, 12kg heavy user-controlled robot, 

created with the goal of housing several types of sensors (such as wireless 

cameras, sonar, and bumpers). Its design was inspired by the ubiquitous 

R2D2, of Star Wan fame. Its name stems from the fact that the 

number 2 is represented as 10 in binary notation. 

RI0DI0 is equipped with a graphical LCD (liquid crystal display) of 

128x64 pixels and an integrated D-Link DCS-900W wireless camera 

(seen at the top of the robot, in Figure lOa). The camera output is redirected 

to a video window in a tablet PC screen via wireless network. 

The operator can see what the robot sees and respond with appropriate 

movements. 

A preliminary working prototype ofR10D10 was shown in GlobalTech 

2007 (a big southern Brazilian technology event where many organizations 

present their recent research projects). It represented our Com- 

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puter Engineering course. For this occasion, the robot was equipped 

with a 2,4GHz video link. R10D10 walked around, while its output was 

directly feed to a video projector. The robot can be controlled either via 

an adapted videogame joypad or remotely, via wireless network (both 

WiFi and ad hoc) . Figure lOb shows the robot's control interface, running 

on a tablet Pc. 

Robot Sumo 

Mobile robots were also used in another experiment in ComGRefe - 

Robot Sumo. In this particular research front, mobile computing devices 

were mostly used in supporting roles. For example, the microcontrollers 

employed in the robots were programmed in tablet PCs. 

Also, the sensors used for movement control, for example, were initially 

handled in test environments built around tablet PCs. 

In Robot Sumo, two robots are put in a circular arena, comprised of a 

black central area and delimited by a large white border. Figure lla 

shows a representation of the arena. The objective of a Robot Sumo 

match is to push the opponent away until he is out of the circle. The 

robot that remains inside the circle is declared the winner. The matches 

are usually disputed in best-of-three rounds. 

(a) Rffpreselltatioll if a Robot SlIHlO arella 

(a) A slflllobot 

Figure 11. Robot sumo in ComGR¢ 

The main challenges in such an application are the detection of the 

opponent's position and of the limits of the arena and pushing the 

adversaries outside of the arena. The opponents and arena limits can 

usually be found via infrared sensors. This way, the robot knows which 

way to turn and when to stop accelerating, in order not to leave the 

arena. The robots can move straight, in reverse, or turn. Different 

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curved paths are achieved by varying the speed of the right or left 

wheels. 

Figure llb presents a sumo-fighting robot (commonly called sumobo~. 

The robots are constructed following specific rules regarding maximum 

size, maximum weight, structure, and control. For example, the robot 

must be totally autonomous (it cannot communicate with external systems 

at all, be they humans or other machines) and must maintain 

structural rigidity (it is permitted to drop small pieces, but cannot drop 

large parts of itself outside the arena). 

Another rule enforced at this competition in ComGrefe is that Robot 

Sumo is not a war. The objective is to simply push the opponent outside 

the arena and not to destroy it. As such, any weapons and projectiles 

that can cause damages to the robot systems, the arena, and people 

are all forbidden. 

Conclusion 

We can underline several results related to mobile and pervasive computing 

in ComGRefe. Firstly, Learning Programs were improved in the 

sense that we are using more interesting methodologies based on mobile 

computing. The implied application of mobile technology itself 

gives us an edge in our pedagogical approach - all of the knowledge 

areas in ComGRefe benefit from mobile technology. Secondly, the 

Learning Projects themselves were improved too, because we oriented 

all activities to use mobile devices. Third, all professors are using mobile 

equipment to do their activities, stimulating the interaction between 

the several knowledge areas, using mobile computing like a tool to 

integrate the group. 

Another interesting result comes from our experience with the creation 

of pervasive games. This activity, while usually concentrating on recreational 

subjects, creates practical, viable learning opportunities. A byproduct 

of this activity is that the interaction between learners is also 

stimulated. Pervasive games still constitute a relatively new research 

area, and there's much to explore. 

Even if the impact of using mobile devices in our Learning Programs is 

already exciting, its use can still be expanded. The mobile and pervasive 

computing experiences acquired in activities pertaining to a specific 

knowledge area can be applied to all of them. Also, hardware is not the 

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only way to improve learning aspects; the use of specialized software 

can vastly improve the use of mobile devices in several key areas. The 

pedagogical impact of such initiatives can be readily measured through 

the evolution of student's grades. This is an interesting future research 

topic. 

As it could be seen in the two Learning Projects shown, mobile computing 

infrastructure can be used to set up reasonably cheap, flexible 

and easy to use experimentation and learning environments. With the 

popularization of mobile and embedded computing devices, the prices 

tend to drop. This fact, allied to the innovation aspect of such research 

topics, guarantees that this field of experiment will become more and 

more popular. 


The authors wish to thank CNPq (the Brazjlian National Counsel of Technological 

and Scientific Det'elopmen~ for funding the research project "Ubi 

Campus: urn Modelo para Suporte a Educa


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Satyanarayanan, M. (1996). Fundamental challenges in mobile 

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Authors 

Jorge Luis Victoria Barbosa received his BS degree 

in Electrical Engineering from the Catholic 

University of Pelotas, Brazil, in 1991. He obtained 

his MS and PhD degrees in Computer Science from 

the Federal University of Rio Grande do SuI 

(UFRGS), Brazil, in 1996 and 2002, respectively. 

Today he is Professor at the University of Vale do Rio dos Sinos, Sao 

Leopoldo, Brazil. His research interests include parallel and distributed 

computing, grid and pervasive computing and programming languages. 

He is a member of the Brazilian Computer Society (SBC). 

Rodrigo Machado Hahn is an undergraduate student, 

on the way to receiving his BS degree in Information 

Systems at UNISINOS, Sao Leopoldo, 

Brazil. He collaborates in research projects at Mobilab 

Research and Development 

(www.inf.unisinos.br!~mobilab). His research interests 

include pervasive computing, ubiquitous learning 

systems, and agent-based learning systems. 

Debora Nice Ferrari Barbosa received her BS 

degree in Information Systems from the Catholic 

University of Pelotas, Brazil, in 1997. She obtained 

her MS and PhD degrees in Computer Science from 

the Federal University of Rio Grande do SuI, Brazil, 

in 2001 and 2006, respectively. She is a Professor at 

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Unilasalle University, Canoas, Brazil. Her research interests include 

pervasive learning systems, distributed computing, multi-agent systems 

and artificial intelligence. She is a member of the Brazilian Computer 

Society (SBC) . 

Wilian Segatto is a student of the Computer Engineering 

course at UNISIN OS, Sao Leopoldo, Brazil. 

His research areas include pervasive games development, 

interactive automation systems and remote 

management, among others. 

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Digitized by Google

Guy, R (Ed.). (2009). 



Chapter 7 

A Short-Term Trial Documenting Students' 

Perceptions, Attitudes, and Experiences with 

Mobile Learning 

Retta Guy 

Introduction 

Bound by accrediting agencies, educators and researchers seek to integrate 

the latest technology, innovation, or strategy to enhance learning. 

As information and communications technology (lCT) continues to 

expand the boundaries of higher education into an "anytime/anywhere" 

experience, recent advancements have incorporated 

mobile wireless technologies into education. 

During the current millennium, the development and delivery of mobile 

education has evolved and provides students the flexibility to access 

classroom information and communication with peers and faculty. 

Traxler (2007) defmes mobile education in terms of its technologies 

and its hardware, "namely that it is learning delivered or supported 

solely or mainly by handheld and mobile technologies such as personal 

digital assistants, smartphones or wireless laptop PCs". 

Traxler (2006) describes current research projects affiliated with wireless 

and mobile learning as 'first generation'. He further claims that 

these projects serve as enhancements to e-Iearning rather than a new 

form of pedagogy. In any case, educators and practitioners must investigate 

to understand student attitudes, new learners, and the different 

study patterns of all learners if we are to achieve successful outcomes 

with mobile learning (Kukulska-Hulme, 2006). 

The adoption of mobile teaching and learning challenges educators and 

designers with redefming this educational experience to ensure an optimal 

mix of technology and pedagogy is attained. Furthermore, the 

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usability of mobile devices to support learning must be explored if it is 

to be embedded in classroom practice as part of a learning experience 

outside the classroom. 

Emerging technologies linked to mobile learning challenge the wisdom 

of traditional pedagogic practice. Educators and designers must explore 

all possibilities in the utilization of these resources and the development 

of new pedagogical practices. They must also continue to assess the 

usability and functionality of mobile wireless technologies if we are to 

move forward with this paradigm shift; moreover, further research is 

needed for new pedagogical approaches in support of this technology 

for learning (Goh & Kinshuk, 2006). 

The examples of innovative practice cited in this chapter, along with 

the current field testing of mobile learning applications, demonstrate 

the impact mobile wireless technologies have had on education to date. 

Specifically, the current study reports on the findings of a mobile-based 

trial piloted during the 2007-2008 academic school year. 

Review of Mobile Learning Projects 

Mobile wireless technologies can be used to present learning materials, 

to seek responses from learners, and to provide appropriate and timely 

feedback. Roschelle et al. (2003) maintain that mobile devices can enhance 

the learning process when used to gather feedback from learners 

during a classroom lecture or demonstration as this process employs a 

hybrid model emphasizing the integration of mobile devices into existing 

teaching methods and practices. Roschelle and colleagues support 

the idea of using classroom response systems noting the following as 

benefits: 

• facilitate whole-class drill and feedback activities, 

• 

• 

gather student responses rapidly and anonymously, and 

quickly assemble a public, aggregate display to show the variation 

in the group's ideas while maintaining individual anonymity. 

In the study conducted by Wang et al. (2004) the Wireless Technology 

Enhance Classroom (WiTEC) was developed. This system integrated a 

wireless LAN, mobile learning devices (MID), an electronic whiteboard, 

a resource and class management server, and an interactive 

classroom server to support everyday activities unobtrusively and seamlessly 

in the classroom. In the WiTEC system, the teacher could display 

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A Short-Term Trial Documenting Students' Experiences with Mobile Learning 

questions on an electronic white board and the students were able to 

use their MLD to vote or to answer questions. The students' answers 

were sent to a server and statistical results were immediately calculated 

and displayed on the whiteboard. Voting could also be carried out 

anonymously. 

Similarly, an electronic voting system, Interwrite PRS (Personal Response 

System) was adopted at Strathclyde, Department of Mechanical 

Engineering. The PRS was designed to increase interactivity in lectures; 

as a result, four large lecture rooms were equipped with infrared voting 

devices and receivers, and seating was modified to enable students to 

engage in group discussion while still facing the front of the theatre. 

Using handsets to answer questions, students could see their responses 

immediately collated and displayed on a screen via a receiver linked to a 

laptop and a data projector GISC, 2004 e-Iearning and innovative team). 

Mobile devices provide an opportunity for learners to become entrenched 

in a realistic context while simultaneously having access to 

supporting tools. Colella et al. (1998) describe a participatory simulation 

in which the learners act out key parts in an immersive recreation of a 

dynamic system. In this simulation, the learners play the role of hosts in 

the spread of a virus and become part of the system by wearing small 

computers that keep track of who they meet and the transmission of 

the disease. The aim of this approach is to move the simulation away 

from the computer screen and more into the tangible world that students 

can interact with; thus, by making them part of the simulation 

itself, they are engaged in the learning process and get to immediately 

see the effect their actions can have on the system as a whole. 

Dufresne et al. (1996) report on the use of a classroom response system 

called 'Classtalk' with first year physics students at the University of 

Massachusetts. Using palmtop computers as input devices, Classtalk 

allowed students to work collaboratively to deepen their understanding 

of physics and to reflect on their own ideas and the ideas of others. 

Additionally, instructors were able to present a question or problem to 

the class and students would enter their responses using the palmtop 

computers; instantly, aggregates and a summary of student responses 

were displayed as a histogram. 

Dawabi et al. (2004) (in Attewell and Savill-Smith) present an approach 

to integrating mobile devices into face-to-face learning scenarios using 

the electronic learning support system ConcertStudeo. This platform 

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provides tools that permit the integration of course materials as well as 

facilitate quizzes, brainstorming, voting, and ranking. ConcertStudeo 

provides interactivity between students and instructors using wirelessly 

connected PDAs in combination with an electronic blackboard, also 

known as Whiteboards. With ConcertStudeo, students can present their 

own ideas and anonymously and synchronously answer multiple-choice 

questions that will be automatically aggregated as well as managed and 

configured by the moderator. 

Nguyen et aI. (2006) report on a case study project that used mobile 

devices to access integrated activities and multimedia content. The 

project, dubbed CoMobile, allowed students to submit questions by 

taking pictures of their notes, share field trip experiences by taking 

videos from mobile phones, and access long text information using 

voice recognition. The CoMobile learning system allowed students to 

apply techniques, such as automatic speech recognition, optical character 

recognition, and text, to speech. 

Hyungsung (2008) utilized PDAs to emphasis visual abstract and conceptual 

information to assess study participants' degree of achievement 

through the learning of non-structured text-only content, structured, 

text-only content, and visualized content. A comparison of the three 

different representations of content on a PDA system revealed that the 

structured text with visuals was more effective in supporting learner 

development and understanding. 

NESTA Futurelab, BBC, NHU, the Mixed Reality Lab (Nottingham 

University) and Mobile Bristol (Hewlett-Packard and University of 

Bristol) conducted a project they referred to as Savannah (Facer et aI., 

2006). This collaboration explored the use of mobile devices to enable 

an interactive experience that would allow students to role play, modeling 

the behavior of a lion. During this simulation, students were able to 

learn about lions while simultaneously roaming in the wild as a lion 

would do. Each student carried a PDA that gave them a window into 

the game-world, displaying content and actions that were appropriate to 

their current location and what was going on in the rest of the game. 

Each PDA could be tracked using GPS and allowed the students to see, 

hear, and smell the virtual savannah they were exploring. The PDA 

screen displayed visual content and indications of scents, and the students 

wore headphones for an auditory experience. The PDAs also 

displayed informative and instructional messages such as "you're hungry", 

"you're too hot", "return to the den". Students also had a den 

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area, to which they could retreat for more reflective learning after being 

out in the field. Students reported favorable opinions regarding the likereal-life 

simulation (Facer et aI., 2006). 

Field Testing of Mobile Learning Applications 

This chapter will report on the findings of a mobile-based trial identified 

as Bronco Mobile piloted at a mid-size university located in southern 

United States during the 2007-2008 academic school year. Together 

with Rave Wireless, the university provided students access to mobilebased 

academic, safety, and community applications utilizing mobile 

phones as an academic and community tool. All current students were 

eligible to participate in the program; however, the one-year trial initiative 

was promoted a great deal in the freshmen orientation courses. 

There were 134 students that responded to the survey, of which 64.2% 

were female while 35.8% were male. In terms of ethnicity, 73.9% were 

African American, 12.7% African, 4.5% Hispanic, 2.2% Caucasian, 

0.7% Asian, and 6.0% other. The students ranged in age with 91% 

between the ages of 17-21, 4.5% 22-25, 1.5% 26-30, 0.7% 31-35, and 

2.2% 36 and older. The majority of the participants were classified as 

freshmen (90.3%) who lived on campus (68.7%). 

To start, the researchers wanted to ftnd out how the study participants 

were currently using technology and their experiences with e-Iearning. 

Participants were asked to rate the their level of computer knowledge; 

only 9.0% rated themselves as expert computer users, while the majority 

felt they were more advanced (40.3%) and intermediate (49.3%) 

users. A small percentage felt that they were beginners (1.5%). 

The survey also asked questions relating to technology ownership. 

Nearly 45% reported owning a desktop computer; 70% own a laptop; 

53% own a cell phone; 32% own an IPOD; 47% own a MP3; only 5% 

own a palm pilot; and less than 2% own an iPhone. 

When asked how much time they spend on the Internet each week, less 

than 1% reported 0 hours, 11.9% spend 1-3 hours, 17.9% spend 4-6 

hours, 31.3% spend 7-9 hours, 14.2% spend 10-12 hours, 9.0% spend 

13-15 hours, 3.0% spend 16-19 hours, and 11.9% spend 20+ hours. 

With respect to e-Iearning, 84% of the students reported that they had 

never taken a fully online course and 66.7% reported not having any 

plans to enroll in the same. Nearly 64% reported they had never read a 

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textbook electronically. However, 79% report using the cell phone to 

access the Internet while 77% reported never using the cell phone to 

take notes for class. 

Students were also asked to determine the likelihood of going online 

for various activities such as blogging, surfing, or e-mail. The results, as 

presented in Table 1, show that an overwhelming 61.2% are almost 

certain to participate in online social networking, while only half that 

percentage (34.3%) were equally as likely to participate in academic 

related activities. As expected, nearly half of the sample population 

reported that they almost certainly go online for e-mail activities. 

Table 1: Students Reported Online Activities 

Activity N ot at all N ot velY Somewhat Likely Almost 

likely likely likely Certain 

Academics 3.0% 5.2% 23.1% 34.3% 34.3% 

Blogging 40.3% 27.6% 13.4% 1l.9% 6.7% 

Burning CD s 19.4% 13.4% 23. 1% 25.4% 18.7% 

D ownloading Music 14.2% 8.2% 20.1% 30.6% 26 .9% 

D ownloading Movies 40.3% 17.2% 14.2% 14.2% 14.2% 

E-mail 2.2% 3.0% 14.9% 34.3% 45 .5% 

Instant Messaging 22.4% 17.2% 13.4% 2l.6% 25.4% 

Gaming 3l.3% 22.4% 18.7% 13.4% 14.2% 

Shopping 32.8% 17.9% 20.9% 16.4% 1l.9% 

Reading N ewsp apers 17.2% 23 .9% 27.6% 19.4% 1l.9% 

Social Networking 7.5% 6.0% 9.0% 16.4% 6l.2% 

Web Surflng 10.7% 6.9% 21.4% 20.6% 40.5% 

Wiki Coilaboration 45.5% 19.7% 13.6% 12.1% 9.1% 

Visiting Libraries 19.7% 15.9% 27.3% 18.9% 18.2% 

Visiting Gossip 39.4% 17.4% 17.4% 15.2% 10.6% 

/ Celebrity Websites 

Vi s itin~ News Websites 18.9% 18.2% 24.2% 18.2% 20.5% 

The survey solicited questions that focused on students' perceptions, 

attitudes, and experiences with Bronco Mobile. Using as-point likert 

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scale, where 1 =not at all likely, 2=not very likely, 3=somewhat likely, 

4= likely, and 5=almost certain, students were asked to rate the quality 

and convenience of mobile learning. The results indicate that less than 

10% of the students reported a high degree of certainty with regard to 

relevance (3.9%), quality (5.2%), meeting learning objectives (2.6%), 

convenience (9.1 %), and ease (5.2%) of mobile learning (see Table 2) . 

Table 2: Students Reported Experiences with Bronco Mobile 

Statement Not at N ot velY Somewhat Likely Almost 

all likely likely likely Certain 

TI,e Bronco Mobile 

experience was fun. 

31.2% 6.5% 35.1% 18.2% 9.1% 

According to my experience, 

I would take a 

mobile learning course 

if relevan t to my learn- 36.4% 11.7% 33.8% 14.3% 3.9% 

ing needs. 

I would recolll1nend 

mobile learning as a 

medlod of study to 

odlers. 

Mobile learning 111- 

creases d,e quality of e- 

learning. 

Course learning objectives 

can be met by 

mobile learning. 

Mobile learning 1S 

convenient for COllllnU1llca 

tion widl students. 

Navigation duough d,e 

mobile leanllng platfonn 

was easy. 

38.2% 9.2% 35.5% 13.2% 3.9% 

31.2% 15.6% 29.9% 18.2% 5.2% 

34.2% 11.8% 38.2% 13.2% 2.6% 

29 .9% 14.3% 29.9% 16.9% 9.1% 

28.6% 7.8% 44.2% 14.3% 5.2% 

Using the same 5-point likert scale, students were asked to determine 

the suitability of a mobile learning course based on their experiences 

with Bronco Mobile. As revealed in Table 3, a large percentage of students 

reported the suitability of mobile learning to be "somewhat 

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likely" for downloading course content (38.2%), communicating with 

the instructor (39.5%), communicating with other course students 

(36%), using graphics and illustrations (34.7%), evaluating and questioning 

(31.5%), increasing access to education and training (34.7%), 

and downloading course material (28.4%). 

Table 3: Students Reported Perceptions of the Suitability for a Mobile Leaming 

Course 

Statement 

N ot at 

all likely 

Not very Somewhat Likely 

likely likely 

Almost 

Certain 

Downloading course content 

would be easy. 

26.3% 

17.1% 38.2% 13.2% 

5.3% 

Communication widl d,e 

instructor of a mobile 

learning course would be 

easy. 

23.7% 

18.4% 39.5% 13.2% 

5.3% 

Mobile leaming is convenient 

for cOlIllnunica tion 

widl odler course students. 

22.7% 

18.7% 36.0% 16.0% 

6.7% 

For mobile leanung to be 

effective, it is n ecessary to 

use graphics & illu strations. 

24.0% 

20.0% 34.7% 14.7% 

6.7% 

Evalu ation and questioning 

in a mo bile leaming course 

would be effective. 

26 .0% 

17.8% 31.5% 20.5% 

4.1% 

Mobile leaming would 

increase access to education 

and training. 

29 .3% 

16.0% 34.7% 17.3% 

2.7% 

TIle cost of downloading 

the mobile course materials 

would be acceptable. 

28.4% 

23.0% 28.4% 17.6% 

2.7% 

TI,e cost of communicating 

111 d,e mobile leaming 

course widl dle instmctor 

and od,er students would 

be acceptable. 

32.0% 

18.7% 29.3% 13.3% 

6.7% 

The Bronco Mobile applications powered by Rave consisted of 

RaveGuardian, RaveAlert, RaveTransit, Rave Email, RaveAcademics, 

RaveGroups, RavePolling, and Rave FlashCard. Participation was voluntary 

on the part of students; thus, there was no indication that faculty 

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utilized or incoroporated the mobile applications into the course. At 

the end of the academic year, a survey was administered to study participants 

asking for students to rate their frequency use for each of the 

components of Bronco Mobile. A description of each application and 

study results are presented herein. 

RaveGuardian served as a security feature for students by allowing 

them to share their GPS location with family, friends, and more importantly 

with campus police. The survey results, as presented in Figure 1, 

show that a large percentage of the students (78.8) never used this 

component of Bronco Mobile. Additionally, only 13.8% reported using 

components very rarely, 5.0% reported occasional use, and 1.2% reported 

use as very frequently and always. 

Figure 1: Survey Results for Rave Guardian 

o 10 20 30 40 50 60 70 80 90 

RaveAlert provided faculty and administrators with the ability to send 

broadcast text alerts to students. Faculty could use this application to 

notify students of class assignment changes, while administrators could 

alert students to school cancellations due to inclement weather or extenuating 

circumstances. As presented in Figure 2, a large percentage of 

students (68.3) reported never using this application, 17.1% reported 

using very rarely, 8.5% reported occasional use while only 3.7% and 

2.4% reported using RaveAlert very frequently and always, respectively. 

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Figure 2: Survey Results for RawAlert 

o 10 20 30 40 50 60 70 80 

RaveTransit served as a tracking device for campus transportation. 

Students were able to identify the GPS location of campus shuttle 

buses as well as information regarding schedules and cancellations. The 

survey results of this application mirrored that of RaveGuardian 

whereby a large percentage of students (78.0) reported that they never 

used the RaveTransit application, 14.6% reported using very rarely, 

3.7% reported occasional use, 1.2% reported very frequent use, and 

2.4% reported that they always used RaveTransit (see Figure 3) . 

Always = 

Figure 3: Survey Results for Rave Transit 

Frequently ~ 

Occasionally I!!!!I 

- 

--- 

---------- - 

o 10 20 30 40 50 60 70 80 90 

RaveEmail allowed students to access a course forum archive to send e 

mail messages to fellow students, instructors, and administrators; to 

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receive e-mail messages from the same; and to submit assignments by 

e-mail attachments, either as text-based e-mail or as Word or text assignments. 

As reported in Figure 4, a larger percentage of students 

(75.0) never used the RaveEmail application, 15.0% reported very 

rarely, 2.5% reported occasional use, 3.8% reported use as very frequently 

and always. 

Figure 4: Survey Results for RaveEmail 

o 10 20 30 40 50 60 70 80 

RaveAcademics provided mobile access to the school's learning management 

platform, Blackboard. Students were able to access their 

courses and view course assignments and announcements. Additionally, 

students were able to download learning content from Blackboard to 

include all course materials (eg. study unit, resources, content page). 

Similarly, a large percentage of students never used RaveAcademics 

(73.2), 12.2% reported using it very rarely, 8.5% reported occasional 

use, 2.4% reported very frequent use, and 3.7 reported that they always 

used this component (see Figure 5). 

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Always == 

Frequently = 

- 

- 

Figure 5: Survey Results for RaveAcademics 

'b~. 

o 10 20 30 40 50 60 70 80 

Using RaveGroups, students were able to interact with friends, clubs, 

organizations, and teams by creating group contacts. This component 

allowed students to send and receive e-mails under group messaging. 

Figure 6 illustrates that a large percentage of students never utilized this 

component (78.0), 13.4% reported using it very rarely, 3.7% reported 

occasional use, while 2.4% reported using very frequently and always. 

Figure 6: Survey Results for RaveGroups 

o 10 20 30 40 50 60 70 80 90 

In an attempt to cultivate increased student involvement and on-the-go 

decision making, RavePolling enabled students to participate in polls as 

well as classroom quizzes by voting and answering questions. Students 

could also create their own surveys. Figure 7 shows that 76.8% reported 

never used RavePolling, 15.9% reported using it very rarely, 

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4.9% reported occasional use, while only 1.2% reported using very 

frequently and always. 

Figure 7: Survey Results for RavePolling 

Always ~ 

Frequently ~ 

- 

Never 

--- -- 

10 20 30 40 50 60 70 80 90 

With the RaveFlashcard application, instructors and students have the 

resources to create mobile flashcard sets through Web interface. The 

flashcards can include text and/or images using material imported from 

Publisher or Excel. The results as expressed in Figure 8 show that 

80.2% reported never using the RaveFlashcard application, 13.6% reported 

very rarely use, 3.7% reported occasional use, while only 1.2% 

reported use as very frequently and always. 

Figure 8: Survey Results for Rave Flashcard 

A variety of cell phones were certified to run the Rave mobile applications 

which included the following: 

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(a) Samsung M520, which features a large screen and slider 

functionality for reading text messages and e-mails, a builtin 

mega pixel camera for pictures and video, and Bluetooth 

compatibility. 

(b) LG LX570 (Fusic II), a basic device for downloading and 

playing music. 

(c) Motorola Q9c, a smartphone designed to access games, e 

mail, and application documents such as Word, Excel, and 

PowerPoint. It features a full keyboard, large screen, and 

speakerphone and is Bluetooth compatible. 

(d) HTC Mogul is designed with the same features as the Motorola 

Q9c with an additional built-in 2 mega pixel camera 

for taking pictures and viewing videos. 

(e) HTC touch, a PDA device with a touch screen navigation 

designed to access games, e-mail, and computer applications 

documents. It also includes a built-in 2 mega pixel 

camera for taking pictures and viewing videos. 

Students were asked to rate the level of ease and use of the equipment 

on a scale from 1 to 5 with 1 being among the worst and 5 being 

among the best. The results as indicated in Figure 9 illustrate mixed 

reviews with 23.4% reporting among the worst and adequate, 10.4% 

reported less than most, while nearly 30% reported better than most 

and only 13% reported among the best. 

Amon!! tho Be.t ======== 

Better than Most ================== 

Figure 9: Survey Results for Bronco Mobile Equipment 

The costs associated with the Bronco initiative included the price of the 

cell phones, which ranged from $49.99 to $249.99, and the price of 

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service plans, which included a variation of anytime minutes for cell 

phone usage (see Table 4), nationwide calling, unlimited free nights and 

weekends, unlimited text messaging, and unlimited mobile-to-mobile. 

Table 4: Bronco Mobile Monthly Phone Plans 

0 400 1000 1400 2000 

Anytime Anytime Anytime Anytime Anytime 

Minutes Minutes Minutes minutes minutes 

$39.99 $51.99 $67.99 $82.99 $99.99 

Students were also asked to rate the cost associated with Bronco Mobile. 

The findings, as presented in Figure 10, point out that a large percentage 

of the students (39.5) felt that the cost was adequate; however, 

many also felt that the cost was among the worst (30.3) while 7.9% felt 

it was less than most, 17.1 % felt it was better than most, and only 5.3% 

felt the cost was among the best. 

Amonll the B •• t = 

Betterthan Most ======== 

Adequate 

Figure 10: Survey Results ror Bronco Mobile Cost 

-------------------------------------- 

--- --- ---------------------- 

Amonll the Wont 

o 5 10 15 20 25 30 35 40 45 

In summary, nearly 70% of the study participants reported never using 

any of the Rave applications developed specifically for the Bronco Mobile 

initiative. An estimated 30% reported that the ease and use of 

equipment employed in this study was better than most while nearly 

40% felt as though the cost of the equipment and calling plans was 

adequate. 

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Final Thoughts and Comments 

Emerging from e-Iearning, mobile learning is going to be a significant 

next wave of learning environments. This is an evolving research area 

and many issues regarding mobile learning have not yet been exhaustively 

covered (Goh & Kinshuk, 2006). 

Current study results indicate that less than 10% of the students reported 

a high degree of certainty with regard to relevance, quality, 

meeting learning objectives, convenience, and ease of mobile learning. 

Across the board, students were neutral regarding the suitability of 

mobile learning in mainstream education with an overwhelming onethird 

of the sampled population reporting "somewhat likely". Additional 

study analysis suggests that the majority of the participants found 

the mobile-based applications to be insignificant, with a large percentage 

reporting having never used the applications: Guardian (78.8), Alert 

(68.3), Transit (78.0), E-mail (75.0), Academics (73.2), Groups (78.0), 

Polling (76.8), and Flashcard (80.2). Despite the minimal usage of the 

customized mobile components, the majority of the participants found 

the equipment certified to run the Rave mobile applications to be easy 

to use and priced adequately. 

As we move forward with mobile education, it is important to identify 

and assess those strategies that will undoubtedly enhance learning. A 

recommendation from Traxler (2006) points to innovative lectures, 

exemplar content, access to a variety of wireless and mobile devices, 

and reliable and robust technical support as key factors that will provide 

continued improvement in performance and usability relating to 

mobile learning. If we are to continue to engage students in the field of 

mobile learning, we must persist in identifying flexible models of teaching 

that allow students to study and learn at any time and any place. As 

Peters (2007) states, "m-Learning lends itself to new methods of delivery 

... that are highly suited to the 'just enough, just in time, and just for 

me' demands of 21 st century learners." 

References 

Colella, v., Borovay, R. & Resnick, M. (1998). Participatory 

Simulations: Using Computational Objects to Learn About 

Dynamic Systems. Proceedings ofCHI1998. 

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Dufresne, R, Gerace, W., Leonard, W., Mestre,]., & Wenk, L. (1996). 

"Classtalk: A Classroom Communication System for Active 

Learning", Journal of Computing in Higher Education 7,3-47. 

Dawabi, P., Wessner, M. & Erich, N. (2004). Using Mobile Devices for 

the Classroom of the Future. (In ed. Attewell,]. & Savill-Smith, C. 

Learning with Mobile devices: Research and Development. 

Published by the Learning and Skills Development Agency. 

Facer, K., Stanton, D., Joiner, R, Reid,]., Hull, R, & Kirk, D. (2004). 

Savannah: A Mobile Gaming Experience to Support the 

Development of Children's Understanding of Animal Behavior. 

Journal of Computer Assisted Learning, 20(6),399-409. 

Goh, T. & Kinshuk. (2006). Getting Ready for Mobile Learning 

Adaptation Perspective. Journal of Educational Multimedia and 

Hypermedia, 15(2), 175-198. 

Hyungsung, P. (2008). The Effect ofInformation Visualization and 

Structure on Mobile Learning. Journal of the Research Center for 

Educational Technology, 4(1), 1-8. 

JISC (2005). Innovative Practice with e-Learning: A good Practice 

guide to Embedding Mobile and Wireless technologies into 

Everyday Practice. Higher Education Funding Council for England 

(HEFCE). 

Kukulska-Hulme, A. (2006). Current Uses of Wireless and Mobile 

Learning. Landscape Study in Wireless and Mobile Learning in the 

post-16 sector-JISC e-Learning Programme. 

Nguyen, D., & Guggisberg, M., & Burkhard, H. (2006). Multimedia 

Information and Mobile-Learning, Eighth IEEE International 

Symposium on Multimedia, 938-946. 

Peters, K. (2007). M-Learning: Positioning Educators for a Mobile, 

Connected Future. International Retiew of Research in Open and 

Distance Learning, 8(2), 1-17. 

Roschelle,]., Vahey, P., Tatar, D., Kaput,]. & Hegedus, S]. (2003). 

Five Key Considerations for Networking in a Handheld-Based 

Mathematics Classroom. Paper Presented at the International 

Conference of Psychology in Mathematics Education, Honolulu, 

Hawaii. 

Traxler,]. (2007). Defining, Discussing, and Evaluating Mobile 

Learning: The Moving Finger Writes and Having Writ ... 

International Retiew of Research in Open and Distance learning, 8(2), 1-12. 

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Traxler, J. (2006) . Strategic Aspects of Wireless and Mobile Learning. 

Landscape Study in Wireless and Mobile Learning in the post-16 

sector--:JISC e-Learning Programme. 

Wang. H ., Liu, T., Chou, c., Liang,J., Chan, T ., & Yang, S. (2004) . A 

Framework of Three Learning Activity Levels for Enhancing the 

Usability and Feasibility of Wireless Learning Environments. 

Journal of Educational Computing Research, 30(4), 331-351. 

Note & Acknowledgement 

The original version of the Bronco Mobile research results were previously 

published in the Proceedings of the 2008 International Conference 

on Global Issues in Business & Technology, National Institute of 

Financial Management, Ministry of Finance, India, Faridabad. 

The author would also like to acknowledge Daniel Okunbor for his 

support, guidance, and valued research contribution on the Bronco 

Mobile Pilot Initiaive. 

Author 

Dr. Retta Guy has an Ed.D. in Curriculum and 

Instruction with emphasis in Instructional Systems 

Design from the University of Kentucky. She received 

her masters in Public Administration from 

Kentucky State University and a Bachelor of Arts 

degree in Business Education from the University of 

Kentucky. Currently, she is an Associate Professor 

in the Department of Business Information Sytems 

at Tennessee State University in Nashville, Tennessee. Online teaching 

and mobile learning serves as the basis for her current research for 

which she has presented at conferences and published in refereed journals 

and book chapters. She has and continues to conduct workshops 

and training sessions on the use of web-based course management 

tools as well as mobile learning technologies. 

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Guy, R (Ed.). (2009). 



Chapter 8 

Design and Assessment of E-Learning and 

M-Learning Tools for the Degree in 

Actuarial Sciences 

Marfa Cruz Mayorga-Toledano and 

Antonio Fernandez-Morales 

Introduction 

During the last six years, a multidisciplinary team of teachers has been 

developing e-Ieaming and m-Ieaming tools for several courses in the 

degree in Actuarial Sciences at the University of Malaga (Spain). Our 

aim is the efficient integration of e-Ieaming and m-Ieaming instruments 

into a blended learning strategy, combining traditional and digital contents. 

Although the University of Malaga has made important efforts in 

developing its on-line campus, it is not a distance-learning centre and 

requires a significant 'face to face' component in the curricular design 

of all the main and compulsory courses. 

The degree in Actuarial Sciences is quite recent in our University (It 

started in 1997.) and shows some peculiarities that encourage the use of 

e-Ieaming and m-Ieaming techniques to improve the efficiency of the 

learning process. We have many students with a finished degree in 

Economics, Business Administration, Law, or Statistics and who are 

currently working. In addition, the 'face to face' sessions are attended 

regularly only by 30% of the students, and there is also a significant 

group of students with an irregular attendance, conditioned by their 

working conditions and status. 

In this paper, we use the term 'e-Ieaming tool' to describe those learning 

tools typically used in a web based learning process, identifying e 

learning with distance learning in which the main technological tool is a 

personal computer and an Internet server is the principal communica- 

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tion and distribution channel (puustjarv and Poyry, 2006). In contrast, 

the term 'm-Ieaming tool' is applied to those learning tools specifically 

designed for wireless phones and handheld devices, i.e., considering m 

learning as the intersection between e-Ieaming and mobile computing 

with wireless phones and handheld devices (11otiwalla, 2007). 

This chapter describes the design, the development, and the assessment 

of the blended learning strategy that we use in the degree in Actuarial 

Sciences at the University of Malaga. It first discusses the general 

scheme of the strategy. Next, it describes the e-Ieaming and m-Ieaming 

tools that we have developed, and then presents the main results of the 

assessment, carried out by means of surveys about the students' opinions 

and satisfaction. Finally, the last section includes the main conclusions 

of our study. 

A Blended Learning Strategy for the Degree in 

Actuarial Sciences at the University of Malaga 

The original use of the term 'blended learning' was often associated 

with simply linking traditional classroom training to e-Ieaming activities, 

such as asynchronous work (typically accessed by learners outside the 

class at their own time and pace). However, the term has evolved to 

encompass a much richer set of learning strategies or dimensions: 

blending online and offline learning, blending self-paced and collaborative 

learning, blending structured and unstructured learning, blending 

learning and practice (Singh, 2003). 

The learning strategy that we have developed can be included under the 

broad category of blended learning (b-Ieaming) due to the coexistence 

of distance learning and 'face to face' components in our courses design. 

Our learning strategy combines 'face to face' classroom activities 

in the traditional classroom and the Faculty's computer lab with synchronous 

and asynchronous web-based learning activities. But it also 

combines structured with self-paced activities and e-Ieaming tools with 

m-Ieaming tools. 

The general scheme of the learning strategy that we have been using 

during the last six years is shown in Figure 1. The interaction between 

teacher and students takes place (i) on a 'face to face' basis in the traditional 

classroom and the computers lab of the Faculty, and (ii) via a 

content server. This server centralizes, by means of a MoodIe platform, 

all the courses at the on line campus of our University, distributes sev- 

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Design and Assessment r!f E-Learning and M-Learning 

TEACHERIS 

,--n1l4 

\ lJJf r---oD>E> SERVER 

) 

~) ~ •. ~ 

I " - -' I -- \ 

CLASSROOM 

STUDENTS 

Figure 1: Framework of the blended learning strategy. 

eral kinds of course materials, depending on the receptor devices, and 

manages several communication tools like course e-mail, chat, and 

forum. At the computers lab, equipped with pes, our students can 

attend scheduled sessions with or without teacher, as well as benefit 

from a free access regime. But we have also designed many activities 

and resources for the students, managed and distributed through the 

MoodIe platform, which allows them to complete the activities at any 

place with a laptop, and some of them with small electronic devices 

with wireless capacity, like mobile phones or PDAs. 

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Usually, students accept pedagogical models only if they bring positive 

outcomes and if students gain some kind of credits for their extra work. 

Since continuous learning during a whole course is vital for manifest 

learning, we introduced the compulsory feature in some of the web 

based activities. With this strategy almost 100% of the students complete 

their compulsory activities, and we observe better study habits 

and motivation, in a similar way as Karlsson et aI. (2007) or Chen et aI. 

(2006). The composition of the compulsory activities varies slightly 

from year to year, but we always maintain a second group of optional 

activities, in order to increase the flexibility of the learning process and 

allow the possibility of a self-assessment process. All the m-Iearning 

tools are included, at present, in this group of optional activities. 

In addition, we also consider that higher education is highly enriched 

with the direct and personal contact between teacher and student that 

take place in the traditional 'face to face' sessions, which also serve as 

the main guide to follow every course. In a recent study, Dabbagh and 

Kitsantas (2005) also found that the majority of the students in their 

survey reported that blended interactions were more beneficial to their 

learning. 

Therefore, we are basing our strategy on the idea that learning is not 

just a one-time event, but a continuous process, and so blending provides 

various benefits over using any single learning delivery medium 

alone, like extending the reach, optimizing development cost and time, 

and increasing effectiveness (Singh, 2003). 

E-Learning and M-Learning Tools 

Didactic materials in electronic support are the essential part of an e 

learning and/or m-Iearning environment. They should not be just 

transpositions of traditional learning materials into electronic formats; 

they should be enriched with interactive tools (e.g. interactive questions, 

online tasks, online assessments, hyperlinks, and interactive multimedia 

elements such as simulations and interactive video) and appropriately 

designed multimedia (Lapuh Bele and Rugelj, 2007; Shen et aI., 

2007). 

First generation e-Iearning (digitally delivered learning) programs 

tended to be a repetition or compilation of online versions of classroom-based 

courses. In the next wave of e-Iearning programs, an increasing 

number of learning designers are experimenting with blended 

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learning models that combine various delivery modes. There is some 

evidence supporting that blended learning not only offers more choices 

but also is more effective (Singh, 2003). 

The didactic tools that we developed are based on a flexible design. 

Our intention is that the students may adapt as necessary their learning 

processes to the digital media more beneficial for them, depending on 

their resources availability or their position in the learning curves of the 

new technologies. Accordingly, we offer some of the didactic resources 

through several channels or media. We also try to exploit the reusability 

of the developed learning objects, using the structures or the contents 

of the learning objects of a course in the developing of objects for 

other courses. As a consequence, the students are familiar with some 

learning tools because they previously used any other one with a similar 

structure, and the time and effort of producing didactic tools is reduced. 

We have designed a wide variety of e-Ieaming and m-Ieaming digital 

contents in different formats, some interactive and some noninteractive. 

Our strategy integrates several of the elements present in 

the Sharples (2000) framework of five approaches for using technology 

in learning (simulation and modelling tools, system tools and resources, 

and communication aids). Our learning tools also fit into almost all of 

the learning object types of Churchill (2007): presentation, practice, 

simulation, conceptual models, information, and contextual representation 

objects. 

These learning tools have been designed considering the strengths, but 

also the weakness, of each platform and technology used, especially in 

the case of the m-Ieaming resources (Motiwalla, 2007; Virvou and Alepis, 

2005), as well as the adequate integration into the general pedagogical 

strategy of every course. 

Within the e-Ieaming resources that we developed, the most interesting 

are: 

1. Interactive tests. All the courses in our project offer a series of 

interactive tests that allow the students to self assess their level of 

competency by courses and thematic blocks in every moment 

and place. The interactive format generates a real time response 

that also permits repeating the tests in order to get better results. 

These tests are available as activities in the MoodIe platform, but 

also as Flash based interactive clips. The first format is integrated 

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in the assessment system of the Moodle platform and every attempt 

is registered as well as its grade. However, the tests in 

Flash clips are not connected with the assessment system, and 

therefore the student can do them as may times as he or she likes 

without the sensation of being 'observed' by the teacher. 

11. Interactive modules. For every course we developed some interactive 

modules available on line to complement the course materials, 

which include tutorials and simulators. The tutorials are designed 

as Flash clips and the simulators are compiled into Java 

applets. We have already used Java applets with good results in 

other courses, like Statistics for Tourism (Fernandez Morales, 

2002). The choice of Flash format gave us good results for its 

simplicity in design, many interactive possibilities and easy online 

delivering through the MoodIe platform. 

An example of a simulator is shown in Figure 2. This simulator contains 

interactive graphics of the main biometric functions of the Makeham 

model for the human life duration. The student can modify the 

parameters values, obtaining a real time response of the functions in 

the graphics. These simulators are integrated into a series of activities 

(three or four for every model) in which the student must experiment 

with the models in order to realize the main features of each model and 

their possibilities to fit several data sets. 

We have also developed some m-Iearning resources, which we call 

micro modules, specifically designed for Java enabled mobile phones 

(they are suitable for PDAs, too, but currently the presence of this kind 

of electronic devices within our students is almost inexistent). Based on 

a survey concerning our student's attitudes towards the didactic use of 

mobile phones, we decided to compile the micro modules as Java 

midlets. Java midlets are small applications developed in Java programming 

language that can be executed in mobile phones and PDAs. 

These midlets can be downloaded to the device and be used off-line 

later, that is, the connection to the telephone network is only needed 

for the downloading and not for the execution of the midlet, thus 

minimizing the economic communication costs. In a previous work we 

developed some didactic resources for mobile phones using W AP platforms 

(Mayorga Toledano, 2002) that need a continuous connection to 

the telephone network, but the experience was not fully satisfactory. 

The fmal survey of that project revealed that our students did not want 

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Design and Assessment if E-Learning and M-Learning 

MODHO ll[ MAKEIiAM Ac" ..... dad 2 

En la venlans de graticos se incluyen cuatro funciones del modele biometri co de Makeham . siguiendo la especificacion 

#~= A+ &~, A2. - B,B>O.~>I,x:o:.O 

Elmod elosepresentainicialmentecon losparametros: 

A=0.0001 8=0.0001 c=1.1 

En el gratico dela funci6n I~se ha representado en rojo los puntos correspondien1es a algunosvalores de la fundan desuper.i\'encia estimada porellnsiluto 

Nacional de Estadistica para Is poblacidn espaliola l'emenina en 1998-99. Busque una combination de valores de los parametros A. Bye cuyo modelo describa 

adecuadamentela mortalidadeslimadaporeII N .E. 

\PI ... ,.,..- ...... vtl ..... U'O"O.0004 y S-G.OOOIlO' ) 

Modifying the parameter values 

and pressing 'actualizar ' button 

a real time response of the model 

functions is obtained 

-- 

scombinacionesposibles . Entreotras 

A=O ,0004 

8=0,000001 

c=1 .1435 

Figure 2: An example of of an interactit'e simulator (Makeham model). 

to assume the costs of connection, and therefore we turned into the 

developing of applications that can be executed off-line, 

Being conscious of the technical limitations of mobile phones, we designed 

deliberately small modules that can be used off-line (Mayorga 

Toledano and Fernandez-Morales, 2003), The availability of Java enabled 

devices within our studentbody has evolved in a clear increasing 

tendency, according with the general market in Spain, The last initial 

survey, carried out in 2008, showed that only 16% of our students had 

a mobile phone without Java capabilities, This survey also revealed that 

the most wanted modules for this device were a) pedagogical assistants, 

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like exams calendar or tutor hours, and b) small tests and frequent errors. 

Taking into account these results, we designed two basic types of 

midlets: one containing an interactive micro test and the other containing 

an interactive module of frequent errors, which includes the correct 

answers. In addition to the test questions or the frequent errors, both 

midlets have a small menu with information about the course, tutoring 

hours, and exams calendar. Therefore, the m-Iearning objects that we 

have designed belong to Sharples categories (2) and (3) : simulation and 

modelling tools, and system tools and resources. 

Figure 3 shows an example of the menu of a middlet containing an 

interactive micro test. As mentioned above, the initial menu includes 

entries with general information about the course, name, teacher, web 

page, etc. (Info), calendar (Fechas), and tutor hours (Tutorias) . The content 

of the tests was designed with the limitations of the size screen and 

memory limitations of this kind of devices as restrictions. Therefore, 

we included in each micro test only five very short questions concerning 

the most important concepts in every lesson. Once selected a question, 

the user must choose an answer and press the check (Comp) but- 

Figure 3: An example oj a micromodule. 

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ton, this action results in a new screen that shows during several seconds 

whether the answer is correct 0 incorrect and returns to the initial 

menu, in the first case, or to the choice of answers screen to select 

another one, in the second case. 

The midlet that contains the micro module of frequent errors has a 

similar design and functioning as the described for the interactive test. 

This type of midlet also includes an initial menu, with entries for general 

info, calendar, tutor hours and frequent errors. In the frequent 

errors section, the user can choose between five frequent errors. Once 

one is selected, the screen displays a concise sentence that is incorrect 

and a button, which activates a new screen with the correct version and 

a short explanation. 

Assessment of the Proposed Strategy 

We assess the efficiency of our pedagogical strategy by means of several 

surveys regarding the students' satisfaction and opinions. At the beginning 

of the first semester, students are asked to fill out an initial questionnaire. 

In the questionnaire, learners were asked to express their 

opinion about: traditional learning materials and web based learning 

materials, experience in web based and blended courses, as well as their 

availability of electronic (laptop or PC, mobile phone, PDA) and Internet 

resources (Internet connection at home). In the last two weeks of 

the semester, all the students that participate in the project are asked to 

complete a final questionnaire about the perceived usefulness of the 

pedagogical tools, the general pedagogical strategy, and their general 

satisfaction about the learning process of the course. With these final 

surveys we evaluate the most important features of the design and quality 

of our course materials and the blended learning strategy in which 

they are integrated. In a recent study about the factors influencing 

learner satisfaction in e-Iearning, Sun et al. (2007) found that within the 

13 identified factors, only seven were significant (learner's computer 

anxiety, instructor attitude toward e-Iearning, e-Iearning course flexibility, 

e-Iearning course quality, perceived usefulness, perceived ease of 

use, and diversity in assessment). Our final surveys are related to five of 

these factors, and we are planning to expand our questionnaires to 

include all of them in the next courses. Table 1 summarizes the surveys 

that were done since the beginning of the project in 2003. 

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Table 1: SUrt'rys 

Type Contents Date Academic 

year 

Initial survey Electronic and Internet resources First two 2003-2004 

availability, technology attitudes weeks of the 2004-2005 

and experience, preferences about first semester 2005-2006 

digital vs. traditional didactic re- 2006-2007 

sources 

2007-2008 

Final survey Electronic and Internet resources Last two 2003-2004 

availability, usefulness and variety weeks of the 2004-2005 

of the didactic tools, satisfaction course 

with the course organization and 

the assessment method, satisfaction 

2005-2006 

2006-2007 

2007-2008 

with the overall 

experience 

Our initial surveys always contain an exploratory analysis of electronic 

resources and Internet availability. Figure 4 shows the evolution of the 

main variables obtained from this part of the surveys (including the last 

available data from the 2007-2008 final survey). It is important to notice 

that 2008 is the first year in which 100% of our students have a 

computer (laptop or PC) at their homes. The surveys of the last two 

academic years yielded values of 78% and 87%, respectively. Regarding 

Internet access, this year we found that 93% of our students are connected 

at home via broadband. This is the result of a significant increment 

over the last years, noting that in 2003 this figure was 76%, but 

only two years ago, only the 67% of our students had an Internet connection 

at home. 

In addition, the access to the digital contents is mostly carried out from 

their homes, with a scarce access from the Faculty's labs: only 8% of 

the registered accesses this year. This fact supports the great interest of 

asynchronous delivering of contents and the importance of increasing 

the flexibility of the learning calendars and locations. 

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100 

80 - 

60 . 

f. 40' 

"?2Y 

' --_ .. 

, , ,---- 

, 

~ , ,, 

" 

, " 

--- --- 

, 

--" 

20 - 

o . 

2003 2004 

2005 

2006 

2007 2008 

-Computer at home 

-Intenet at home 

--- Course access: Faculty Lab 

-Course access: Home 

- - Previous use of Moodie - - Java enabled phone 

Figure 4: Technological em.ironment of our students. 

The main part of our final surveys explore the opinions of the students 

about the effect of the learning objects over their learning process. For 

the whole project, in the last academic year (2007-2008), 44% of the 

students answered "very much" (five in a scale 1-5) to the question 

''Does the use of these e-Ieaming and m-Ieaming materials help you in 

the learning process of the course?" and 31% answered "quite much" 

(four in the scale). Only 7% answered "little" and 3% answered "nothing" 

(one and two in the scale). There is certain variation between subjects 

that we attribute to the different volume of electronic resources 

delivered, since the course with the smallest values (67% of answers 

"'very much" and "quite much" combined) is the one with less e- and 

m-Ieaming tools. 

Table 2 shows the means and standard errors of the responses by type 

of didactic resource, corresponding to the last academic year (2007- 

2008). From the results shown in the table it is clear that our students 

value e-Ieaming tools more highly than m-Ieaming ones. In addition, 

the resources with the highest means are tests (4.29) and cases (4.32). 

These two types of e-Ieaming tools are also the ones with the highest 

Pearson's correlations with the variable that measure the overall satisfaction 

with the learning experience. 

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Variable 

Table 2: Main statistical results of the 2007-2008 final SUrt'ry 

Usefulness in the learning process of: 

Mean" Standard Correlation 

error with O.S. 

E-Iearning tools: Tests 4.29 0.14 0.52 

Tutorials 4.00 0.17 0.43 

Simulators 4.09 0.19 0.38 

Cases 4.32 0.11 0.53 

M-Iearning tools: Calendar 3.56 0.12 0.48 

Tutor hours 3.12 0.14 0.36 

Micro tests 3.59 0.17 0.52 

Frequent errors 3.24 0.16 0.45 

Satisfaction with the Moodle platform 4.00 0.15 0.30 

Usefulness of e-mail 3.74 0.20 0.24 

Satisfaction with the assessment method 2.96 0.12 0.32 

Overall satisfaction (O.S.) with the aca- 4.09 0.13 1.00 

demic experience 

'All the variables in the table are measured in a five point scale 1-5. 

The m-Ieaming resources evaluated in our survey are those included in 

the micro modules for mobile phones: calendars, tutor hours, frequent 

errors and micro tests. In general, these tools show lower means (in the 

range 3.12-3.59) than those corresponding to our e-Ieaming resources 

(in the range 4.00-4.32), but the correlations with the overall satisfaction 

variable are of a similar magnitude. The m-Ieaming resources with 

higher means are the micro tests and the calendar tool - a pedagogical 

assistant that is included in all the micro modules - that show mean 

values of 3.59 and 3.56, respectively. In addition, the micro test tool has 

also been better valued than the frequent errors one (with a mean of 

3.29), revealing again the preference of our students for interactive 

tests. 

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The University of Malaga adopted a MoodIe platform for all the 

courses in its virtual campus in 2004. Since then, our project is based in 

this platform to deliver digital contents, as well as to organize the activities 

and as a communication channel between teachers and students. In 

our surveys we also check the opinions about the platform and its utility. 

Currently, our students are well familiarized with the MoodIe platform. 

The last survey reveals that 89% of our students had taken at 

least one course through the platform before enrolling in the Actuarial 

Sciences degree (Figure 4). The level of satisfaction with the platform is 

notable, with a mean of 4.0 in the last survey (Table 2). Within the 

communication tools of the platform, we favoured the use of the internal 

courses e-mail. The use of this tool is increasing in the last years, 

although the 'face to face' component of our courses is still preferred 

by our students. The MoodIe e-mail system was used in the last course 

at least once by 57% of the students, who valued its utility with a mean 

of3.74 in the last survey (Table 2). 

Finally, the main results obtained in our surveys suggest that the majority 

of the students are satisfied with the experience and the blended 

learning strategy that we adopted, considering that it helps them in the 

learning process. The number of students declaring their academic 

experience as "satisfactory" or "very satisfactory" is always above the 

70%, with a mean of 4.09 in the last survey (Table 2), although there is 

some variability by subject and course. 

Conclusions 

Blended learning combines e-Ieaming and m-Ieaming with traditional 

classroom training. The combination of web based and mobile oriented 

activities with instruction in the classroom achieves a flexible course 

design that can be very useful to reach and educate a heterogeneous 

group of students, as the one in our study, with a variable degree of 

attendance and learning styles. 

We have designed a wide variety of digital contents in different formats, 

some interactive: tests (html-javascript, Flash, and Java Me), tutorials 

(Flash), simulators Qava applets), and some non interactive: case studies 

(pdf and Microsoft Excel), assignments (pdf). We classify these resources 

into two broad categories: e-Ieaming tools and m-Ieaming 

tools, distinguishing by the type of device in which they are used (PCs 

or laptops in the first group and Java enabled phones in the second 

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one). The learning materials have been integrated into a blended pedagogical 

strategy for the courses in the first year of the Degree in Actuarial 

Sciences at the University of Malaga, which we are using during the 

last six years. 

In order to assess the efficiency of our learning strategies we carried out 

several surveys concerning the students' satisfaction and opinions. The 

main results suggest that the majority of our students are satisfied with 

the experience and with the blended learning strategy, considering that 

it helps them in their learning process. In addition, the access to the 

digital contents is mostly carried out from their homes (with a scarce 

access from the Faculty's labs). This fact supports the great interest of 

asynchronous delivering of contents and the importance of increasing 

the flexibility of the learning calendars and locations. 

The results of the surveys indicate that interactive tests and cases are 

the e-Iearning tools best valued by our students, who consider them the 

most useful ones in their learning process. The valuations of these two 

resources are also the most correlated ones with the variable that measures 

the overall satisfaction of the course. 

The results of the students' perception of the usefulness of our m 

learning tools are also satisfactory, with mean values that range from 

3.12 (tutor hours) to 3.59 (micro tests) in a scale 1-5, although, in general, 

e-Iearning tools are better valued than m-Iearning ones. This can 

be explained by some facts like (i) our m-Iearning tools have a more 

limited nature and features than our e-Iearning tools, and (ii) almost all 

students have positives experiences in previous courses with the use of 

e-Iearning tools, but the m-Iearning ones were new for them. 

Within the four assessed m-Iearning tools - two interactive tools (micro 

tests and frequent errors) and two 'pedagogical assistants' (calendar and 

tutor hours) - the micro tests and the calendar are the most preferred 

ones by the students. The preference for micro tests over the other m 

learning interactive tool, the frequent errors micro module, seems to 

reinforce the favourable response obtained by interactive tests also 

observed in the evaluation of the e-Iearning tools. In addition, the calendar 

tool obtained almost the same average than the micro test tool in 

our last survey, supporting the fact that students can perceive a pedagogical 

assistant in an m-Iearning environment as useful as any other 

didactic resource. 

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To conclude, it is important to note that final academic results of the 

courses included in this project are very good. The number of participants 

who finished the courses successfully has never been below 70%, 

reaching 85% in some cases. These figures are generally above the average 

of the whole Degree in Actuarial Sciences that is usually around 

70%. 


The fmancial support of the Services of Educative Innovation, Virtual 

Learning and Technological Laboratories of the University of Malaga 

(project PIE07-10) is gratefully acknowledged. The authors extend their 

thanks to the two anonymous referees for their valuable advice and 

helpful comments. 

References 

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Method Teaching in an Online Asynchronous Learning 

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513-540. 

Fernandez Morales, A. (2002). "Teaching seasonality with SISMO: an 

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Educational Technology. Vol II. Consejeria de Educaci6n, Ciencia y 

Tecnologia, Badajoz, Spain. 

Mayorga Toledano, M. e. and Fernandez Morales, A. (2003): "Learning 

tools for java enabled phones. An application for actuarial studies", 

in J. Attewell et aL (coords.) MIEARN 2003. Learning with mobile 

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Motiwalla, L.F. (2005): "Mobile learning: A framework and evaluation", 

Computers and Education, 49 (3), pp. 581-596. 

Puustjarv, J. and Poyry, P. (2006) "Information Retrieval in Virtual 

Universities" InternationalJournal Distance Education Technologies, 4 (3), 

36-47. 

Sharples, M. (2000) 'The design of personal mobile technologies for 

lifelong learning', Computers and Education, 34, 177-193. 

Shen, R., Wang, M. and Pan, X. (2007). Increasing interactivity in 

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Singh, H. (2003): "Building Effective Blended Learning Programs", 

Educational Technology, 43 (6), 51-54. 

Sun, P.e., Tsai, R.J., Finger, G., Chen, Y.Y. and Yeh, D. (2007): "What 

drives a successful e-Learning? An empirical investigation of the 

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44,53-68. 

Authors 

Maria Cruz Mayorga-T oledano is Profesor Contratado Doctor in the Department 

of Private Law of the University of Malaga (Spain) and teaches 

at the Faculty of Economics of the Malaga University, since 1994. She has 

special interests in the teaching and learning of private Law, bank and 

insurance regulation. Maria Cruz has coordinated several innovative projects 

in new technologies in higher education and its adaptation to the new 

European Space for Higher Education in the University of Malaga. Email: 

mcmayorga@uma.es 

Antonio Fernandez-Morales is Proftssor Titular de Unitmidad at the 

Department of Applied Economics of the University of Malaga (Spain) 

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and teaches at the Faculty of Economics and the School of Tourism of 

the Malaga University, since 1988. He has been involved in several projects 

of new learning tools in e-Ieaming. He has special interests in the 

teaching and learning of Statistics. Email: afdez@uma.es 

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Guy, R (Ed.). (2009). 



Chapter 9 

Understanding User Experience to Support 

Learning for Mobile Journalist's Work 

Heli Vaataja, Anssi Mannisto, 

Teija Vainio and Tero Jokela 

Introduction 

This paper presents a case study of mobile learning related to journalism 

education. The goal of our study was to explore the factors affecting 

user experience in the case of mobile journalism, which was set in 

an educational context. User experience is often defmed to be a consequence 

of the interaction between a user and a product, system, or 

service. It is affected, e.g., by the characteristics of the user and the 

system as well as by contextual factors. In this paper we concentrate 

especially on the temporal nature of user experience, namely the relationship 

of prior experiences and expectations and user experience as 

well as the motivational aspects related to user experience. 

We present a case study, the MappiE 24h project, on university-level 

teaching and learning. The MappiE 24h project was part of a project 

work course for graduate students in journalism. The objective of the 

project was to experiment and learn how to produce a real-time web 

publication with mobile tools. Based on this case study, we present 

factors which affect user experience in the formal, situated learning 

context and discuss the implications of the findings for educators as 

well as for producers of mobile devices, applications and services, 

whose systems are aimed to be used this type of learning context. 

Learning in Mobile Context 

Mobile learning is gaining increasing attention both in the field oflearning 

in general and in the field of designing mobile systems and services 

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for learners. This development is also evidenced by the growing interest 

to study these phenomena scientifically. However, the variety of deftnitions 

and approaches that are related to learning with handheld devices 

or to mobile learning or to m-learning is extensive. Sharples (2000), 

Robertson, Calder, Fung, Jones, and O'Shea (1997), and Nyiri (2002) 

were the first ones to emphasize the need to understand the use and 

effectiveness as well as the design issues in addition to the philosophical 

issues of mobile learning. 

When exploring mobile services for learners, it is important to understand 

the phenomena of mobile learning itself, as well as how to design 

and evaluate services and tools to support learning in varying mobile 

contexts to be able to develop better services and tools. O'Malley et al. 

(2003) developed guidelines for teaching and learning in mobile environments, 

whereas Thomas, Scott, and Kambouri (2003) present usability 

guidelines for educational games in the mobile learning context. 

Guidelines for system designers for understanding the adoption of 

mobile learning are described by Vavoula, Lefrere, O'Malley, Sharples, 

and Taylor (2004), encompassing the recognition of key stakeholder 

needs. 

With respect to development of mobile learning from a humancomputer 

interaction (HCI) perspective and when focusing on technical 

capabilities of mobile devices and applications, we are lacking 

deeper understanding of the impacts that using mobile technology has 

in varying contexts and which factors affect the user experience of 

learners. Therefore, when developing mobile learning tools, we should 

gain a broader view of the impacts of user experience and evaluate 

impacts of usability related factors as we develop better tools for mobile 

learners. McGovern and Gray (2005) stated that implications for 

the learning experience should be explored. By the learning experience 

they refer to, e.g., the usefulness of learning resources and activities, or 

whether mobile learning can be mandatory or optional. 

According to Livingstone (1999), learning can be classified into a) external 

or b) internal structure and into c) external or d) internal initiation. 

If learning is externally initiated and structured, it is formal learning. 

In our case study, we explore formal learning among university 

students who in their future work as a journalist are increasingly utilizing 

mobile systems and services at their work. Furthermore, when exploring 

the learning theories in relation to the usage of mobile technology, 

Naismith, Lonsdale, Vavoula, and Sharples (2004) found the fol- 

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Understanding User Experience to Support Learningfor Mobile Journalist's Work 

lowing six categories of theories: 1) behatiourist, 2) constructitist, 3) situated, 

4) collaboratit'e, 5) informal and lifelong and 6) learning and teaching support. We 

find that the situated learning paradigm, introduced by Brown, Collins, 

and Duguid (1989) and Lave (1991) referring to learning within an 

authentic context and culture, is most salient to our case study with 

journalist students. In situated learning, knowledge is presented in authentic 

context and learners are participating in community in practice 

(see Naismith et aI., 2004). 

Trends in Mobile Journalism 

The selection of devices a journalist uses in his or her work is changing 

rapidly. Sophisticated mobile multimedia computers or camera phones 

are at the core of this development. These devices (e.g. the Nokia Nseries) 

can be used in a way where one single device is employed in multiple 

purposes within the journalistic work process. In making an article, 

an all-in-one device can be utilized, for example, in the following tasks: 

as a phone (making arrangements), as a recorder (making audio or 

video recordings of the interview), as a camera (stills or video for the 

article), as a computer (writing and storing the text with the help of an 

external Bluetooth keyboard), as an internet-tool (for gathering information) 

and as a mailing tool (sending the material to the editor or 

straight to the web/blog). 

Based on this, we define mobile journalism to be journalism characterized 

by the usage of handheld mobile multimedia devices in mobile 

context to retrieve, gather, capture, produce, and/or edit as well as to 

wirelessly send and/or publish journalistic material, like text, photos, 

audio, video or their combinations. Ideally all the tasks would be performed 

with a single device. 

Adoption of this type of device in the media organizations has just 

begun. It was only in spring 2005 when the first professional-level camera 

phones with computer capabilities were introduced to the market. 

Since then the picture quality of these devices has increased considerably 

and it is currently good enough for use in newspapers - not to mention 

publishing on the Internet. Better lenses and digital sensors and, 

most recently, the effective Xenon-flashes, which can now be found in 

the flag-ship-models of camera phones, are features that are at an increasing 

speed closing the gap between them and consumer-level digital 

cameras. 

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All together camera phones are at the moment the most significant 

single issue forming the future of photojournalism. They are profoundly 

changing the way and speed with which the media companies 

are getting their news photos and videos. During the year 2007 all major 

international media companies began to publish web sites, which 

focus on current issues and rely extensively on multimedia and video 

content. The changing nature of journalistic work is an important 

theme among the professionals. One of the pioneers of multimediajournalism, 

Brian Storm claims, "You are not print photographers. You 

are multi-platform visual journalists" (Bolt, 2007). 

Bolt (2007) strongly encourages young photographers to gather audio 

records in the form of interviews from subjects and their images in 

order to be used on the web, from flipbook-style sequences to combinations 

of maps, graphics, sound, and images. Professional-level camera 

phones seem to fulfil the tasks Storm is describing. While job opportunities 

in nearly every other newsroom category are shrinking, jobs for 

videographers are opening up. Many photographers are especially eager 

to master the new field. Video offers them the prospect of deliverance 

from print-centric thinking and perhaps a more prominent role to play 

in newsrooms (Layton, 2008). 

In the forthcoming years this will cause a tremendous need for educating 

journalists to use and exploit these devices fruitfully and purposefully 

in their profession. As the number of devices necessary to carry is 

decreasing, the journalistic work truly becomes mobile. New forms of 

journalism and new ways and situations in which to use these devices 

are also emerging. The most visible forms of new journalism have so 

far been seen during some major news-events and accidents. In those 

situations the recording eye of a camera phone is nowadays always 

present because of witnesses who happened to be on the spot with 

their phones. This is one example why news journalism has become 

faster, more present and even more intruding by nature. At the same 

time the audiences are brought into the process of making journalism 

tighter than ever before. 

The field of journalism and particularly the newspaper industry is currently 

living through an era of considerable changes. Newspapers are 

trying to find successful concepts to cope with the Web. No one really 

knows what the newsroom of tomorrow will look like (Stepp, 2007). 

Some see that the key to the future of newspapers is the effort to build 

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multiplatform portfolios of products around the core product, the traditional 

newspaper (Smolkin, 2006). 

In hopeful scenarios newspapers stay alive as hybrids. They use the 

Web to enrich traditional journalistic forms and retain its professionalism 

- along with a readership that is part print, part Web (Kuttner, 

2007). In those conditions tomorrow's journalists will more likely be 

identified by their function than by their medium. As newsrooms tum 

into diversified information retailers, the biggest distinction may be 

between those who develop the content and those who distribute it, via 

print, broadcast, the Internet, or other channels (Stepp, 2006). One 

example of a successful transition is made by British daily newspaper 

The Telegraph in October 2006. The paper underwent a thoroughgoing 

adaptation into the age of internet - something that is called in the 

industry the Telegraph revolution. The Telegraph was newly 

constructed around a multi-platform approach with integrated 

newsroom. Part of the move was making staff realize that they all 

worked for the digital element of the newspaper (Luft, 2008; Wilby, 

2006). 

Purpose of the Study 

The aim of our study is to provide a broader view to the design, development, 

and utilization of mobile learning systems by exploring what 

affects users' experiences with technology in the context of formal, 

situated learning in the case of learning for mobile journalist's work. 

The research questions that we aim to answer in this paper are 1) what is 

the relationship between pretious experiences, expectations, motif-'ation and user 

experience in formal situated learning context when a mobile [Ystem is utilized and 

2) what kind of implications the findings hat'e for producers of mobile software, 

hardware and smices as well as for educators? 

Following this Introduction section, we start by reviewing related work, 

and then present our study. Finally, we present our ffidings based on 

the mobile journalism case study in mobile learning context. Furthermore, 

we discuss the results and present practical implications for those 

involved in designing mobile learning tools as well as for educators 

planning to use mobile systems in formal, situated learning context. 

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Related Work 

Next, we will present recent studies and key issues concerning mobile 

learning and journalism education in university context. We will also 

discuss the characteristics of mobile journalism, which was our research 

context in the study presented in this chapter. 

Mobile Learning, Journalism Education and Earlier 

Journalism Related Studies in Hel 

According to Elgort (2005), adoption of mobile learning in the university 

context will be influenced by organisational, socio-cultural, and 

intra- and interpersonal factors. When examining the critical factors 

determining the successful adoption of mobile learning, Zurita, Nussbaum 

and Sharples (2003) stated that interactivity, coordination, negotiation 

and communication, organisation of material and mobility are 

such factors. 

In the field of journalism, Steel, Carmichael, Holmes, Kinse and Sanders 

(2007) have reported lessons learned on a case study of experiential 

learning in the context of journalistic studies. They found that experientiallearning 

programmes within journalism education provide for students 

valuable experiences that simulate the real world of journalism 

practice. Furthermore, according to Deuze (2005), journalism is facing 

one of the biggest challenges in journalism studies and education due to 

the 1) radical changes in the integrations of digital network technologies, 

2) need for the mastering of the multi-skilling requirements for 

different media formats, and 3) rethinking of the news producerconsumer 

relationship. Therefore, it is important that education prepares 

the students for working with various new types of tools including 

mobile tools for multi-skilling, to various types of media like the 

Internet or even mobile Internet and in contexts as close to real-life as 

possible. 

Some researchers have also studied the journalistic work from the point 

of view of human-computer interaction and computer supported cooperative 

work. In their early study, Bellotti and Rogers (1997) identify 

mobility as one of the notable characteristics of the journalist work as 

the journalists needed to travel over a wide area to gather the news. 

They propose a handheld device (e.g., a PDA) as a potential tool to 

support various tasks in the journalist work, e.g., taking notes while 

interviewing. Moreover, Fagrell (2000) and Forsberg (2001) focus their 

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research on the early phases of news making when the journalists transform 

everyday events into newsworthy stories, do background research, 

and frame news stories. Their work results in a PDA-based knowledge 

management system (Fagrell, Forsberg & Sanneblad, 2000) intending to 

provide journalists with contextual information relevant for news tasks 

in mobile situations. 

User Experience and Hel 

When learning is aimed at preparing the students for using interactive 

mobile systems in their future work, it is important to understand the 

factors that affect their user experience. Students are like any users of 

systems - the ways that users use, perceive, and experience using a system 

affects their future expectations and attitudes towards mobile systems 

and mobile work, as well as acceptance of the systems (see, e.g., 

Davis 1989; Venkatesh & Davis, 2000; Zhang & Li, 2003). In fact, it 

could be argued that in the case of learning by doing, user experience 

has an even more important role, since learners' perceptions of mobile 

systems are formed through hands-on experience of the systems and 

will have an impact on their attitudes, expectations and, therefore, future 

use in their working life in a causal manner. 

One of the early frameworks for user experience in the field of HeI 

was presented by Forlizzi and Ford (2000). They approach userproduct 

interaction by breaking it down to three main components, 

namely, user (e.g. their prior experiences, emotions, values and feelings), 

product (e.g. form language, features and aesthetic qualities), and 

other things surrounding interaction. In the more recent deftnition by 

Hassenzahl and Tractinsky (2006), user experience is defined as a consequence 

of a user's internal state, the characteristics of the designed 

system, and the context or the environment within which the interaction 

occurs. 

The temporal aspect of user experience has been approached, for example, 

by Makela and Fulton Suri (2001). According to their deftnition, 

user experience is a result of motivated action in a certain context. Furthermore, 

they propose that the previous experiences and expectations 

of the user influence the present experience, which in tum leads to 

more experiences and modified expectations. Their model is illustrated 

in Figure 1. This model is used in this case study for exploring the factors 

affecting user experience from the point of view of mobile learn- 

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ing. It is also used in the discussion of the results of this study on temporal 

aspects of user experience. 

revious experiences 

xpectations 

Current 

experience 

Context 

Figure 1. Model of user experience 

(Makeli:i & Fulton S uri, 2001,. Kankainen, 2003). 

There are a few studies available that report user experience related 

findings in the context of mobile learning, e.g., on use of PDAs (see, 

e.g., Bradley, Haynes, & Boyle, 2005), however, we are not aware of 

studies which are aimed towards theory building on the user experience 

in the context of mobile learning. Current research on user experience 

is focusing mainly on consumer products and applications. Since mobile 

learning is extending rapidly, there is an urgent need to understand 

the phenomenon in the context of mobile learning. 

Methods 

The mobile journalism case study (Yin, 2003) was conducted as part of 

a larger research project on user experience of mobile systems and 

services. The aim of the research project was to contribute to the theory 

building of user experience and to provide practical user experience 

related implications and tools for HCI -specialists and designers as well 

as for developers of mobile systems and services. We were interested in 

studying cases in which new types of mobile systems and services are 

taken into use. The case study on mobile journalism provided multiple 

views to studying the factors affecting the user experience, for example, 

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from the point of view of learning, system's properties, and functionalities, 

as well as taking new systems with multiple components into use. 

Multiple data collection methods (Yin, 2003) were used to gain a 

broader view of the factors affecting the user experience. The data 

collection methods used are presented in chronological order of conducting 

the study. Data triangulation (Yin, 2003) utilizing multiple 

sources of data was used to validate the results. In this paper, also the 

user experience framework by Makela and Fulton Suri (2001) is used to 

explore and discuss the factors affecting the user experience. We were 

specifically interested in the relationship of previous experiences and 

expectations to present experience and on a general level how motivation 

is related to user experience. This case study offered a possibility to 

study this, since some of the participants had past experiences in using 

a mobile multimedia device in their prior studies and others did not 

have prior experiences. 

Participants 

In our study, there were nineteen participants who were graduate students 

at the university (12 female, 7 male). The median age among the 

participant was 25 years (min age=22, max age=41). Ten students of 

journalism were participants in a course called "Development project 

of journalistic publishing" and nine students were studying in the 

graduate program for visual journalism. Students of visual journalism 

participated in the project day in the role of photographers, taking also 

video clips if needed. 

All nineteen participants were familiar with mobile devices. All of them 

had experience using their own mobile phones for making phone calls 

and most of them (18) typed and received text messages daily. One of 

the students did not type text messages since the space key on her 

phone had fallen off and made it impossible for her to write messages. 

Five of the students used a multimedia feature, like listening to music 

or taking photos, on their mobile phone on a weekly basis. None of the 

students used regularly, for example, mobile Internet on their mobile 

phone. Students of visual journalism (nine) had been using mobile 

phones in their curriculum in the previous semester. Students of journalism 

(ten), however, had not used mobile phones previously in their 

journalism studies, but three of them mentioned that they had used 

mobile phones for taking stills or video clips as summer trainees when 

working for newspapers. 

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Prior to the study, the students of journalism had some knowledge of 

the plans for the project day, namely, about using a new mobile system 

with a separate keyboard for direct publishing on the web and they had 

made some plans on the what kind of articles they would be doing. 

Students of visual journalism had less or no prior knowledge of the 

system or the setup of the project day. 

Mobile Journalist Toolkit 

The Mobile Journalist Toolkit is a research prototype of a lightweight 

set of tools for mobile journalist's work. The toolkit prototype has been 

developed by Nokia Research Center in a close collaboration with professional 

journalists at Reuters. The toolkit provides a compact set of 

tools for producing news stories and publishing them directly from the 

field. 

Figure 2. Components of the Mobile Journalist Toolkit (photo: Tero Hakala). 

Figure 2 shows the components of the Mobile Journalist Toolkit. The 

toolkit consists of: 

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• Nokia N82 mobile device. The N82 is a state-of-the-art camera 

phone with a 5-megapixel camera and a Xenon-flash for capturing 

still images and video. It can also be used as a voice recorder. 

The N82 provides wireless broadband Internet connectivity 

via 3G cellular and WLAN networks. 

• Wireless Bluetooth keyboard. An almost full-size QWERTY 

keyboard for typing text. The keyboard can be folded for easier 

transport. 

• Microphone adapter. Enables an external microphone to be 

connected to the N82. Using an external microphone improves 

the sound quality when recording video or audio clips. 

• Camera tripod. Can be used to hold and stabilize the N82 

when capturing still images or video. 

• Mobile Journalist Toolkit software application running on the 

N82. Combines all key functions needed by a mobile journalist 

in a single well-integrated user interface. The application provides 

a quick access to camera and audio recorder for recording 

still images, video, and audio. It also allows the user to 

create new articles, type in text, attach images, video and audio 

clips, as well as related metadata, and enables to submit the 

completed article to the news production system. 

The Mobile Journalist Toolkit was used by the students in their project 

MappiE 24h, which is described in the next section. 

MappiE 24h Project 

The MappiE 24h project was part of a project work course for graduate 

students of journalism. The objective of the project was to learn how to 

produce a real-time web publication in the mobile environment and 

experiment with the new possibilities offered by mobile technology. 

During the project day in February 2008, the students produced a realtime 

blog of events (http://mappie.uta.fi/24/) taking place at the university 

campus for a period of 24 hours. All the stories were produced 

with the Mobile Journalist Toolkit. There was also special emphasis on 

producing and publishing stories instantly from the location of the 

event or interview or from nearby for simulating the real-life field work 

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of professionals with mobile reporting and content creation systems 

(see Figure 3) . 

Figure 3. Using the Mobile Journalist Toolkit in mobile context 

(photo: Heli Viiiitiijii). 

The role of the Mobile Journalist Toolkit system in the course was to 

provide the students with the possibility to use it in the project for a 

new type of real-time publishing in form of a blog as well as to experiment 

with it in their publishing assignments. The main target was, however, 

to make the publication in whatever way and with suitable tools to 

achieve the goals present in journalism and in their assignments, namely 

the meaningfulness of the content of the publication to the target 

group, conforming to publishing schedules and predefined length of 

the articles and the journalistic quality of the publication. 

Well in advance of the project day, a support person had set up a blog 

with the W ordPress web blog publishing system for enabling instant 

publishing on the Internet. A week before the MappiE 24h project day 

a planning day was held, where all the students were present as well as 

the course lecturers. The day included a brief introduction to the mo- 

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bile system to be used and also the direct blog type publishing setup of 

the project day, and its goals were briefed to the students. This was 

followed by an ideation session, where the students ideated in pairs 

topics for the articles to the blog publication. 

Some examples of the assignments and articles ideated by the students 

were: 

• Interview of the first customer in the student cafe including 

two photos made by a solo journalist as one entry to the blog. 

• "An hour with the cleaning lady" including interview and photos 

made in several entries to the blog by a solo journalist. 

• An interview with information specialist made by a journalist 

and a photographer together as one entry to the blog. 

After the ideation session for the articles and deciding the assignments, 

the students were given a half an hour briefing on the usage of the 

mobile phone's camera for still and video capture. This was followed by 

signing out the mobile phones, SIM cards, and Bluetooth QWERTY 

keyboards. Twelve students received the mobile device at this point, 

and seven of them received the Bluetooth -keyboard. The rest of the 

students could pick up the phones and keyboards from the lecturers 

later during the week. A one hour -long training was given to the students 

on use of the mobile journalism application, including making 

adjustments to the application settings. Students tried out the application 

and devices in the training session. They also had a possibility to 

experiment with and use the mobile phones during the week before the 

project day. 

Journalism is a field of work which is always more or less mobile by 

nature. A typical article is usually made out of the office or newsroom. 

Traditionally a journalist does not need much technology in the field to 

make an interview, and writing an article is done at the newsroom with 

a Pc. Pen and paper are still the basic tools for making notes. When 

recording devices are needed, digital voice recorders have become more 

and more common. But still the hassle-free audio-cassette recorders are 

widely used for recording. Also the education of journalists is still 

mainly based on the traditional approach, and the use of mobile multimedia 

phones is rare or non-existent in it, although the need to master 

them in professional work is increasing. 

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Compared to this, the work of a visual journalist is heavily loaded with 

high tech devices and applications. His/her work is at all times mobile 

(except when the photo-session is done in a studio). Professional pressphotographers 

have always used the best state-of-the-art cameras, 

lenses, flashes, and other enhancements. Up till the late 1990's they had 

to know how to develop the films and make prints from the negatives. 

In those days, when a photographer went abroad to shoot, e.g., in a 

major sports event, he/she had to carry a load of 30 kg's in addition to 

the camera bag. This extra load was due to developing chemicals, portable 

scanner, and telephoto devices. In the era of digital cameras, laptop 

computers, and high speed mobile networks all the equipment a photographer 

needs fits into an ordinary camera bag. The load to carry is 

nowadays dramatically lighter than just a decade ago. The question of 

the technological aspects of photographers' or visual journalists' work 

is now how to master the multiple applications and programs needed 

during the workflow. This includes the use of mobile multimedia 

phones in capturing, editing and sending the material to the newsroom 

directly from the field. 

From educational point of view the MappiE 24h project therefore 

aimed to enable the students of journalism and visual journalism to 

become familiar with and gain experience on new mobile tools and 

mobile work processes for their future working life. 

Procedure 

Three members of the research staff participated in conducting the 

study. The main sources of data were semi-structured interviews, two 

questionnaire studies, and observations. 

Semi-structured interviews were conducted before and after the usage 

of the system. In addition, questionnaire studies were also conducted 

before and after the usage of the Mobile Journalist Toolkit. The use of 

the system was observed in real-life usage situations when students 

were doing their assignments of the project day in mobile context. In 

addition, a week before the project day we observed the preparation 

day for the project and training for use of the Mobile Journalist Toolkit. 

Also the review meeting of the project day, which took place a week 

after the project day, was observed. 

Interviews were recorded and transcribed along with hand-written 

notes from observations. Also, photos and video were captured during 

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the observations. In addition, the data from the real-time blog was 

recorded and the written plans for the project day and email instructions 

given to students were gathered as background material. 

Data Collection 

Pre-usage interviews were used to familiarize us with the topic, to get 

background information, e.g., on participants' prior experiences of and 

expectations for using of mobile multimedia devices and mobile services 

in their personal, university and working life as well as in relation 

to mobile journalism. Pre-usage interviews were conducted as two 

separate group interviews, separately with journalists (three subjects) 

and with visual journalists (two subjects). 

The pre-usage questionnaire was prepared after the pre-usage interviews, 

partly based on the findings from it. The aim was to get data 

from topics covered in the pre-usage interviews from the whole set of 

participants. The selected themes on user experience were related to 

fears, attitudes, expectations and opinions on mobile journalism systems 

and on use of mobile multimedia devices in journalism. Also relevant 

background information, for example, on their mobile phone 

usage in their everyday life, was covered. A questionnaire was conducted 

on the preparation day before the users were given further information 

and training on the use of the system. All nineteen students 

answered the paper version of the questionnaire. 

Observations of the users were made on the preparation day, which 

was held a week before the project day, and during the actual project 

day as well as in the review meeting a week after the project day. The 

preparation day was observed in the classroom ("newsroom''). All nineteen 

students were present and also three lecturers, as well as two persons 

for technical support, one for the Mobile Journalist Toolkit and 

one for the blog publishing system. 

Prior to the project day, researchers had made arrangements with some 

of the students and agreed with them to observe their assignments for 

making the publication. Four assignments were observed by the researchers 

during the day and also some observations were made at the 

newsroom. Part of the assignments covered a set of shorter articles and 

they lasted for the whole day whereas some were only one-time stories. 

Different types of assignments were observed. One photographing 

journalist working solo was observed and three pairs, consisting of a 

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writing journalist and a photographer, amounting to seven participants, 

were observed during the project day. A week after the project day the 

review meeting was also observed in the classroom. 

Semi-structured interviews were conducted with eleven participants 

within three days of the project day. Six were students of journalism 

and five were students of visual journalism. Three of the interviews 

were conducted with pairs who had worked together on the project day 

and five students were interviewed alone. Among other things, the 

interview covered their prior usage of mobile systems and services, 

expectations they had had for the Mobile Journalist Toolkit, experiences 

with taking the system into use and using it, going through one 

example of their assignments, and their opinions of the system and 

what it is suitable for. 

The post-usage questionnaire was conducted as a web survey. All of the 

participants (nineteen) were sent an email with the link to the survey. A 

reminder was sent by email three days after the initial email. The answering 

time was limited to a week. Fifteen respondents participated in 

the survey. The questionnaire covered topics such as their perception 

of the Mobile Journalist Toolkit, their usage of different functionalities 

of the system, their perception on how well the project went and certain 

aspects of their experience of using the system in learning, how 

well their goals were satisfied, and relevant background information. 

The common theme in all data collection was gaining information on 

factors related to user experience. This was based on prior earlier studies 

and literature on user experience as well as by utilizing the information 

gathered during this study for the next phases of the study. 

Analysis of the Collected Data 

We used qualitative methods to analyze the collected data. The first 

phase of the analysis was done on transcribed pre- and post interview 

notes as well as observation notes by utilizing the so-called Afftnity 

Wall method from Contextual design (Beyer & Holzblatt, 1998). Figure 

4 illustrates the making of the Affinity Wall in this study. For it the 

transcribed notes were arranged by the three researchers in cooperation 

under themes as they emerged in the processing of the notes. 

The transcribed interviews and observation notes were later also analyzed 

by using the user experience framework by Makela & Fulton Suri 

(2001) as one way to categorize the ftndings in the data. Data from the 

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Understanding User Experience to SUppOrl Learningfor Mobile Journalist's Work 

pre- and post-usage questionnaires were analyzed using descriptive 

statistics, namely frequencies, which were appropriate for small sample 

Sizes. 

Figure 4. Making the Affinity Wall from inteniew and obsen·ation notes 

(photo: Heli Viiiitiijii). 

Results 

In the following, we present results from different phases of the research, 

which are related to the learning context. First we present results 

from pre-usage interviews and pre-usage questionnaire, continuing 

with the observations, and concluding with the results form post-usage 

interviews and post-usage questionnaire. 

Pre-Usage Interviews and Questionnaire 

In the group interview of the students of journalism, they expressed 

their expectations to be two-fold for the project, namely, a bit reserved 

but on the other hand they were somewhat enthusiastic about the project. 

They were interested in trying out direct publishing to the Internet 

as well as to see what the system was capable of. Concerns were ex- 

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pressed towards writing articles with the mobile system, specifically 

naming the usage of external keyboard and the small size of the display 

of mobile phones as examples for their concern. They also questioned 

that ''Is it possible to combine et'erything in one det-ice without the usability and the 

pleasantness of working to be sacrificetP." 

The students of visual journalism, who were interviewed before the 

usage of the Mobile Journalist Toolkit, had used another commercial 

off-the-shelf mobile system in their prior studies. They described their 

prior experiences as 'Jrustrating': since the mobile system they had used 

had many bugs, which, for example, made them lose their work suddenly. 

According to them, this was especially frustrating in situations 

when they were editing their video material on the mobile phone and a 

call came in simultaneously causing their editing to crash and all their 

work to be lost. They also stated that the system they had used previously 

was not appropriate for some of the assignments they had been 

given and that the quality of the generated material was not good 

enough for the intended purpose. They also expressed that they were 

not especially enthusiastic to work with mobile multimedia devices in 

the forthcoming project, since they had had so bad previous experiences. 

On the other hand, they were interested to see if the new system 

would function better than the one they had tried out previously. Their 

major concerns were related to technology, quality of generated material, 

and functioning of the mobile system. 

Results from the pre-usage questionnaire related to learning as well as 

related to selected findings from the pre-usage interviews are shown in 

Table 1. All nineteen students answered the questionnaire, namely ten 

students of journalism and nine students of visual journalism. We can 

see that the students of journalism were more enthusiastic about the 

project than students of visual journalism. Students of journalism were 

more concerned that learning to use the new system would distract 

them from concentrating on doing their work. Students of visual journalism 

clearly show frustration by the use of the mobile journalism 

system, whereas students of journalism do not express the same feeling. 

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Table 1. Results from the pre-usage questionnaire. 

I'm expecting enthusiastically to try out the new 

system. 

Strongfy ModeratelY Neither ModeratelY Strongfy Not 

disagree disagree agree nor agree agree able to 

disagree 

sqy 

J OUl:nalists 0 0 4 6 0 0 

Visual 0 4 4 1 0 0 

jou=alists 

I'm afraid, that learning to use the new system 

will distract me from my work. 


disagree Disagree agree nor agree agree able to 

disaJ'.ree 

say 

Jou=alists 1 3 1 4 1 0 

Visual 1 2 4 0 0 2 

jou=alists 

Using the new mobile system frustrates me 

professionall . 


disagree disagree agree nor agree agree able to 

disagree 

sqy 

Jou=alists 1 5 2 2 0 0 

Visual 0 1 1 4 3 0 

jou=alists 

Observations 

One of the key findings based on the observations of the preparation 

day were the problems encountered in taking the mobile system into 

use. Mobile Journalist Toolkit is a multi-part product and to be able to 

use the external Bluetooth -keyboard a special application needs to be 

installed on the mobile multimedia device. The wireless keyboard application 

had been installed on two of the mobile devices in advance, and 

the rest of the devices did not have it installed in them. This caused 

some confusion, since the participants did not at first get instructions in 

the training given on use of the keyboard how to connect it with the 

device or how to install the required application. Students assumed that 

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the keyboard would work when they had the Bluetooth (BT) connection 

on. Students also had a lot of trouble in making the BT connection, 

even in the cases where the keyboard application had been installed 

on the device. As many of the students were making the pairing 

of the mobile device and keyboard simultaneously close to each other, 

they could not identify the right keyboard on the listing of the BT devices 

nearby. Technical support personnel needed to give help to the 

students to solve the problems. It took about a half an hour to fix the 

problems and to continue experimenting with the mobile system. 

In the observations during the project day we noticed that some students 

were motivated and enthusiastic about trying out various possibilities 

of using the mobile device in their assignments. For example, 

they realized that the mobile device could be used as a voice recorder 

and that they could make written notes with the device while interviewing. 

Also, one of the students realized that the mobile phone enables a 

new type of storytelling with video. He was taking part as a visual journalist 

in making an article in the university library about the automatic 

returning machine used by the students to return books to the library. 

He tied the mobile phone onto a book to be returned to the library 

with the machine. As the book was returned with the machine, the 

mobile phone was on and making simultaneously a video of the book's 

journey through the machine (see Figure 5). 

Figure 5. A tideo made ttith a mobile phone of book's journry through an 

automatic book returning madJine at the uniu!rSity library 

(figures capturedfrom the tideo made fry Juuso Haarala). 

During the project day students also noticed that using the mobile system 

and working in public spaces writing the articles made their work 

more visible to the audience and enabled the audience to interact with 

them more easily. They also recognized that the reactions of their interviewees 

varied from admiration to disbelief and amusement when they 

used the mobile system for writing or taking photos or video clips. The 

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latter was also mentioned in the pre-usage interviews by the students of 

visual journalism. In their earlier project visual journalists had noticed 

that especially professionals, who, like actors, are used to being interviewed 

and photographed in their work, found it hard to take it seriously 

when mobile phones were used for taking photos or video. 

One of the most common problems observed during the project day in 

using the Mobile Journalist Toolkit was related to using the Bluetooth 

keyboard, namely connecting it with the mobile device and not knowing 

if it was turned on. Some mobile devices were also still missing the 

keyboard software and it was not discovered until the students were 

starting to write the article. If the keyboard software was missing, the 

students needed to return to the newsroom to solve the problem either 

by installing the software on the device or by switching their device to 

another one. 

Post-Usage Interviews 

In the interviews after the project day, the interviewed students of 

journalism expressed their experiences with the Mobile Journalist Toolkit 

as fun, interesting, useful, and suitable for the purpose, referring to 

postings to a blog. The most enthusiastic student expressed his/her 

feeling of the usage as "captivating". However, participants expressed 

that they were not as serious about the project as they would have been 

if the project had been published in some other form than a blog and 

with, in their words, "serious" tools. 

The students of visual journalism were more reserved in their comments. 

All of them were positively surprised that the mobile device 

itself had less bugs, for example, in editing video clips. Also the quality 

of the images and video were better than in the mobile devices that 

they had previously used. However, all of the interviewed visual journalists 

said that they would have preferred to choose the tools that 

would have suited the purpose of their assignment, since they were not 

in real fieldwork a in mobile context but mainly within a few hundred 

meters of the editorial office. They did not find the project especially 

motivating for them. Also one of them stated that she or he did not 

take the project seriously, but still it was an interesting trial. 

Most of the students stated that using the mobile journalism application 

was easy and the training they had received was sufficient. Especially 

the students of visual journalism were confident in use of the system 

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and satisfied with the training they received. Two of them commented 

that the system should have been ready to use, without students needing 

to do adjustments. One of the students of journalism stated that the 

training had been incoherent and too many students were present. 

Some participants stated that using a mobile system in learning context 

will be beneficial for them when applying for a job as well as in their 

future work, since this type of system will be used in the future. One 

student also stated, ironically, that students get the credit points for 

their studies, so it is useful for the students. Some of them also expressed 

that hands-on experience gives understanding on the possibilities 

and limitations of current mobile journalism systems. 

Post-Usage Questionnaire 

There were fifteen responses to the questionnaire, seven from the students 

of visual journalism and eight from the students of journalism. 

According the responses (see Table 2), the students of journalism 

found experimenting with the Mobile Journalist Toolkit useful, whereas 

visual journalists mainly neither agreed nor disagreed. Most of the students 

stated that they learned new things. Especially visual journalists 

did not find the project motivating and they also felt the project was 

frustrating. Students of journalism found the project more motivating 

than visual journalists. Visual journalists also expressed more clearly 

that the project frustrated them. 

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Table 2. Results from post-usage questionnaire of students' opinions on 

experimenting with the Mobile Journalist Toolkit. 

How would you characterize experimenting 

with the Mobile Journalist Toolkit? 

Useful 

Strongfy ModeratelY Neither agree ModeratelY Strongfy Not 

agree agree nor disagree disagree disagree able to 

sqy 

Jou=alists 3 4 1 0 0 0 

Visual 0 0 5 1 1 0 

jou=alists 

Learned new things 



sqy 

Jou=alists 4 3 0 1 0 0 

Visual 0 5 2 0 0 0 

jou=alists 

Motivating 



say 

Jou=alists 0 3 1 3 1 0 

Visual 0 0 1 3 3 0 

jou=alists 

Frustrating 



sqy 

Jou=alists 1 4 1 1 1 0 

Visual 3 3 0 1 0 0 

jou=alists 

Students were also asked for their satisfaction in the project. The results 

are presented in Table 3. Both student groups were satisfied in trying 

out new ways of working as well as trying out mobile journalism systems 

- students of journalism being slightly more positive in the responses. 

The majority of students of journalism were satisfied with 

learning to use the system, whereas visual journalists neither were satisfied 

nor dissatisfied. 

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Table 3. Results from post-usage questionnaire on satisfaction in the project. 

How satisfied are you to trying out new ways of 

working in the project? 

Very Somewhat Neither Somewhat Very Not 

satis- satisfied satisfied nor dissatisfied dissatis- able to 

fied dissatisfied fied sqy 

J oUl:nalists 2 5 0 1 0 0 

Visual 0 5 2 0 0 0 

jou=alists 

How satisfied are you to trying out 

the mobile journalism systems in the pro·ect? 



fied dissatisfied fied say 

Jou=alists 2 6 0 0 0 0 

Visual 0 5 2 0 0 0 

jou=alists 

How satisfied are you to learning to use 

mobile journalism s stems? 



fied dissatisfied fied say 

Jou=alists 1 4 2 1 0 0 

Visual 1 1 5 0 0 0 

jou=alists 

In the open-ended questions of the questionnaire, one partiCipant 

stated that she/he does not like to be a ''guinea pit' for new types of 

mobile systems in the university. She/he felt that the students did not 

learn much new after a few trials of experimenting with the mobile 

systems they had used in their studies. The latter was also supported by 

the comments expressed by some of the students of visual journalism 

in the post-usage interviews. 

Discussion 

In the following we will discuss the presented results of the mobile 

journalism case study on factors affecting user experience in the case of 

formal, situated learning. We will also reflect the results against the user 

experience framework presented by Makela and Fulton Suri (2001). In 

addition, we will present implications based on our findings for educa- 

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tors and producers of mobile systems and services for mobile system 

usage in education. A discussion of the limitations of the study, generalizability 

of the results, rival explanations as well as directions and 

needs for future work will be presented. 

There were nineteen (19) participants in the study, of which ten (10) 

were students of journalism and nine (9) were students of visual journalism. 

The students of visual journalism had prior experiences in using 

a commercial off-the-shelf mobile multimedia device in their studies, 

whereas the students of journalism had no prior experiences of mobile 

devices in their earlier education. 

Before the experimentation with the Mobile Journalist Toolkit in the 

MappiE 24h project, the students of visual journalism were not as enthusiastic 

as the students of journalism to try out the new system. The 

students of journalism found experimenting with the mobile system in 

the project more useful to them than visual journalists. These results 

can be explained by the fact that this was the journalists' first experience 

of using mobile systems in their education, whereas visual journalists 

had made an extensive trial earlier in their study. Journalists also 

expressed more clearly than visual journalists that they learned new 

things in the experimentation, which can be explained by the same fact. 

In addition, mobile systems also provide new possibilities, especially for 

journalists since they can extend their work from writing the text for an 

article to making the entire story, including taking the photos and videos 

for it. 

Visual journalists showed not only less enthusiasm for system usage 

prior to the project, but also more frustration both before and after the 

usage of the system in the project. They also expressed that they were 

less motivated by the experiment than journalists. On the contrary, 

journalists did not express frustration for using the system before the 

project and system usage. However, after the project they expressed 

more frustration than before it, but not to the same extent as the visual 

journalists did. Visual journalists not only had prior frustrating experiences 

with using mobile systems in their studies, but they also already 

had gained experience and knowledge on using mobile multimedia 

devices for their work before this experiment. Visual journalists are also 

used to using high-quality devices in their studies as well as work, and 

this may cause frustration as they cannot achieve the quality with mobile 

phones that they would like to achieve. It seems that they were also 

not expecting to learn much new in this project, but, nevertheless, the 

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results also show that in fact they were somewhat satisfied both with 

trying out the Mobile Journalist Toolkit as well as trying out new ways 

of working enabled by it. The used system provided them new possibilities 

in sending the material to a real-time online publication as well 

as tyring out a new work process, either alone or in co-operation with a 

journalist. 

The framework for user experience by Makela and Fulton Suri (2001) 

states that the previous experiences and expectations of the user influence 

the present experience, leading to more experiences and modified 

expectations. The results from the pre-usage questionnaire and preusage 

interviews imply that the previous negative experiences with 

mobile multimedia devices in learning context have influence on the 

expectations for use as illustrated by the students of journalism. In our 

case study the expectations of students of journalism, who had no prior 

experiences in learning context, were more positive and even enthusiastic 

compared to the students of visual journalism. However, as discussed 

previously, there may also be other explanations for this and 

further and more extensive studies are needed to gain more knowledge 

on this. Also further studies on understanding the relationship between 

the level of expectations, prior experiences, and the actual user experience 

are needed. 

Our findings also imply that prior experiences may also have a connection 

to motivation. Prior experiences, expectations, and motivation 

seem to have a connection to user experience in the learning context. 

However, further studies are needed to show the relationships and to 

draw more profound conclusions from them. Also it needs to be taken 

into account that the personal goals in learning, more professionally 

oriented goals, new challenges, or all of these together may contribute 

to the motivation to use the mobile system. The framework proposed 

by Makela and Fulton Suri (2001) for user experience could be elaborated 

to take into account the relationship between prior experiences 

and expectations as well as motivation. Also other factors that affect 

the expectations and motivation need more in-depth studies and to be 

incorporated into the model. 

How to make the use of the system motivating in the mobile context 

when formal, situated learning is in question? Our results indicate that 

it is important for motivation that the system should be suitable for the 

tasks at hand, that the goals of the assignments should be meaningful 

and in balance with the capabilities of the system, and that using the 

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mobile systems should be set in as realistic mobile situations as possible. 

The goals and reasons for experimenting with new systems and 

work processes should also be clear for the students. In fact, when 

using new systems, the new work processes are forming and the learners 

can through their hands-on experiences be involved in developing 

and ideating them. There exist also other factors that affect the user 

experience and that are not covered in this paper. Examples of these 

are usability, personal preferences, utility, and suitability for the tasks 

and processes. 

It is also important that the mobile systems that are used in situated 

learning are reliable, usable, and technologically mature for the intended 

use. In our case the students had a real publication to be made and 

educational goals to be reached and, in this case, major problems with 

the mobile systems and applications or services is frustrating to the 

users. This has a direct effect on the user experience unless the learners 

are aware of what they are experimenting with and willing to reach out 

to explore the limits of the systems. When taking new mobile systems 

and applications into use, the systems should be ready to use. Not 

many of the learners are technologically oriented or even interested in 

tackling with settings of the systems or downloading software from the 

Internet to their PC and further to their mobile devices. 

Based on our synthesis of the findings in this case study and earlier 

related literature, we present implications of the findings for educators, 

as well as for producers of mobile systems, applications and services, 

whose solutions are aimed for formal situated learning. 

1. "Out-of-the-box" experience is important as it creates the first 

impression of the system or service. This can be ensured by 

making the mobile system, including all needed software and 

hardware, ready to be taken into use directly without needing 

extra effort from the learners. 

2. A mobile system is a tool for achieving the goals users have in 

their education. Mobile systems, applications, and services 

should be suitable for the intended use in mobile learning. System 

should support the educational goals by having good usability. 

This also decreases the possibility for frustration of the 

learners. 

3. Learners should not be testers of unstable mobile systems, 

unless they are aware of this and give their consent to trying 

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out the system or to experimenting to the extremes with it. 

Otherwise this may increase their resistance, as well as frustration, 

leading to poor user experience and having an influence 

on their future expectations about using similar systems. 

4. Provide adequate training before the use of the mobile system 

in assignments as well as technical support for the system, especially 

when new systems are taken into use and for problems 

encountered during use. The latter is especially important when 

situated learning is used in real-life context. 

5. It is important for the motivation of learners to work in the 

learning situation in a real-life context with relevant and meaningful 

goals. 

6. Leave room for innovativeness of learners in the use of the 

mobile systems for their assignments. 

7. Previous experiences have an effect on expectations and motivation 

as well as on user experience of mobile systems and ser 

Vices. 

8. Every experience and interaction with a mobile system is important. 

Extreme experiences with mobile systems, either positive 

or negative, are remembered well by the learners. 

The presented implications are a synthesis of our ftndings in this study 

and aimed to be used both by educators and producers of mobile systems, 

applications, and services. This list is not comprehensive due to 

the small sample size in this study and relying on its results. Further 

elaboration of the list is needed by future studies in the fteld. 

Conclusions 

We presented a case study of mobile learning related to journalism 

education in formal, situated learning. The goal of this paper was to 

explore the factors affecting user experience when learning for mobile 

journalist's work and to present implications based on the fmdings both 

for educators and for producers of mobile systems and services. User 

experience in the context of mobile learning is an area that will be of 

growing interest due to the increasing amount of interest and solutions 

taken into use in this fteld. This paper concentrated especially on the 

temporal aspects and factors of user experience. In addition, we re- 

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ported from this study other learning related findings that have an effect 

on the user experience of the students. 

The ftndings of this study imply that prior negative experiences in using 

mobile systems in the formal, situated learning context affected the 

expectations towards new mobile systems in a similar context as well as 

motivation of the users. Results also imply that there is a connection 

between prior experiences, expectations, motivation, and user experience. 

Further studies are needed to gain a deeper understanding of the 

factors affecting user experience in mobile learning as well as understanding 

the temporal aspects of user experience when mobile systems 

are used in different types of learning contexts. Implications based on 

the findings of this case study were presented for both educators when 

planning their educational activities and producers of mobile systems 

and services, who provide solutions for mobile learning. 

In addition, the MappiE 24h project also allowed the students to practice 

mobile journalist work in a realistic environment. It helped them to 

see the new opportunities and current problems in applying mobile 

technologies to journalism. They also made observations on how the 

attitudes of other persons, e.g., interviewees, changed when they used 

the mobile tools. The limitations of the mobile tools helped the students 

to see what was essential and also created new insights on use of 

the standard tools and work practices. 

International surveys show that the journalists are very anxious about 

their futures as they struggle to learn new technology and worry about 

how long their jobs will be there. It is suggested that this pessimism 

stems from changes in the workplace. In earlier days, the reporters 

came back to the newsroom to write stories after gathering the information 

they needed. Now the feeling of connection around the newsroom 

is missing in an age when reporters can file stories without ever 

meeting their coworkers (Wilson, 2008). These kinds of challenges 

should also be borne in mind when weighing the gains of mobile journalism 

applications and devices and when trying to educate both the 

new professionals for journalism and visual journalism as well as the 

old-school journalists. 

Acknowledgments 

We would like express our thanks to Prof. Hannu Olkinuora and Dr. 

Ari Heinonen from the Department of Journalism and Mass Commu- 

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nication at University of Tampere for co-operation during the study, as 

well as to all the students, who participated in this study. Special thanks 

to Tiina Koponen for her assistance in the study, to Prof. Kaisa 

Vaaananen-Vainio-Matciia and Timo Partala for comments on the article, 

to Sami Vaskuu for his invaluable work during the project with 

Mobile Journalist Toolkit as well as to Ilari Kajaste for the WordPress 

blog setup and support. We would also like to thank Dr. Kari Laurila 

and Timo T. Koskinen from Nokia Research Center for making the 

project day and this study possible. Thanks also to Tero Hakala for his 

assistance in preparing the photograph of the Mobile Journalist Toolkit 

and to all those, who have contributed to the development of the 

Toolkit at Nokia Research Center. 

References 

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Authors 

Heli Vaataja is a researcher in the Unit of Human-Centered Technology 

(IHTE) at Tampere University of Technology, Finland. Her current research 

interests include user experience of mobile systems and services, 

mobile ecosystems and ubiquitous computing. She is currently pursuing 

her doctoral research after working eleven years as a research engineer at 

Nokia Research Center in Tampere, Finland. Her previous research has 

been related to elaborating user requirements in the development of a 

novel mobile device architecture NoT A (Network on Terminal Architecture), 

development of multiuser detection algorithms for WCDMA, analysis 

of measurement signals, as well as audio modeling and simulation. She 

received her M.Sc. in 1993 in electrical engineering from the Tampere 

University of Technology, Finland. 

Anssi Mannisto is a senior lecturer and senior researcher in the Department 

of Journalism and Mass communication at the University of 

Tamp ere. He has previously worked in the Information society Institute 

at the University of Tampere and Tampere Peace and Conflict 

Research Institute. He teaches digital photography and photojournalism 

since 2000, educating both university students and staff in various Finnish 

media companies. Besides his academic carrier he has worked 

almost twenty years as a freelance photographer. His doctoral dissertation 

in 1999 explored the Western media images ofIslam and the Muslims 

during the Cold War era. Since then he has made several case studies 

of major international media events. His recent research interests 

have focused on the use of multimedia computers in journalist's work. 

Teija Vainio is a researcher in the Unit of Human-Centered Technology 

(IHTE) at Tampere University of Technology, Finland. Her current 

research interests include mobile human computer interaction, 

three-dimensional virtual environments and user interface design issues. 

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She has been involved in a number of research projects in mobile learning 

and e-Iearning, with research interests relating to the visualizing 

complex phenomena and adaptive user interfaces in mobile learning. 

Tero Jokela is a Principal Member of Research Staff at the Media 

Laboratory of Nokia Research Center in Tampere, Finland. His primary 

research interests include user interfaces and interaction techniques as 

well as mobile multimedia applications. Jokela received his M.Sc. in 

information technology from the Tampere University of Technology. 

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Guy, R (Ed.). (2009). 


Santa Rosa, California: Informing Science Press. (pp. 211-247). 

Chapter 10 

Measuring Quality of M-Learning Information 

Systems 

Ruti Gafni 

Introduction 

Technology improvements enable the building of information systems 

which can be used "any place, any time," through mobile and wireless 

devices and networks. One of the emerging applications of mobilewireless 

information systems is mobile learning, or as commonly referred, 

m-Iearning. M-Iearning information systems allow training and 

learning by using mobile devices and wireless networks, even when the 

users change their actual position. 

Mobile-wireless information systems in general, and m-Iearning systems 

in particular, can create benefits for organizations and users; e.g., productivity 

enhancement, processes and procedures flexibility, customer 

services improvement, and information accuracy for decision makers, 

which together emphasize competitive strategy, lower operation costs, 

and improve processes. However, these benefits can be nullified by 

using sub-quality information systems. In order to use these systems 

successfully, they need to be of high quality (ferho, 2002). Quality is a 

multi-dimension concept which includes a multitude of characteristics. 

Several attempts have been made to examine the nature of information 

systems, to define quality components, and to ftnd systematic ways to 

measure them (ISO/IEC 9126-1, 2001; Kan, 2002; Pan dian, 2004). 

Many information systems fail due to poor quality. Research has been 

focused on traditional (Kan, 2002) and internet information systems 

(Calero et aI., 2004; Covella & Olsina, 2006). However, mobile-wireless 

information systems face new kinds of problems, such as narrow 

bands, lack of coverage, devices with small memory and screens that 

cannot display a large amount of data, and diversity of users and de- 

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vices. M-Ieaming systems are affected by these special problems; thus, 

they require an enhanced quality definition. 

This chapter focuses on the characteristics of mobile-wireless information 

systems which affects the quality of m-Ieaming systems and introduces 

a list of questions from which new metrics can be defined. This 

is done methodologically, using software engineering, to define and 

quantify the mobile-wireless/m-Ieaming information systems quality 

components, in order to enable the evaluation, comparison, and analysis 

of m-Ieaming information systems quality. 

M-Iearning As Mobile-Wireless Information System 

Mobile learning, is the ability to learn independently of place and time, 

wireless and ubiquitous (Alexander, 2004) using a mobile-wireless information 

system. Such a system consists of an information system 

operated by small mobile digital devices, such as cellular phones or 

personal digital assistants (PDA), connected by wireless networks. Laptop 

computers and tablet personal computers can also be used to facilitate 

mobility, but here we focus on the devices that are typically identified 

by their small screen, keyboard, and pocket-sized nature. 

There were unsuccessful attempts to develop mobile-wireless information 

systems at the beginning of the millennium, since technology, devices, 

and infrastructures were immature. This situation changed during 

2003, and analysts agree that these kinds of systems will grow and their 

market share will expand (Lee, 2003; Lau, 2006). The major reasons are 

emergence of third generation wireless networks (UMTS - Universal 

Mobile Telecommunications System, CDMA2000 1x - Code division 

multiple access and GPRS - General Packet Radio Service), their coverage 

expansion, and development of smart mobile devices. The technology 

improvements lead to the development of diverse kinds of systems, 

including m-Ieaming, which can be seen as an extension of e-Ieaming. 

M-Ieaming can be used by a variety of users and for different tasks. 

Among others, students traveling by bus or train can read course summaries, 

perform online quizzes and assessments, and send them to the 

relevant instructor; company workers can use these systems for specific 

training, using any free time, wherever they are situated; museum visitors 

can receive information for each exhibit, according to its location; 

and travelers can avoid carrying travel books when visiting old towns, 

and receiving the desired information using their mobile device. 

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Problems in m-Leaming Systems 

Measuring Quality r!I M-Learning Information Systems 

Although most benefits of mobility can be regarded as being based on 

technical quality, either of hardware, software, or the carrier network, 

mobile-wireless information systems face some unique problems originating 

from the mobile devices and from the characteristics of the network. 

Because m-Ieaming systems are part of the mobile-wireless information 

systems, they suffer from the same problems. 

The mobile devices cause some of these problems: 

• The devices have technical limitations: 

o 

o 

o 

They have small memories, so the amount of information 

stored on them cannot be large. 

They have short battery life, so the continuous period of work 

cannot be long. 

They include limited calculation and computation capabilities. 

• There is a wide variety of devices, possessing different characteristics, 

and the application must be adaptable to all of them. 

• The devices' use is uncomfortable, because of their size: 

o 

o 

o 

They include tiny screens, which restrict the amount of data 

displayed. 

The resolution is low, so pictures and video-clips are not seen 

in their optimally. 

Their small keyboards are difficult to operate. 

• Security problems can arise when lost, due to possible unauthorized 

access to sensitive data. 

These problems intensify when the m-Ieaming system is targeted for a 

wide audience, where the users are faceless and there is neither user 

training nor implementation, but they are significant also in closed organizational 

information systems (firms, schools, universities, etc.). 

The network causes other problems, including: 

• Limited bandwidth, which influences directly the display of movies 

and video-clips. This problem diminishes over the time because of 

the network generations' evolution (3G and up). 

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• Inconsistent connection stability and transfer delays, according to 

the infrastructure, which interfere with learning continuity. 

• Moreover, when users operate the system during mobility, the 

connection point to the network can change and obstacles can disturb, 

causing temporary disconnections, interruptions, or disturbances. 

• Varied standards and protocols, some with high overhead, decreasing 

the performance level, others with geographical restrictions, restricting 

system use pervasiveness. 

• Issues of security, privacy and confidentiality (Di Pietro & 

Mancini, 2003; Herzberg, 2003) arise, which include risks of eavesdropping 

and need for user identification and authentication, especially 

when conducting quizzes and exams or delivering private information. 

• High costs of operation, especially when the users are low budget 

as students. 

All these problems demand precise considerations, both in trying to 

avoid them as much as possible by specific and targeted design of the 

system and in measuring system quality, which is significantly influenced 

by all these features. This chapter deals with measuring quality of 

the system which enables learning, and not the quality of the learning 

itself 

Information Systems Quality Measuring 

In order to measure the quality of m-Iearning systems, there is a need to 

understand the significance of information systems quality measuring. 

Measuring creates a quantitative description of processes and products 

that allows behavior comprehension. This knowledge enables selection 

of tools and techniques to control and improve processes, products, 

and resources. People at dissimilar tasks, like developers, managers, 

users, and learners, have different viewpoints on quality. Information 

systems quality cannot be measured only by the absence of software 

faults; it must be broader, including characteristics to cover all aspects, 

life-cycle phases, and viewpoints. 

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Measuring Quality if M-Learning Information Systems 

Several standards and frames have been defined for information systems 

development process measuring. The most recognized are CMMI 

(Capability Maturity Model Integration) (Chrissis et ai., 2006), 

IS09000:2000 (2000) with its IS090003 (2004) guidelines for software 

and ISO/IEC 15504 (2004, 2006), formerly known as SPICE (Software 

Process Improvement and Capability Determination) which integrates 

CMMI and IS090003. 

Attractiveness 

L----.JI Testability Replaceability Satisfaction 

Functionality 

Compliance 

Usability 

Compliance 

Maintainability 

Compliance 

Portability 

Compliance 

Figure 1 - ISO / IEe 9126 quality characteristics and sub-characteristics 

Product quality measuring is complicated, since there is no consensus 

on quality meaning. Several hierarchical models for quality definition 

were proposed (McCall et ai., 1977; Boehm et ai., 1978). The most 

recent model, defined by the International Organization for Standardization 

and the International Electrotechnical Commission, is ISO /IEC 

9126 (ISO/IEC 9126-1, 2001) standard which decomposes quality into 

seven characteristics, as seen in Figure 1: Functionality, Reliability, Usability, 

Efficiency, Maintainability, Portability and Quality in Use, each 

one further divided into sub-characteristics. This standard defines, for 

each sub-characteristic, internal metrics to be measured without having 

to operate the system and external metrics to be measured while testing 

or executing the system. Gafni (2008) proposed to extend the metrics 

of the ISO/IEC 9126 standard to cope with the problems of mobilewireless 

information systems. 

Quality Aspects in m-Learning Systems 

As mentioned before, m-learning systems are part of the mobilewireless 

information systems family, and as so, these systems must be 

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measured on the basis of traditional systems metrics, e.g., ease of maintainability, 

minimum complexity, lack of faults, and mean time between 

failures (MTBF), which are the fundamental metrics for all information 

systems. Furthermore, they must be measured according to internet 

systems metrics, e.g., no broken links and ease of navigation. In addition, 

they need to be measured with special targeted mobile-wireless 

metrics (Spriestersbach & Springer, 2004; Gafni, 2008). 

This section describes the mobility and wireless influences of m 

learning systems on ISO /IEC 9126 quality characteristics followed by 

relevant questions which need to be quantified to define the system's 

quality. 

Functionality 

Functionality is "the capability of the software product to provide functions 

which meet stated and implied needs when the software is used 

under specified conditions" (ISO/IEC 9126-1, 2001). It includes five 

sub-characteristics: suitability, accuracy, interoperability, security, and 

functionality compliance. 

Suitability - the capability of the system to provide an appropriate set 

of functions for specified tasks and user objectives. Suitability means 

that the functionality of the application fits the needs of a user to fulfill 

a certain task without overwhelming the user. This is important in m 

learning systems, especially because of the problems caused by the use 

of small devices. This is the reason that the information for these systems 

must be delivered in small and concise amounts (Venkatesh & 

Ramesh, 2002; Parsons & Ryu, 2006). 

Accuracy - the capability of the system to provide the appropriate or 

agreed results or effects, namely, the application's behavior is correct. 

In location aware applications, using automatic user location can alleviate 

the input operation, improving suitability. This can be used in outdoor 

m-Iearning, for example, in museums, exhibitions and city tours, 

to minimize the need for input. However, the user location can change 

during the transaction performance, causing incorrect output, affecting 

the accuracy. It is inappropriate to receive an explanation about architecture 

of a super-modern building, which we just passed, when in 

front of a renovated old house. 

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Interoperability - the capability of the system to interact with one or 

more specified systems. The application may need to access data at 

different servers and interact with one or more specified systems. In 

order to perform this correctly and support interoperability, it must use 

standard protocols. 

Security - the capability of the system to protect information and data 

so that unauthorized persons or systems cannot read or modify them, 

whether accidentally or deliberately, and authorized persons or systems 

are not denied access to them. Security is affected in different ways, for 

example: loss or theft of the mobile device, exposure of the messages in 

the network to unauthorized access, and privacy loss because of location 

aware functions. 

Functionality compliance - the capability of the system to adhere 

to standards, conventions or regulations in laws and similar prescriptions. 

According to these sub-characteristics, m-learning systems' quality 

questions that need to be quantified are: 

• Does the application use location aware functions where applicable? 

• Is the location aware function's output updated according to the 

user's position change during the transaction operation? 

• Does the application apply user profile in order to adapt the output 

to user and device? 

• Does the application use standard protocols and interfaces? 

• Does the application include mechanisms of authentication, encryption, 

authorization and confidence? 

Reliability 

Reliability is "the capability of the software product to maintain a 

specified level of performance when used under specified conditions" 

(Iso/IEe 9126-1, 2001). It includes the maturity, fault tolerance, recoverability, 

and reliability compliance sub-characteristics. 

Maturity - the capability of the system to avoid failure as a result of 

faults in the software. 

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Fault tolerance - the capability of the system to maintain a specified 

level of performance in cases of software faults or of infringement of 

its specified interface. 

Recoverability - the capability to recover data affected in case of a 

failure. Recoverability is measured by the time and effort needed for it. 

Reliability compliance - the capability of the system to adhere to 

standards, conventions, or regulations relating to reliability. 

During mobility, network problems, hidden obstacles, and hopping 

between antennas may disturb and interrupt communication. Thus, the 

system must be fault tolerant to maintain a specified level of performance, 

and, if connection is suspended, the system needs to re-establish 

the communication and recover the data directly affected, supporting 

recoverability. To measure quality according to these issues, the following 

questions apply: 

• To what degree does the mobility cause interruptions? 

• Does the application use cache memory efficiently to avoid loss of 

data? 

• Does transaction interruption damage data? 

Usability 

Usability is "the capability of the software product to be understood, 

learned, used and attractive to the user, when used under specified 

conditions". (ISO/lEe 9126-1, 2001). It includes the following subcharacteristics: 

understandability, leamability, operability, attractiveness, 

and usability compliance. 

Understandability - describes the user's effort to recognize the logical 

concept of the system and its applicability. 

Leamability - the user's effort for learning the application; for example, 

operation control, input and output. 

Operability - the user's effort to operate the system and to control its 

operation. 

Attractiveness - the capability of the software product to be attractive 

to the user. 

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Usability compliance - the capability of the system to adhere to 

standards, conventions, style guides, or regulations relating to usability. 

Usability is one of the most important characteristics when targeting 

systems to wide audiences, such as students, that need to operate an 

intuitive system without direct training and support. Mobile users may 

not be able to concentrate on the system use, so the application should 

not be complicated, the input must be easy to insert, intuitive, and simplified 

by using location aware functions (Terrenghi et aI., 2005). 

The operability sub-characteristic is affected mainly by the mobile device 

attributes (screen size, keyboard or numeric pad, etc.), which restrict 

output and input interaction possibilities. The output capabilities 

of mobile devices are determined by their screen, which limits the 

amount of information for simultaneous display. Applications need to 

consider this limitation, for example, by distributing information across 

multiple pages or adapting the content of the application. But, on the 

other hand, the operation of leafing through multiple pages in a mobile 

device decreases the operability. The input restrictions are due to size 

constraints of mobile devices and due to keyboard capabilities. This 

must be taken into consideration by applications which need to limit 

data input to minimal required data, pre-defmed options, and automatic 

filled-in fields. 

Moreover, the noisy surroundings (when operating the system while on 

a street or public environments) may distract the user and cause input 

errors, inaccuracy, and slowness. The ability to reach the relevant data 

"any place any time" enlarges system attractiveness. 

All these reasons show that m-Iearning applications should minimize 

and simplify the required interaction between the user and the system 

and are the incentive to the following questions: 

• To what degree does screen overload diminish application understandability? 

• Are there specific menus for each possible operation? 

• Are the buttons which operate each option clear enough? 

• Is the help function for tasks easy to fmd? 

• Is the application configurable according to user and device? 

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• Do input fields have default values or choices instead of textual 

input to minimize errors? 

• Does the system use location aware functions to minimize inputs? 

• Are length and format of the outputs optimized to screen size? 

Efficiency 

Efficiency is "the capability of the software product to provide appropriate 

performance, relative to the amount of resources used, under 

stated conditions". (Iso/IEe 9126-1, 2001). It includes these subcharacteristics: 

time behavior, resource utilization, and efficiency compliance. 

Time behavior - the capability of the system to provide appropriate 

response and processing times and throughput rates when performing 

its function, under stated conditions. The time behavior describes, for 

instance, processing times and throughput rates. 

Resource utilization - the capability of the system to use appropriate 

amounts and types of resources when the software performs its 

function under stated conditions. 

Efficiency compliance - the capability of the system to adhere to 

standards or conventions relating to efficiency. 

The high costs of wireless network usage, which currently have an economic 

impact greater then wired networks, mean that applications must 

be focused and the usage time reduced, otherwise users will avoid expensive 

systems. Moreover, users are accustomed to rapid systems, so 

slowness is unacceptable, especially when users are "on the move." 

Mobile devices include small memory and low processing resources, so 

applications must be aware of these restrictions and optimize resource 

utilization. These contribute to application's suitability as well as time 

and resource based efficiency, and the questions which need to be 

measured are: 

• Is transaction execution time minimal? 

• Does the application utilize the cache memory to reduce resource 

utilization? 

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• Is the size of the application stored in the device proportional to 

the memory size? 

• Is the size of the help system stored in the device proportional to 

the memory size and the application size? 

Maintainability 

Maintainability is "the capability of the software product to be modified. 

Modifications may include corrections, improvements or adaptation 

of the software to changes in environment, and in requirements 

and functional specifications" (ISO/IEC 9126-1,2001). 

The term of system maintenance was broadened to "system evolution" 

when changes to the systems functionality or properties are performed 

(Chapin et al., 2001; Lehman & Ramil ,2003). Software evolution is the 

result of the ongoing need to support the stakeholders' mission in the 

face of changing assumptions, problems, requirements, architectures, 

and technologies. Evolution is a broad concept that expands upon the 

traditional notion of software maintenance. 

Maintainability, as in ISO/IEC 9126-1, includes the following subcharacteristics: 

Analyzability - the effort needed for the diagnosis of deficiencies or 

failures and for the identification of parts to be modified. 

Changeability - the effort needed for modification, fault removal or 

for environmental change. 

Stability - the tolerance of the application towards unexpected effects 

of modifications. 

Testability - the effort for validating modification. 

Maintainability compliance - the capability of the system to adhere 

to standards or conventions relating to maintainability. 

This set of sub-characteristics reflects mainly the technical stakeholders' 

viewpoint, such as the developers and maintenance people (Hordijk & 

Wieringa, 2005). Thus, the mobile-wireless features do not have significant 

influence, additional to those of the traditional systems features, 

upon them, and learners are not affected by the level of quality of the 

maintainability characteristic. If the application to be used for m- 

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learning is the same used for e-Ieaming, the architecture must be adaptive 

and rely on reusability of components (Goh & Kinshuk, 2006), so 

the level of maintenance quality will not lessen. 

Portability 

Portability is "the capability of the software product to be transferred 

from one environment to another" (ISO/lEe 9126-1, 2001). It includes 

the adaptability, installability, co-existence, replaceability, and 

portability compliance sub-characteristics. 

Adaptability - the capability of the system to be adapted for different 

specified environments without additional effort. 

Installability - the effort for installing the system in a specified environment. 

Co-existence - the capability of the system to co-exist with other 

independent software in a common environment, sharing common 

resources. 

Replaceability - the capability of the system to be used in place of 

another specified software product for the same purpose in the same 

environment. 

Portability compliance - the capability of the system to adhere to 

standards or conventions relating to portability. 

Portability is very important in m-Ieaming systems which are targeted 

to wide audiences because of the large diversity of devices held by users 

and the lack of control over these devices, e.g., configuration devices 

and applications run by them. The application must adapt itself to the 

device features, both during installation and operation, and according 

to the user's preferences (Goh & Kinshuk, 2006). The application installation 

on the device must be invisible to laypersons. The application 

operation in the mobile device needs to exist harmonically, sharing 

common resources, with other applications installed in the same device, 

especially co-existing with the telephone facilities, when used in mobile 

or smart phones. According to the above, the questions which have to 

be asked are: 

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• Does the application adapt to different devices? 


• Does the application utilize middleware to adapt outputs to users 

and devices according to the user proftle? 

• Is the application easy to install in all required devices? 

• Does the application interfere with other applications/services 

installed in the same device? 

Quality in use 

Quality in use is the user's view of quality: "The capability of the software 

product to enable specifted users to achieve specifted goals with 

effectiveness, productivity, safety and satisfaction in specifted contexts 

of use" (ISO/IEC 9126-4, 2004). Since mobile applications may be 

used while driving or walking, tasks which need the user's attention, the 

application manipulation must be simple and intuitive, enforcing safety. 

The ISO /IEC 9126-4 standard includes the following subcharacteristics: 

Effectiveness - the capability of the software product to enable users 

to achieve specifted goals with accuracy and completeness in a specifted 

context of use. 

Productivity - the capability of the software product to enable users 

to expend appropriate amounts of resources in relation to the effectiveness 

achieved in a specifted context of use. 

Safety - the capability of the software product to achieve acceptable 

levels of risk of harm to people, software, equipment, or the environment 

in a specifted context of use. 

Satisfaction - the capability of the software product to satisfy users in 

a specifted context of use. 

Kim and Ong (2005) examined the success factors of m-Iearning from 

the learner's perspective, identifying three main dimensions of user 

satisfaction: system quality, content quality and service quality. The 

system quality deals with the technical level, which is covered by the 

above characteristics, especially reliability and usability. Content quality 

deals with the semantic level, meaning the information quality and output 

accuracy and reliability. Service quality includes the installation 

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assistance, product knowledge of the body supplying the service, training, 

support, and online help. 

Parsons and Ryu (2006) divided the quality aspects of m-Iearning systems 

to three major issues: technical aspects, content related aspects 

and context aspects. They proposed two new design issues that affect 

quality of m-Iearning: the user role and collaboration, extending the 

quality in use, considering the context of use. They suggested three new 

metrics to measure the proposed issues: (1) metaphor, which bridges 

from abstract and elusive vision to a concrete and complex situation, 

(2) functions to support interactivity with other members and tutors, 

regardless of location and (3) learning content, which highlights 

whether an m-Iearning system can provide content that is both optimized 

for mobile delivery and justifies delivery through the mobile 

channel. 

Some other questions which have to be asked are: 

• Does the application prevent unnecessary input or output paging? 

• Does input operation require minimum typing? 

Methodology to Define m-Learning Quality Metrics 

In the next sections the methodology to define the metrics will be explained 

and a list of relevant metrics developed will be exhibit. Then 

the experiments performed to validate the metrics will be described. 

Last, examples to three different metrics will be presented, each with 

the outcome of its validation. 

The Methodology 

The definition of new metrics to quantify the quality of m-Iearning 

systems is based on Gafni's research process, as shown in Figure 2, 

which consists of several phases: 

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Research Process 

Mobile-Wireless 

Information Systems 

I 

Protocols 

II 

Architectures 

I 

~ Specific Problems I 

Definition of quality attributes 

which are affected by 

mobile-wireless information systems 

I 

---....- 

Definition of objects to be measured 

Quality Quantification of 

Information Systems 

I 

I 

"""'"O""~ 

Reliability 

Usability 

Efficiency 

I 

I 

I Maintainability I 

Portability 

I 

I 

I 

Quality in Use 

I 

I Definition of new rnetrics I 

Experiments and metrics validation 

I 

I 

I 

I" Electronic Mail" I I "Where is the Child" II "Cellular" 

Figure 2 - The reseann proa!ss 

II 

"PDA" 

I 

(1) Mobile-wireless information systems examination, to detect special 

quality problems and risks that outcome from the architectures and 

protocols of such systems. (2) Choice of ISO /IEC 9126 quality characteristics 

affected by mobility and wirelessness. (3) Definition of objects 

and metrics to allow objective measurement of mobile-wireless information 

systems quality. (4) Metrics theoretical and empirical validation. 

In order to define the new metrics, the architecture and protocols of 

the mobile-wireless information systems were analyzed (Asunmaa et ai., 

2002; Green, 2003; Huber, 2004; Tarasewich, 2003; Varshney & Vetter, 

2002; Vaughan-Nichols, 2004) and the objects which affect the characteristics 

and sub-characteristics of quality were detected. These architectures 

and protocols are also the basis for m-learning systems. 

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The objects identified were, among others, the device type, the device 

screen, the device memory, phone calls performed during usage of 

system, system displays (including type of fields), types of tasks, user 

profile, and user location. All the objects identified can be clustered 

into four entities: device, application, architecture, and user. 

Quality Model 

Quality 

characteristic 

Is diVidetnto 

Affects 

mo 

~ 

/ 

Mobile Information 

System 

Object 

! Has one or 

more 

Quality sub- 

Attribute 

characteristic 

"7/ 

Quantifies 

Is measured by one or 

Quantifie 

one 

or more 

Metrics I Unit 

Defined;it~ 

Has. 

vutcomesto 

Scale 

Measure 

I 

Measurement Model 

I 

Figure 3 - Definition of metrics 

As described in Figure 3, the method used to define the metrics is as 

follows. Each identified object is decomposed into measurable attributes 

(ISO/IEC 15939,2002). Each attribute is assigned a unit measure 

and a scale, according to its meaning. This is done based on Kitchenham 

et al. methodology (1995). Using the objects identified and their 

attributes with corresponding units and scales, metrics (ISO /IEC 

15939,2002) can be defined. The metrics are methods for the measuring 

process with specific formulas. 

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List of Relevant Metrics 

This methodology enables the definition of innumerable metrics. The 

relevant metrics for each system must be defined according to the requirements 

of the system, its goal, and its users. 

In Gafni's research thirty one metrics were defmed, and mapped in two 

different viewpoints: 

• As a matrix which displays the metrics according to the specific 

problems in mobile-wireless information systems. Table 1 presents 

this viewpoint mapping. 

• As a hierarchy starting from the quality characteristics, describing 

which metrics quantify the degree of quality for each characteristic 

and sub-characteristic. This is shown in Figure 4. 

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Table 1 - Metrics mapped to mobile-wireless problems 

Problem source: Network Device Mobility 

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Metrics Z 3 ~ '" .3 3 b :J ~ :J 

Response time to X X 

~_t information 

X X X 

rom server 

Response time to X 

~t information 

X X X X X X 

rom cache 

Size of applica 

tion in mobile 

X 

device 

Size of help in 

mobile device 

X 

Device mem~ry 

leanup afte 

X 

transaction 

Network 

throughput 

X X X 

Display load 

X 

Clarity of opera 

tion possibilities 

X 

Operation menu 

eXlstence 

X 

Completeness 0 

operation menu 

X 

Display self 

adjustment pos 

X X X 

sibilities 

l\iessages 

Iseness 

con X X X X 

Ease of mpu 

ntering 

X 

Ease of outpu 

use 

X X 

Parameters self X 

adjustment pos 

X X X 

sibilities 

Ease of use 

displays pe 

X X X X X X 

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Problem source: Network Device Mobility 

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Metrics tZ 3 Jl 

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putput 

lEase of use X X X X X X X 

~splays per task 

rl'asks based on X X X 

'-tser location 

Upd~te of use! X X 

ocation based 

asks 

Speed of use! 

X X 

ocation update 

ILoss of accuracy 

X 

pn user location 

asks 

Secure messages X X X X 

and information 

pn device 

~essage time on X 

au 

Use of user pro 

ile 

X X X X 

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~are 

Installations 

X 

success 

lEase of installaltion 

X 

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X X 

ltivities 

Use of standard 

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X 

Use of cache X X 

lKesume of trans 

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action after dis 

onnections 

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I Efficiency 

Time behavior 

---......: Response time to get information from server I 

IResponse time to get Information from cache I 

..JSize of application in mobile device 

"'IResource utilization ........-:: Size of help in mobile device I 

IDevlce memory cleanup after transaction 

·ILearnablllty I Network throughput 

.IUnderstandability 

I Usability IV Operability 

Attractiveness 

Display load 

--.... Clarity of operation possibilities 

loperation menu existence 

",!Completeness of operation menu 

~DiSplay self-adjustment possibilities 

IMeSSages conciseness 

,~_OfrpK~_g 

Ease of output use 

'" Parameters self-adjustment possibilities 

~ Ease of use - displays per output 

Effectiveness l7 '\ Ease of use - displays per task 

-::::.- Productivity Tasks based on user location 

fQuality in use ~ --.::::Isafety 

Satisfaction 

------- 

~ 

__ Update of user location based tasks 

Suitability Speed of user location update 

fFunctionality Accuracy Loss of accuracy on user location tasks 

I Portability 

~ 

Security ~ Secure messages and information on device 

Interoperability 10., IMessage time on air I 

Adaptability i\ ~ Iuse of user profile I 

p Installability ~ -.oJUse of middleware I 

~~t~~ 

Replaceability 

I 

--........; Co-existence Ease of installation I 

~ Analyzability ~ ICo-existence with phone activities I 

Changeability 

fMalntalnabllity ~ITest~bility Use of standard protocols I 

IStabllity 

I Reliability 

~ Fault tolerance 

Recoverability 

~Maturity 

Use of cache 

Resume of transaction after disconnections 

I 

I 

I 

I 

I 

I 

I 

I 

I 

Figure 4 - Metrics mapped to qualifY characteristics 

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The Experiments 

Each metric defined by the research was validated theoretically and 

empirically at least by one of four different experiments performed in 

diverse technologies and devices, such as cellular phones and PDA 

devices (examples of different displays can be seen in Figure 5): 

MO.,.I"" ~ .:' -c lJ 00 

Pie...., ..-hoW mlldl VIM' Ike tile 

following "'II'ICb of the ..-1.: 

Action 

I ·1 

SOipt 

r ·1 

S~IEKects 

1 ·1 

~ 4016 ctDm 

OW 

_IA 

(1) "PDA" (2) "Cellular" 

(3) "Where is the child?" (4-b) "Electronic Mail" 

Figure 5 - Examples of displays of the experiments 

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1. The "PDA" experiment was performed on a system developed 

by Dooblo, a commercial company. The system allows conducting 

surveys on a PDA infrastructure. This system contains 

five different surveys, each including several displays. This is 

similar to performing quizzes in an m-Ieaming system. 

2. The "Cellular" experiment was performed via a simulation 

developed specifically for this research. The system simulates a 

cellular phone application. This application allows technicians 

to service customers at home, per customers' complaints that 

they generated via the cellular phone. This system was implemented 

twice, a "high quality" and a "low quality" system, to 

enable comparisons. This is similar to an m-Ieaming system 

which has both input and output displays, menus to choose 

from, and there is interaction between the user and the system. 

3. The ''Where is the Child" experiment was performed using a 

service provided by a major mobile phone company, which enables 

parents to receive information, over the cellular phone 

using GPS and cellular infrastructure, about the location of 

their child. This system is analogous to an m-Ieaming system 

used inside a museum make available explanations about the 

exhibitions, or in a tourist route to get information about the 

buildings passed along, surroundings, etc. The information is 

received both textual and graphical. 

4. The "Electronic Mail" experiment was performed in two different 

environments, in order to compare them, and on a third 

environment, not wireless and not mobile, as a reference point: 

a. Electronic Mail on a PDA environment, based on Microsoft 

Outlook. 

b. Electronic Mail on a cell phone, based on a service supplied 

by a major mobile phone company, which was developed 

based on Microsoft Outlook Express. 

c. Electronic Mail on a desktop computer, based on Microsoft 

Outlook Express. 

The aim of the validation was to prove that the metrics behave in a 

consistent and logical mode; thus, it is possible to rely on them to quantify 

the quality of these systems, for example, by showing that the value 

of the metric grows when quality increases and vice versa. 

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The theoretical proof and the empirical experiments successfully validated 

the new metrics defined in the research. This paper focuses on 

the metrics development process; therefore, the validation results are 

detailed only for the above example metrics. 

The Metrics Examples 

Three of the new defined metrics are described in this section. Outcomes 

of the validation of each metric are exhibited after the relevant 

tables. 

The measure of each metric receives a value in range 0-1: the higher the 

value, the better the quality. 

The "Display load" metric 

Table 2 describes ''Display load" metric which measures the burden 

degree of the displays. Because of the screen's size, the understandability 

is lower when the display is overloaded. 

Table 2 - Definition of ''Displqy load" metric 

Metric N arne 

Quality 

sub-characteristic 

Purpose of the metric 

Method of application 

Metric type 

Attributes measured 

Display load 

Usability - Understandability 

To what degree are the displays loaded? 

The screen of the devices is small, and the understandability 

is lower when the display is overloaded. 

Check the ratio between display size (information 

displayed) and screen size. 

The ratios are categorized and given a score, in 

inverse relationship to the display size, thus smaller 

displays categories receive greater scores. 

Then a weighted average is calculated. 

Internal 

ScrS - Device screen size 

PgS - Display size 

DisNum - Number of displays in the system 

i-Display number (1..DisNum) 

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Computation 

Deftnition of categories and scores: 

Xi= 

X= 

I if 0< PgSi:::;; ~ 

ScrS 4 

X if ~


The "Display Load" metric was validated in two different experiments, 

"PDA" and "Cellular". First, it was validated by the "PDA" experiment 

(Figure 6) which contains five different surveys, each including several 

displays. Therefore this experiment was further divided into six cases, 

one for each survey as it was an independent system and one for all 

Task1D i P9S1 PgS/ScrS xl DlsNum AvglPgSI X 

Flight 1 1 105 0.167 1 10 73.6 1 

1 2 42 0.067 1 

1 3 

•• 

0.157 1 

1 4 61 0.097 1 

1 5 sa 0.140 1 

1 61 0.097 1 

• 

1 7 73 0.116 1 

1 8 82 0.130 1 

1 62 0.09S 1 

• 

1 10 63 0.1 1 

Purchase 2 11 112 0.178 1 8 137.38 0.875 

2 12 150 0.238 1 

2 13 66 0.105 1 

2 14 160 0.254 0.667 

2 15 115 0,183 1.000 

2 16 231 0,367 0.667 

2 17 67 0,106 1.000 

2 18 1.8 0,314 0.667 

M ... 3 1. 108 0,171 1.000 7 129.43 0.905 

3 20 130 0,206 1.000 

3 21 75 0,119 1.000 

3 22 83 0,132 1.000 

3 23 203 0,322 0.667 

3 24 14. 0,237 1.000 

3 25 158 0,251 0.667 

Supermarh I 4 2. 105 0,167 1.000 7 143.57 0.857 

4 27 183 0,290 0.667 

4 28 14. 0,237 1.000 

4 2. 7' 0,125 1.000 

4 30 .2 0,146 1.000 

4 31 321 0,510 0.333 

4 32 76 0,121 1.000 

PartlclpaUon S 33 102 0,162 1.000 6 130.1667 0.'" 

S 34 SO 0,079 1.000 

5 35 217 0.344 0.667 

5 36 127 0,202 1.000 

5 37 175 0,278 0.667 

5 38 110 0,175 1 

1.00 

101 - PDA 

n,.,. oa9 0.91 

n ,,, 0.90 

1.00 

r- - f- 

:; 0.80 -~f-- - f-- - f--r- - 

~ 0.60 - f-- f-- f-- - - f- 

0 

·c 0.40 - f-- f-- f-- - - f- 

4i 

E 0.20 - f-- f-- f-- - - f- 

0.00 

# rl' 

. ..," 

.~ 

~ 

Q' .¢-


together. For less loaded displays the metric value received was higher, 

i.e., the displays of the "Flight" survey which are the less loaded, got a 

metric value of 1, the highest possible. Second, the metric was validated 

using the "Cellular" experiment, once with the "High quality" system, 

and once with the "Low quality system", each was performed with 

empty and full displays (Figure 7). 

101- Cellular 

1.00 .---=0=.9=4::--_ ____ ---, 

., 0.80 

~ " 0.60 

.!:! 

~ 0.40 

E 0.20 

o Hgh Quality - errpty 

• Hgh Quality - full 

• Low Quality - errpty 

• Low Quality - full 

0.00 L--..L._..L.._ 

Figure 7 - Validation of "Display load" metri( in "Cellular" experiment 

The "Memory cleanup" metric 

Table 3 defines "Memory cleanup" metric which measures the degree 

of cleaned-up memory after completing a task. The small resources of 

memory in the devices have to be carefully handled to avoid decrease 

of performance. 

Table 3 - Difinition of "Memory deanup" metri( 

Metric Name 

Quality 


Memory cleanup 

Efficiency - Resource Utilization 

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Purpose of the metrics 


Metric type 


Computation 

Expected output 

Interpretation of 

measured value 

Metric scale type 

Measure type 

Input to measurement 

ISO/IEC 12207 

reference 

Target audience 

To what degree the memory is cleaned-up 

after completing a task? 

The devices have small memory, so any "garbage" 

left after completing a task may decrease 

the subsequent work performance. 

Check the size of free memory before starting 

the test, and afterwards. 

External 

MmETt - 

free memory size at end of task i 

ApS - Application Size 

MmS - Memory Size 

y MmETt 

X = (=1 (MmS - ApS) 

INum 

TNum - Number of Tasks in System 

where 

MmS-ApS> 0 

and TNum ~1 

O~X~l 

The higher the better 

Ratio 

Size 

User Monitoring Record 

Test Report 

System Testing 

Operational testing 

Requirer 

Developer 

Maintainer 

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The "Memory Cleanup" metric was validated with the "PDA" experiment, 

for each survey, as it was an independent system and for all together. 

In the cases where the memory was better cleaned after completing 

the task, the metric value was higher, as shown in Figure 8. 

The "Speed of user location update" metric 

Table 4 defines "Speed of user location update" metric which measures 

how fast does the application recalculate the information based on user 

I 

I A~s I MmS I 

Tnum 

150 5.75 35.49 

case LMmETi x 

all all 2983.45 100.318 0.669 

Flight 1 577.64 19.423 0.647 

Purchase 2 617.62 20.767 0.692 

Movie 3 608.00 20.444 0.681 

Supermarket 4 584.76 19.662 0.655 

Participation 5 595.43 20.021 0.667 

I 

130 - PDA 

111M n mn ill 

~ V;- *>0(:- ~ ~~ roe 

v.~


Table 4 - Difinition of "Speed of user location update" metric 

Metric Name 

Quality 


Purpose of the metric 


Metric type 


Speed of user location update 

Functionality - Suitability 

Functionality - Accuracy 

How fast does the application recalculate the 

information based on user location when the 

user moves on? 

Mobile systems which outputs are based on 

user location must be accurate and change the 

relevant information quickly according to the 

new position. 

Calculate the elapsed time between the user's 

change oflocation and the application's output 

update. 

External 

UPosChng - Time of user's position change 

SysPos Upd - Time of updated output display 

to user 

PosPNum - Number of tasks based on user's 

location checked during measure 

i-Case number (1..PosPNum) 

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Computation 

For each location change: 

X; = SysPosUpd - UPosChngi 

The time unit used must suit the restriction: 

SysPOSUpdi - UPosChngi ~ 1 

Average of all cases: 

PosPNum 

LX; 

i=1 

X'= 

PosPNum 

When 

PosPNum ~1 

In order to allow summarize of all metrics, to 

enable total quality comparison between systems, 

the metrics need to be consistent, the 

higher the better. In this case, to get consistency, 

the metric needs to be transformed. 

There are two ways to perform this transformation: 

Expected output 

Interpretation of 

measured value 

1. X= max-X' when max is an extrinsic 

max 

value determined by the requirements of the 

system or an external research. 

1 

2. X = -. This transformation can lead, in 

X' 

some cases to non-uniform distribution on the 

range of 0-1, which prevents summarizing all 

metrics. 

O~X~l 

The higher the better. If two systems get the 

same value for this metric, the standard deviation 

must be checked. The system with smaller 

standard deviation is the one with better quality. 

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Metric scale type 

Measure type 

Input to measurement 

ISO/IEC 12207 

reference 

Target audience 

Interval 

Time/Count 

Operation Report 

Test Report 

User Monitoring Record 

System Testing 

Operational Testing 

System Operation 

Requirer 

Developer 

User 

The "Speed of user location update" metric was validated using the 

''Where is the child?" experiment. This experiment was performed 

during car driving, using two mobile phones, one locating the other. 

The experiment started when the located mobile phone was in a determined 

point, the other phone asked for the location, and then the located 

phone changed it position. The time was measured using a stopper. 

The results of this experiment have a normal distribution with an 

average of 68.93 seconds, and standard deviation of 20 seconds. The 

metric result received using the X = _1_ transformation was 0.87, when 

X' 

values were transferred to minutes. 

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PosPNun x' X max X(max) 

I 30 I 68.93 1.15 0.870 110 0.373 I 

seccnds minutes minutes secoods 

seconds 

i l',.Jlnl9jl:J.IDT UPosChng SysPosUpd Xi' 

1 0 0 90 90 

2 0 0 95 95 

3 0 0 72 72 

4 0 0 85 85 

5 0 10 75 65 

6 0 10 95 85 

7 0 10 114 104 

8 0 10 93 83 

9 0 15 85 70 

10 0 15 87 72 

11 0 15 120 105 

12 0 15 110 95 

13 0 30 94 64 

14 0 30 91 61 

15 0 30 103 73 

16 0 30 102 72 

17 0 30 80 50 

18 0 30 77 47 

19 0 30 90 60 

20 0 45 95 50 

21 0 45 110 65 

22 0 45 95 50 

23 0 45 77 32 

24 0 45 105 60 

25 0 60 100 40 

25 0 60 103 43 

27 0 60 116 56 

28 0 60 149 89 

29 0 60 160 100 

30 0 60 95 35 

>. 8 

(,) 

114 - W here is the child 

10 9 

0 0 

r- 

c 6 r-- r-- 

CI) 

::::J 

C'" r-- r-- 

L. 

r-- r-- 

4 3 

~ 2 

ft- u.. 

0 

40 60 80 100 120 More 

sec 

J 

u 

Figure 9 - Validation "Speed of user Im't1tion update" metri( in 

'Where is the ~!Jild?" experiment - X' t'alues 

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Conclusion 

This chapter describes a methodology to enable quality measuring of 

m-Ieaming information systems which allow interactive learning "any 

place, any time" using mobile and wireless devices, such as cellular 

phones and personal digital assistants, and networks. 

There are several advantages of using mobile-wireless information systems 

in the place and time needed. These include, but are not limited 

to, productivity enhancement, resource allocation flexibility, competitive 

advantages, service improvements, and information accuracy. 

However, mobile-wireless information systems face new kinds of problems, 

such as narrow bands, lack of coverage, devices with small memory 

and tiny screens which cannot display large amounts of data, and 

diversity of users and devices. The mentioned benefits can be nullified 

by using information systems of insufficient quality. 

M-Ieaming information systems are a sub-field of mobile-wireless information 

systems. As such, they comprise the benefits of mobilewireless 

information systems, but, on the other hand, they face the 

same problems and challenges affecting quality characteristics. 

Many information systems fail due to poor quality. Quality of information 

systems is a multi-dimension concept which includes a multitude 

of characteristics. The special m-Ieaming information systems problems 

require a different quality definition. The quality characteristics, based 

on ISO/lEe 9126 standard, affected by m-Ieaming information systems 

were widely described and analyzed in this chapter, and a set of 

questions that need to be measured was defmed. From these questions, 

using the presented methodology, which analyzes the measurable objects 

and features of the information system which affect quality characteristics, 

accurate metrics can be defmed. These metrics are methods 

for the measuring process with specific mathematically defmed formulas. 

The metrics enable objective quality evaluation and comparison of 

mobile-wireless information systems. A list of optional metrics was 

mapped in two different viewpoints, covering the quality characteristics 

on one hand, and the system problems on the other hand. Samples of 

three metrics were exhibited. Each metric was tested and validated in 

one or more empirical experiments, based on different technologies, to 

determine the quality of these systems. 

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These metrics are useful when the quality of a mobile-wireless information 

system must be analyzed and quantified, for example, when comparing 

two proposed systems, or when a system has to be developed or 

bought. When the metrics are used to compare systems, the higher the 

metric value, the higher the system's quality. However, when only one 

system has to be evaluated, the metrics need an external acceptance 

value to compare to. These acceptance values can be defmed in advance 

according to the requirements of the system. 

The selection of the suitable metrics to be measured must correlate to 

the nature of the m-Iearning system to be bought or developed. For 

example, the metrics should be chosen according to the audience of the 

m-Iearning system. There are differences between a training m-Iearning 

system to be used by workers of a company, who can receive prior 

instructions for use, and an m-Iearning system to be used by wide audiences, 

like in museums or tourism. Another example is the environment 

in which the m-Iearning system has to be operated. Using the 

system in a noisy surrounding, as on city streets, has different needs 

than using it inside a building, in a more calm ambient. 

When the need for a new m-Iearning information system arises, the 

quality characteristics important to the specific system must be analyzed 

and defined, and according to these characteristics, the metrics to 

measure the quality of the system must be selected, and the acceptance 

values for these metrics must be defmed. 

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Author 

Dr. Ruti Gafni holds a PhD from Bar-llan University, 

Israel in the Business Administration School, 

focusing in Information Systems. She holds an M.Sc 

from Tel Aviv University and a BA (Cum Laude) in 

Economics and Computer Science from Bar-llan. 

She has more than 30 years of practical experience 

as project manager and analyst of information systems. 

She teaches in the Management and Economics 

MBA program, both at the Open University of 

Israel and at Netanya Academic College. 

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Guy, R (Ed.). (2009). 



Chapter 11 

Evaluation of Mobile Learning Contents and 

Mobile Services and Applications 

Gianna Avellis 

Introduction 

Mobile e-Iearning, and Mobile Services and Applications (M:SAs) in 

general, are relatively new, so we are only beginning to see the potential 

of mobile devices in several applications and services, including training 

and performance support. Further, there are presently very few successful 

implementations on which to base a study of best practices of 

MSAs. The first generation of mobile e-Iearning closely resembles conventional 

e-Iearning, but is presented on a smaller screen. As mobile 

devices evolve and new ways in which the functionality of mobile devices 

are identified and applied to training, mobile e-Iearning will 

probably become increasingly different from conventional e-Iearning, 

no longer a miniaturized version of it. Further, internet-connected 

phones may be applied to mentoring and used to register students on 

courses and pay their fees, as well as present training content through 

the use of audio. 

There is a need to evaluate successful services and applications in the 

educational mobile sector. MSAs to e-Iearning is a very promising area 

of development, in which it is interesting to grasp how actual Software 

Engineering (SE) methods and tools can be applied to engineer good 

time-to-market products and to evaluate them in new educational settings. 

Innovative applications in MSAs are centered on user requirements 

and draw on a range of technologies and services that will shape 

the future wireless and mobile world. The potential for market growth 

in the MSAs domain is unlimited, but there are few methods and tools 

to engineer successful MSAs to e-Iearning. Our research is relevant to 

this domain for it will provide all the necessary concepts of N on- 

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Functional Requirements (NFRs) to implement and evaluate future 

systems with open interfaces, cost-efficient and high flexibility in mobile 

services, and applications to achieve successful products in a global 

competitive environment. 

Today, the economic impact of the mobile and wireless sector is now 

greater than that of the Internet. Europe has the highest level of mobile 

phones per person compared to the US and Japan, and mobile computing 

devices are becoming increasingly sophisticated and interactive. 

There are many tracking and monitoring devices being developed that 

have a range of potential applications, from supporting mobile learning 

to remote health monitoring. Mobile learning is already an important 

market, especially for PDAs in the US, and is likely to generate significant 

demand for the next generation of "converged devices" to effectively 

access mobile learning services. The rapid spread of Wi-Fi technology, 

and the prospect of even more powerful WLAN technologies 

in the near future, will lead to rapidly falling telecommunications costs, 

eliminating the major obstacle to the uptake of mobile learning services. 

In addition to the new opportunities opening up on the internet, the 

arrival of a new generation of technologies, especially mobile technologies, 

is beginning to revolutionize the way we live, work, and play, creating 

enormous potential for improving the quality of our lives. This 

radical departure from the usual way in which people are expected to 

interact with computers has created gaps in our understanding of how 

best to fit new applications around people. Importantly, needs and 

requirements are not uniform for all users. These differences in users' 

profiles and backgrounds throw up a complex set of technology and 

user interface design issues to be resolved if inclusive and beneficial 

usage are to be assured. 

From the point of view of usability, educators and learners have raised 

the concern that the handheld elements of the mobile environment 

have very small screens, which do not facilitate easy access to text, and 

small keyboards, which impede input of, or annotation of, content and 

do not support skim reading. These are very real ergonomic concerns. 

We must beware of trying to make devices perform beyond their capacity 

to deliver what is required, but, rather, we should examine potential 

activities that could be supported and evaluate the pedagogic benefits 

of these activities, which may be distributed across several devices. The 

totality of the experience needs to be evaluated, not just the component 

parts. This will mean ensuring that mobile technologies are used ap- 

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Evaluation of Mobile Learning Contents and Mobile Services & Applications 

propriately to exploit their potential, supporting activities which might 

simply be impossible without them. This is quite a challenge for evaluation 

because we have to recognize that the integration of new tools into 

existing activities creates a dialectic - the tool introduces new possibilities 

for action and new constraints that change the way in which the 

activity is performed (Taylor et aI., 2006). 

Quality Requirements playa key role in this context. The need for quality 

in mobile e-Iearning (m-Iearning) for vocational training is widely 

recognized, due to the pervasive uses of electronic mobile devices, such 

as mobile phones, smartphones, PDAs, tablet PCs, wearable PCs, or 

laptop computers with an associated device. 

Quality Engineering is a new paradigm playing a crucial role in the 

European market of Services and Applications. The evaluation of Quality 

Requirements has been underlined as an important step to have 

time-to-market products satisfying the quality and user's needs, by the 

European Commission in the context of the FP7 Strategic Objective 

1.2 "Service and Software Architectures, Infrastructures and Engineering". 

Seventy percent of software development takes place in nonsoftware 

software companies, and NFRs are key factors to designing 

successful software systems. This is why we address quality requirements 

engineering. 

This paper presents current research on the issue of Evaluation of Mobile 

Learning Contents and Mobile Services and Applications. It also 

introduces work in progress to trace Non Functional Requirements to 

architectures (Avellis, 2008a; Avellis and Finkelstein, 2005; Finkelstein 

et aI., 2004). 

Unlike Functional Requirements (FRs) that set out services expected by 

the system user, NFRs, such as usability, modularity, security, reliability, 

performance, maintainability, portability, or operational and manufacturing 

costs, are key user's requirements that set out the constraints of 

the system and the product and process standards to be followed. As 

such, they playa major role in evaluating the quality of systems during 

their construction and maintenance. This applies more so to m-Iearning 

systems that interact with end-users. 

A system quality attribute (i.e., the NFR) is largely permitted or precluded 

by its architecture. The motivation for software architecture is 

to have a basis for understanding and standardizing systems and their 

components. Software has yet to achieve the level of reuse realized by 

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hardware disciplines. Although software is easy to reproduce, its variations 

are much more difficult to standardize, identify, and control. Although 

a universal reuse solution remains elusive, great improvements 

have been made by focusing on well-defined areas of knowledge or 

activity domains. Architectures provide a means for structuring knowledge 

of the system within a domain, including their requirements. The 

possibilities for reuse are greatest when the specifications are the least 

constrained at the architectural level. Reuse is normally considered only 

at the implementation phase. This practice limits reuse to fine-grained 

modules at best and fails to allow for broader use of assets at a subsystem 

or higher level by neglecting to plan at the early stages of development. 

In this chapter, we focus on setting down a process where argumenting 

on the quality of an MLC is considered on the basis of identified NFRs 

and have developed some case studies to evaluate the process critically. 

A follow-up research result project will develop an evaluation tool to 

help MLC users to choose educational software of high quality, suitable 

for their needs and valuable as an educational resource to integrate into 

their own courses or current curriculum based on the selection of 

NFRs. Our aim is also to research and demonstrate innovative mobile 

contents for training in the IT and education sectors and to evaluate the 

requirements, especially NFR, of e-Iearning modules for mobile applications 

and services. The wireless e-Iearning solution will focus on the 

representation of mobile learning objects that suit the mobile delivery 

media and on methodologies for adapting educational multimedia to 

mobile learning environments. 

Mobile learning systems represent a broad class of software systems 

with complex characteristics that tend to make evaluation difficult; also, 

there are no existing comprehensive frameworks for formative evaluation 

in the mobile environment. The effectiveness and pedagogical 

soundness are, for example, very important to evaluate in m-Iearning. 

The approach adopts the human-centered view focusing on the learners' 

existing tasks and their structures and impose tasks upon them that 

designers thought were 'beneficial', i.e. possibly favoring the capabilities 

of the technology rather than the users. Here, the learner is at the heart 

of the enterprise, so it is important in this context to observe and analyze 

the effect of technology on learner actions, intentions, and goals as 

they engage in learning (Sharples et aI., 2006). The aim is to incorporate 

pedagogical evaluation in the proposed framework. 

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The open issue on how to develop software production processes that 

takes users requirements, especially NFRs, into account earlier is tackled. 

This will contribute mainly to the current "state of the art" in providing 

methods and procedures to make the NFRs 'exoskeletal: i.e., 

visible to the external users of software systems. Moreover, it is widely 

recognized that early identification of system architecture can assist in 

elicitation of detailed requirements, in design and reuse. And the implications 

of different architectural choices for the subsequent development 

process are ill-understood. The objective is to introduce the explicit 

representation of architectures in the annotation scheme ofNFRs 

in order to set a link between the process view and the product view of 

the software system under evaluation to support requirement traceability. 

Requirements traceability (Finkelstein, 1991) refers to the ability to 

describe and follow the life of a requirement, in both forwards and 

backwards direction. Pre-requirements specification traceability refers 

to those aspects of a requirement's life prior to inclusion in the requirements 

specification vs. post-requirements specification traceability 

that results from inclusions of those aspects in the requirements specification. 

However, a lack of common definition of requirements traceability 

(purpose-driven vs. solution-driven, vs. information-driven, and 

vs. direction-driven) has been detected in Gotel and Finkelstein (1996) 

where the requirements traceability problem was perceived not to be 

uniform due to diverse definitions and a number of fundamental conflicts 

have been found. 

NFRs have not been yet to be incorporated in the core of specification, 

design, implementation techniques, and tools (e.g. notations such as 

design or programming languages). We attempt with the techniques 

described in this chapter, to "reconnect" NFRs to the methods and 

representations that traditionally have been developed to deal with 

functional requirements. 

Many requirements, especially NFRs, are subject to change and their 

traceability will certainly aid in understanding the impact of changing 

NFRs of MSAs on architectures. Further, MSAs development environments 

are usually populated with new technologies, tools, and paradigms, 

which raise new NFRs and architectural styles in the MSAs 

domain. We have designed traceability links with architectures by applying 

the Quality Function Deployment (QFD) concept of Quality Man- 

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agement to assure that the user requirements, especially the NFRs, are 

traced in all development stages and thus in the final system. 

The novelty of our approach is to address the NFRs in the critical domain 

of MSAs for future time-to-market applications, especially to e 

learning. The results can be extended to mobile services in different 

sectors (automotive, health care, procurement, etc.), such as the ones 

addressed by the largest European project on wearable computing, 

WEARIT@WORK (WEARIT@WORK Consortium, 2004), which 

addresses emerging sectors with well-defined set of core NFRs, and 

which present many challenges to the system developers. 

The second section introduces the evaluation methodology, which 

evolved from the one developed in the context of the European project 

ESPRIT ERMES (European Multimedia Educational Software) for the 

Multimedia Educational Software (MES), to address a broader class of 

applications, such as Mobile Learning Contents (MLC) and MSAs. 

The third section describes the scheme to represent the quality requirements 

(or NFRs) and apply it to the issue of evaluating MLC. We 

have extended the scheme to address the issue of evaluating the architectures, 

besides the reusability of both NFRs and architectures. 

The fourth section addresses the issue of pedagogical evaluation and 

how we intend to represent the evaluation of multiple stakeholders by 

applying the semantic hypertext and hypermedia methods and techniques, 

currently implemented in the Compendium system at the Open 

University, Knowledge Media Institute. 

The conclusions points out further work. 

The Evaluation Methodology 

Many national and international activities in mobile learning have been 

partially funded by the European Commission, involving the private 

and public sectors (Avellis and Fresa, 1999). In this context, the need 

for quality mobile learning contents and applications is widely recognized. 

However, users of mobile learning cannot appraise educational 

resources because they are not able to evaluate their characteristics, 

potentialities, and limits (Avellis and Capurso, 1999). 

The reason why it is not easy to carry out a critical evaluation of mobile 

educational multimedia is that these resources are relatively new compared 

to traditional print-based learning materials. Most people are still 

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not used to handling them nor aware of their educational potential. 

Mobile learning content has an additional intrinsic complexity because 

it is a type of software that runs on a computer and is also an educational 

resource. Evaluating both these aspects is very different from 

evaluating a book or any traditional educational resource because of the 

interleaving of the two aspects: software and learning resource (Avellis 

and Ulloa, 1997). The distinction between software and supporting 

learning is blurred because of the way the application runs, which affects 

its educational effectiveness, and the educational purpose, which 

underlies the design of the software. Therefore, both aspects must be 

carefully considered during the evaluation. However, it is difficult to 

develop a pre-defined set of standards against which the educational 

value of the software can be defined because it is not possible to define 

a unique and general instructional approach. Thus the mobile educational 

value of a piece of software is very difficult to define in practice. 

The evaluation methodology adopted in the ESPRIT project ERMES 

consists of identifying aspects of the object under evaluation and then 

defining quality indicators in relation to these aspects. Defining the 

object of evaluation is a key step, because it suggests the evaluation 

criteria to be used. We group the characteristics of mobile learning 

contents under the following four evaluation categories: 

• educational fiatures; 

• technical fiatures; 

• aspects relating to the ease of use (usability); 

• aspects relating to the content. 

Each one of these categories has been further divided into subcategories. 

For example, educational features can be divided into target 

users, pedagogical characteristics, instructional support materials, and 

so on. That means that, when evaluating the educational features of an 

MLC, the aspects relating to the target users, the pedagogical characteristics, 

the instructional support materials, and so on, all have to be 

taken into account. 

Mobile learning performs a specific educational task. The mobile component 

can be identified in the use of a variety of media to deliver instruction 

or support for the learning activities. It is also characterized 

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by the presence of interactive components, which should enable the 

user to control the learning environment. 

Features of Mobile Learning Contents (MLC) include (Avellis and 

Finkelstein, 2002), besides the content, the following: 

• delit'ery media used to provide information; 

• user interface - the way the educational software presents itself to the 

user; interaction devices by which the user interacts with the computer 

(making choices, answering questions, or performing activities) 

and is provided with feedback to each response; 

• instructional strategy adopted; 

• access, which refers to the navigational paths available to the user to 

reach the needed content; 

• natigation allowing the user to go from one piece of content to another; 

• presentation, which can provide guidelines for defming the visual 

communication strategies or presenting the content, navigation 

strategies, and operation to the user; 

• user operations, i.e., those operations that are visible to the users and 

the only ones the user must be aware of; 

• [Ystem operations that are not visible to the users, but are essential in 

building user operations (Avellis and Capurso 1999; UW A Consortium, 

2002). 

A Scheme using Arguments in the 

Evaluation Process 

New methods and techniques are needed to express NFRs, which include 

quality requirements (Finkelstein, 1994). This underlines, at the 

centre of the development process, the 'generation of a tdue mode! such as 

is used in classical engineering disciplines (Finkelstein and Finkelstein, 

1983). A key component of the system development process is achieving 

a model of what is t'alued in the resulting system. Using this view, 

quality characteristics are not externally imposed on a development 

process but 'constructed' within it. Implementing this concept in the 

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scheme to represent NFRs traceability contributes to the current "state 

of the art" at a high scientific and technological level. 

The scheme developed to express NFRs is based on the work done by 

Kunz and Rittel (1970), particularly in the area of design rationale 

(potts and Bruns, 1988; Lee, 1991). We also take into account the 'issue-position-arguments' 

model (Conklin and Begeman, 1988). 

In our scheme, as shown below in Figure 1, an 'issue', that is a problem 

to solve, is an 'NFR, or quality characteristics/sub-characteristics to 

evaluate'. An 'argument', that is, a supporting justification of the issue, 

is a procedure that helps to determine which design alternative to choose 

to implement in the related NFR. Finally, a 'position', that is, a solution 

to the problem, is either a 'statement' of the NFR, which gives a quality 

goal to be supported by the final design, or 'design alternatives'. A 

statement is an ascertainable property (possibly measurable) characterizingNFRs. 

process 

description 

generalises/ 

specialises 

replace/ques lion/ 

is-sugges ted-by 

generalises/ 

specialises 

de term in ed-by 

ascertains 

Figure 1 Non Functional Requirements representation scheme 

It is important to underline that the statement in Figure 1 contains 

measurable elements by which the NFR can be 'constructed' in software 

systems. It is a procedure that applies to different architectural choices. 

In this way we relate NFRs to architectures by linking statements and 

different system architectural choices. 

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We have enhanced the representation of NFR with a Quality Management 

technique, namely the Quality Function Deployment (QFD) features. 

Since the late 1960s, Mizuno and Akao (1978) have established a 

new systematic method of design-oriented approaches to ensure that 

customer needs drive the product design and production process. They 

developed a method called 'Quality Deployment and/or Quality Function 

Deployment' (QD/QFD). We have enhanced the scheme ofNFR 

representation by introducing the context of evaluation and weights to 

the link "achieve" in Figure 1, as discussed below. 

To be assured that we will achieve a particular software quality characteristic 

it is helpful to associate it with some activities within the software 

evaluation and development process. Actitiry is the evaluation 

and/ or implementation activity of the quality characteristic that provides 

the context of evaluation. A quality characteristic is obtained in a 

strong/medium / weak/ negatit'e way as a result of performing an activity. In 

a QFD style we attach some weights - strong/medium/weak/negative 

- to this link, to let the end users (teacher, trainers, students, administrators) 

assign a weighted value to the characteristic of the system under 

evaluation. 

Although a quality characteristic can be constructed independently of 

the description of the development process of a product, it is useful to 

link the product and process descriptions to the quality characteristics. 

An example of the application of the scheme above to MLC is given in 

the following paragraphs (A vellis et al., 2004). 

An NFR related to a MLC could be 'the MLC should fit the suiject/ topics 

and learning oijectit'es of!l?J course'. The activity related to this example is to 

'et'aluate the educational aim of the MLC package', which strongly achieves 

the quality characteristics' 'educational fiatures'. 'Educational features' 

quality characteristics have several sub-characteristics to be taken into 

account, such as 'instructional characteristics: which suggest by their requirement 

statement that 'appropriateness of learning oijectit'es are suitable for 

the age and competence of targ,et users' and this is measured by a procedure to 

't'f!rijj that the content and learning oijectit'es are consistent with the national curricula 

requirements '. 

Another example is the NFR 'the MLC should be ea[Y to operate'. The activity 

related to this is 'understanding the usage of a MLC', which achieves 

in medium form the quality characteristics of 'usability'. This in tum can 

be further specialized into the sub-characteristics 'ease of use: which is 

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suggested by the requirements' statement 'the wqy software operates' and 

several procedures are used to measure usability: 'What are the IT skills 

required to operate the software? Is on-screen help at'ailable? Are directions clear 

and accurate? Are directions at'ailable at all times? Is the management of assessment 

instruments easy?' 

Despite the amount of discussion, little research effort has been devoted 

to techniques to support both evaluation and traceability of requirements, 

especially quality requirements, in m-Ieaming. We enhance 

the current "state of the art" by developing a representation scheme to 

evaluate and trace the requirements based on design rationale and argumentation 

and addressing increasing awareness of information, requirements 

evolution history, explanation, justification and change 

management, at a high technological level of the ongoing modeling, 

design and implementation techniques. We will take a process-oriented 

view vs. current product-oriented views, being influenced by the work 

of decision support systems. Our approach aims to extend the model 

for representing design rationale by making explicit the evaluation goals 

presupposed in the argument of the rationale representation and providing 

the means to improve the quality of the system. 

In the long-term future of Requirements Management Tools, it is 

emerging that the selection of a suitable architecture for a system is 

critically dependent upon the NFRs. Further, in the current "state of 

the art" of Requirement Management, the requirements are not organized 

so that the impact of changing a requirement on other requirements 

or on the system design can be determined. It might be thought 

that the research efforts in Software Quality, Domain Modeling and 

Software Process Modeling have tackled the issues above. However, 

they appear to have ignored a process view as the basic viewpoint vs. a 

product-oriented evaluation of software systems. This has lead to several 

problems, respectively, in evaluating the NFRs during the process 

of software development and evolution and in evaluating the properties 

of a system built to a particular architecture. 

Avellis (2008b) provides insights into how to relate this process view to 

a product view by introducing the role played by the architecture of a 

software system and relating it to the NFRs, as shown in Figure 2. The 

following figure is the extension of the scheme above in order to represent 

the traceability links with architectures of MSA, in order to reuse 

both requirements and architectures, and trace which architectures 

support which NFR. 

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process 

description 

generalizes/ 

specialises 

replace/question/ 

is-suggested-by 

generalizes/ 

specialises 

de term ined-by 

generalizes/ 

ascertains 

product 

description 

Figure 2 - Extension of the Scheme to Architectures 

Although a quality characteristic can be constructed independently of 

the description of the development process of a product, it is useful to 

link the product and process descriptions to the quality characteristics. 

We introduce in Figure 2 the explicit representation of architecture in 

the annotation scheme of NFR given before in order to set a link between 

the process view and the product view of the software system 

under evaluation. The complete scheme for the representation of the 

links between NFRs and architectures provides the explicit representation 

of the architectural description of the software system and new 

links to architecture and statement (position) and procedure (argument), 

as follows: 

• supports (a statement is grounded on the specific choice of an architectural 

description and its upkeep. It becomes obsolete if the 

statement/position changes in the software system. An architecture 

can be chosen as the alternative which satisfies the statements in 

strong/medium/weak or negatively way, following the QFD style); 

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• applied-to (a procedure has to be implemented by the related architecture, 

that is the architecture accomplishes or neglects a given 

procedure both formal or informal, which can also be provided as 

argument during the evaluation to improve the current software 

system). 

In Avellis (2008b) we give an example of the application of the scheme 

above to a Banking Information System that has undergone a reengineering 

process to improve some NFRs, including its reusability. 

Pedagogical Evaluation 

Our aim is to perform further research in this context on how to address 

the pedagogical evaluation of MLC and MSAs in general, taking 

into account the move from the transmissive mode of teaching/learning 

toward the constructivist or socio-cognitive models, where 

the learner is at the heart of activities (Taylor, 2004; Taylor et al., 2006). 

Collaborative group work and sharing with peers (and others) can be a 

powerful way of confronting one's own conceptions (pre-conceptions), 

contributing to the perceived need to restructure one's cognitive schemas; 

learning then takes place in a social context versus learning at the 

individual level (Rogers, 2002). Thus, we underline and share this view 

where learning is perceived as being as much about communication as 

it is about content. This is why we intend we focus on argumentative 

approaches to evaluation on content and add the features of semantic 

hypermedia discourse (Shum, 2007) to address the second issue, the 

collaborative group aspect oflearning. 

Some radical pedagogical approaches, facilitated by mobile computing, 

also suggest that no content is a useful starting point for learning - a 

group of learners may decide themselves what they are going to learn 

and how they are going to learn it, bringing their own material to bear 

in whatever way they feel appropriate. This is the approach of the 

MOBILe am project (MOBILearn, 2002) to usability evaluation, and it 

justifies its success from the pedagogic perspective. Pedagogical evaluation 

demands understanding, not only whether or not a learner has 

succeeded in learning, but also understanding the reasons for success or 

failure, which depends upon deep knowledge of the appropriate relationship 

of tasks to the technology in question - an area of knowledge 

that spans both the pedagogic/educational, and the technical fields. 

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MOBILe am results are very important in this context, especially in 

managing requirements for learning-on-the-move, working with interdisciplinary 

consortia joining telecom operators, broadcasters, content 

owners, publishers, and educational managers from Europe, the US 

(MIT and Stanford), and Australia. It is a large European project of 30 

months, and 8 Million of euros, founded in the context of the Information 

Society Technology of the 5th Framework Programme. The project 

coordinator is GIUNTI Interactive Labs, Italy, with the key objective 

to improve the knowledge level of individuals by developing learning 

processes that are time-efficient as well as cost-effective. We are 

interested in integrating the results of the MOBILearn project concerning 

user requirements and evaluation, as well as the work on pedagogical 

strategies for learning in mobile environments, in our evaluation 

scheme. 

Although there are tried and tested methods for pedagogic evaluation 

of specific applications of technology for learning (Draper et al., 1997; 

Scanlon et aI., 2000), there are no existing comprehensive frameworks 

for broader formative evaluation in the mobile environment, largely 

due to its novelty. A task-centered approach to user requirements, 

rather than technological advances, is the way suggested by 

MOBILEARN (2002) for an effective evaluation strategy. Addressing 

this issue, Taylor (2004) adopted the socio-cognitive engineering 

method for system design (Sharples 2000; Sharples et aI., 2002), which 

describes a two-stage process: first, that of activity analysis, which sets 

constraints on the system design and analyses how people work and 

interact with their current tools and technologies; and, second, a stage 

of design of new technology integrated into the user's/learner's environment 

and activity structures. 

One such technique for engaging in activity analysis is the Future 

Technology Workshop (Vavoula et al., 2002). In these workshops, 

participants are encouraged to consider the range of, and benefits of, 

their existing activities before being supported in thinking about how 

those activities could be more effective when supported by new technologies 

and services. This allows participants to approach the concept 

of a new activity structure in a way that has their goals at the forefront 

of the discussion, rather than have their aims and objectives subsumed 

beneath the glamour and glitz of new technology for its own sake. In 

addition to this method, an activity theoretic view (Mwanza, 2001) 

helps the analysis of the environment in which the activities are taking 

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place, other potential collaborators in the activity, and the ways in 

which organizational requirements can impinge on those activities. 

Through this enriched view of users and their current and future activities, 

in which learning is viewed as a distributed activity, it is possible to 

better understand the range of actions and opportunities that are on 

offer to mobile learners and seek ways of extending this range to support 

what learners want to do - even if they themselves do not yet 

know what that is. This broadening of the scope of the 'learning system' 

enables a much deeper understanding of users' needs and the 

constraints which govern their behavior. 

From the evaluator's point of view, then, the task is to evaluate the 

effectiveness with which learners are able to achieve their goals and 

complete learning activities, irrespective of the specific devices that 

might have been used in doing so. Indeed, the same or similar activities 

could be instantiated in a variety of different ways depending on availability 

of technical support (e.g., access to wireless LAN) and user preferences. 

In so doing, we will necessarily be evaluating the validity of the 

tasks themselves as vehicles for learning. 

The evaluation framework for the MOBIlearn project is driven both 

top-down and bottom-up. The theoretical perspectives of Activity 

Theory and constructivism, here represented by the socio-cognitive 

method, allow us to analyze learners in their appropriate contexts and 

to understand the nature of their learning tasks and how they go about 

them. The Future Technology Workshops provide much useful data on 

the views of potential mobile learners and what they see as crucial elements 

in their learning activities. At the same time, usability studies are, 

of course, essential. As the MOBIlearn system is being developed, 

standard usability testing is being performed on component software 

and devices in parallel with higher-level evaluations of pedagogic benefit. 

The next step is to embed that system in an environment which can be 

used for the learning purposes envisaged. At that point, it is possible to 

address the higher-level evaluation involving socio-pedagogic perspectives 

and pedagogic validity. That is, it is possible to address what can 

best be described as deep human -computer interface (HCI), where the 

people are at the heart of the enterprise, and understanding them as 

they use mobile and handheld learning devices is the key objective. This 

involves much more than examining usability, interface design, or tool 

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use. It entails an examination of the many factors that can influence a 

person's approach to learning and that can impact upon his or her success, 

including pedagogical strategies for learning in mobile environments. 

To this end, we will investigate the hypermedia discourse approaches 

to contesting Networks of Arguments during the evaluation 

process (Shum, 2007), which is at the basis of the Compendium system, 

a dialogical medium for modeling the discourse around wicked problems, 

such as multi-perspective software development of complex, 

typically heterogeneous, composite systems. This is because this kind of 

evaluation is characterized by the existence of multiple participants/stakeholders, 

who hold multiple (often inconsistent) views on a 

problem or solution domain and who may express these views using 

different representation schemes and develop them using different 

development strategies. 

The framework developed in the context of MOBILeam project for 

pedagogical evaluation will be taken into account, and the novel approaches 

and techniques in HCI and Educational Technologies will be 

integrated with Quality Management techniques. The advantage is to 

introduce qualitative aspects in pedagogical evaluation of mobile leammg. 

Conclusions 

Further work includes applications of the scheme to the domain of 

Mobile Services Application (MSAs). We plan to review the architectures 

in MSAs systems and analyze how the documented architectural 

styles in the literature support the NFRs of MSAs domain. This will be 

a difficult task in the chosen domain as the architectures of MSAs are 

not explicitly represented. The advantage of our approach consists in 

identifying the hidden architectural styles of MSAs by comparison with 

documented architectural styles in the literature. The aim is to investigate 

whether MSA applications have similar NFRs and architectures 

and to search for evidence whether there are common challenging ones 

that characterize the chosen domain. Based on these results, we will 

develop a lightweight but effective method to address the evaluation of 

style suitability for fulfilling a given NFR, which can serve a broader 

community of MSA planners, managers, architects, and developers. 

The architectures of MSAs will be shown to exhibit characteristics of 

various architectural styles. By analyzing how these styles support the 

NFRs, we can identify those styles that offer the "best-fit" and provide 

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guidelines for the engineering of MSAs. Finally, the work will be validated 

in the chosen domain. Several case studies will be performed in 

the domain, in industry and SMEs interested to exploit the results with 

respect to its applicability in the near future time-to-market products. 

Mobility poses particular challenges and constraints on the development 

process (Haley et aI., 2004). These include a need to cope with a 

changing environment, which itself has an impact on other qualities 

such security, reliability, and availability of information. Different models 

of software development and of learning will be brought in this 

context, such as the results of the EPSRC Privacy Rights Management 

for Mobile Applications (PRiMMA) project at the Open University 

(OU) in collaboration with a multi-disciplinary team working with OU 

students and international researchers in digital privacy management, 

from IBM's TJ Watson Research Lab, Purdue University, and Carnegie 

Mellon University. This project is overwhelming important to this research 

as a case study in security management (Haley et al., 2007). 

We aim to enhance our argumentative scheme by the hypermedia discourse 

approach adopted by the Compendium project developed at the 

Open University (OU) in collaboration with various US partners. 

Compendium is a software tool providing a flexible visual interface for 

managing the connections between information and ideas. It places few 

constraints on how you organize material, though many have found 

that it provides support for structured working, for instance, following 

a methodology or modeling technique. We have a particular interest in 

visualizing the connections between people and mapping discussions 

and debates for evaluation of mobile learning by multiple stakeholders 

and what skills are needed to do so in a participatory manner that engages 

all stakeholders. Another aspect of our investigation concerns the 

application of the Compendium project results (Shum, 2007) of relating 

ideas and information at multiple levels, useful in implementing the 

scheme to relate quality requirements to architectures. Validated in both 

small and large-scale projects across diverse sectors in society, it is the 

result of over 15 years of research and development at the intersection 

of hypertext, collaborative modeling, organizational memory, computer-supported 

argumentation, and meeting facilitation. Compendium 

has been applied on more than 50 projects at NYNEX, Bell Atlantic, 

and Verizon. 

Finally, we aim to include in our scheme problem-oriented approaches 

to representation and analysis of requirements and the relationships 

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between problem and solution structures, i.e., requirements and architectures 

(Hall et al., 2002). 

Acknowledgement 

This work has been partly fmancially supported by the European 

Commission under the Human Capital and Mobility scheme, and the 

European projects ERMES (EuRopean Multimedia Educational Software) 

(Avellis and Capurso, 1999), MACS (M:aintenance Assistance 

Capabilities for Software) (Avellis, 1990), and MOBITECH (European 

SMEs Challenge m Mobile Communication Technologies) 

(M:OBITECH Consortium, 2001). The author thanks Prof. Antony 

Finkelstein (UCL, London, UK), Prof. Bashar Nuseibeh and Prof. Josie 

Taylor (OU, Milton Keynes, UK) for their support and encouragement 

to this research. 

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Author 

Gianna Avellis is Senior Researcher in ICT, 

TECNOPOLIS CSATA Science Park, Valenzano 

(Bari), Italy. She has been involved as coordinator 

and project manager in a number of European projects 

in Software Engineering, Multimedia, and Mobile 

Telecommunications. She is board member of 

Marie Curie Fellows Association (MCFA) and ITWIIN (Italian Women 

Innovators and Inventors Network), interested in women in Science 

and Technology. She is member of IADIS and WSEAS. Her current 

research interests are in e-Iearning and m-Iearning. She served the EU 

Commission as independent expert evaluator of European projects in 

Software & Services. 

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Guy, R (Ed.). (2009). 



Chapter 12 

The Future of Mobile Learning: 

The Paradigm Pioneers of Pedagogy 

Craig Wishart 

Introduction 

Of all the civil rights for which the world has struggled and 

fought for 5,000 years, the right to learn is undoubtedly the 

most fundamental ... The freedom to learn ... has been bought 

by bitter sacrifice. And whatever we may think of the curtailment 

of other civil rights, we should fight to the last ditch to 

keep open the right to learn, the right to have examined in our 

schools not only what we believe but what we do not believe; 

not only what our leaders say, but what the leaders of other 

groups and nations, and the leaders of other centuries have 

said. We must insist upon this to give our children the fairness 

of a start which will equip them with such an array of facts and 

such an attitude toward truth that they can have a real chance 

to judge what the world is, and what its greater minds have 

thought it might be. (Du Bois, 1949) 

The greatest challenge facing the future of mobile learning in the 

United States is the acceptance of this means of instruction. Despite 

overwhelming market demand for alternative methods of education 

delivery, academics and their traditional institutions of learning resist 

the communication innovations that US corporations have rapidly 

adopted over the decades. The concern underlying this resistance is 

quality instruction and assurance of learning. With institutional reputations 

on the line, this concern cannot be underestimated. Often the 

"cutting edge" of technological innovation is the "bleeding edge" for 

the consumers, who may become overwhelmed with frustration in face 

of the challenges of technology development and infrastructural sup- 

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port for these innovations. Additionally, academics must contend with 

anxiety and uncertainty, as they struggle to keep up with the accelerated 

learning curve demanded in adopting these technology changes. After 

decades of practice, their core pedagogical competency in traditional 

classroom settings is threatened by the paradigm shift technology proffers. 

Yet currently, the US is falling behind this axial change in pedagogical 

practices. Given the torrential growth of the global market place 

and its torrid impact upon the US economy, failing to address the educational 

requirements of our post-industrial age will yield devastating 

consequences. Rather than retrenching into predictable practices of 

past, we need to embrace technological innovation, enabling pioneers 

to create radically new pedagogies that will "pull" rather than "push" 

American academic institutions into the future. 

Demand for Alternative Methods of 

Education Delivery 

College education is no longer a luxury of the fortunate few. The world 

is demanding a more highly skilled workforce to effectively compete in 

the 21 st Century global marketplace. The outsourcing millions of 

United States jobs over the past decade has left few prospects for those 

without a college degree, and retaining employment necessitates continued 

training and education. Consequently, record numbers of students 

today are seeking to reap the benefits of an education and the 

promise of a better future (Association of American Colleges and Universities, 

2007). 

With college education more important than ever before, 

both to individual opportunity and to American prosperity, 

policy attention has turned to a new set of priorities: the 

expansion of access, the reduction of costs, and accountability 

for student success. (Association of American Colleges 

and Universities, 2007, p. 1) 

With more than 3.2 million students taking online courses during the 

fall term of 2005, representing an increase of more than 850,000 students 

and an unprecedented annual growth rate of 35 percent, the market 

demand for e-Iearning cannot be denied (Allen and Seaman, 2006). 

This rapid growth suggests the need for institutions of higher education 

to provide alternative methods of education delivery to contend with 

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The Future of Mobile Learning 

the changing demographic of both undergraduate and graduate students. 

Due to the alarming increase in costs of higher education, students 

often carry one and two part-time jobs, or engage in full time employment, 

while pursuing their studies. Older students seek out re-training 

to secure their futures in face of uncertain and increasingly competitive 

industries. These "non-traditional" students are far outpacing the number 

of traditional campus-housed students of decades ago, with nearly 

85 percent of the nations matriculating college students categorized as 

non-traditional aISC Development Group, 2005). 

The majority no longer follow a traditional path through college. Nearly 

60 percent of those who earn a baccalaureate degree now enroll in two 

or more institutions before they finish their studies (Bradburn et aI., 

2003). Most students work, many attend part-time, and since 40 percent 

are twenty-four or older, many are raising families as well (Hom and 

Nevill 2006). These trends will accelerate as higher education reaches 

out with new vigor to increase college access for those who have historically 

been underserved: low-income students and racial and ethnic 

minorities (Association of American Colleges and Universities, 2007). 

Because higher education is one of many priorities this new population 

of student must balance in their lives, they express the need for convenient 

schedules, a preference for working at their own pace, and the 

desire for self-directed learning as their primary reasons for seeking 

online learning (Chen et al., 2006). 

In the current environment of wireless and mobile technologies, the 

potential to reach these non-traditional students, as well as create dynamic 

learning opportunities in the classroom, is unprecedented. The 

national agendas to expand college access and make full use of these 

new educational technologies are a burgeoning reality. The present 

challenge is to create rich learning opportunities through the use of 

effective, engaging, and innovative educational practices. Recent studies 

identify that active, engaged, collaborative, and inquiry-based methods 

are a means of achieving elusive learning outcomes (Association of 

American Colleges and Universities, 2007). "Social constructivism, in 

which learners actively formulate ideas through collaborative and group 

activities and/or dialogue, is widely adopted as a model of learning in 

all parts of the post-[secondary education] sector. As a result, learning 

and discussion are now as inextricably linked as learning and informa- 

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tion retrieval once were" aISC Development Group, 2005, p. 26). The 

wireless devices and mobile technologies are tools well suited to enhance 

these practices, since they have already become indispensable to 

modem life, creating rich social networks and informal learning opportunities, 

through web browsing, chat forums, and online communities. 

Leveraging these technologies for education delivery challenges prevailing 

presumptions about how, when, and where students can learn. The 

portability of wireless mobile devices enables students to connect anytime, 

anywhere, with instant access to resources and communication, 

providing the flexibility for self-paced and self-directed learning experiences 

of active and engaged learners (Sharples, 2006; JISC Development 

Group, 2005). 

An attempt to comprehensively characterize the unique nature of mobile 

learning is difficult at best, since it means many different things 

depending upon the perspective held. Focusing upon the technology, 

some argue that mobile learning is distinct from e-Iearning, with the 

advent of wireless connectivity and the functionality of these devices, 

such as laptops, tablet PC's, mobile phones, PDA's and iPods. Rather 

than the device, others focus upon the mobility of the learner. Unlike 

distance education that tethers students to specific locations or remote 

campuses for learning, the radical implication of mobile learning is that 

the learner is not fiXed to a predetermined location. Meanwhile, other 

researchers identify the informal learning contexts as the critical factor 

of mobile learning that is revolutionizing pedagogical practices (Winter, 

2006) . Yet a common thread emerges among the divergent views, when 

mobile learning is generally conceptualized from the leamer's perspective 

as the adaptation of technology to enable learning that is flexible, 

location free, and learner centered. 

Learner Centered Education 

Developing a theory of mobile learning for the 21 st Century entails 

developing different theories about how we learn and what we define as 

learning. A learner centered theory of mobile education is not focused 

on information transmission, but as Winter (2006) suggests, it "might 

be trans formative in nature, i.e. allow learners to achieve things they 

couldn't have achieved before," embodying key characteristics that: 

• Enable knowledge building by learners in different contexts 

• Enable learners to construct understandings 

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• Mobile technology often changes the pattern of learning/work 

activity 

• The context of mobile learning is about more than time and 

space. (p. 7) 

While researchers persist in the debate on the specific definition of 

mobile learning, the JISC Development Group (2005) compiled case 

studies on mobile education that suggested three universal qualities that 

add the greatest value for learners: any time, any place learning, widening 

participation, and personalized learning. Wireless and mobile technologies 

serve to create spontaneous and immediate learning opportunities. 

Regardless of their location, students can learn when they feel 

ready from a portable device that enables communication and access to 

information and resources at the point of need. These devices take 

education to the student, enabling easy access to learning and increasing 

their participation in contemporary cultural life. Where learners were 

once isolated or dispersed, these mobile devices enable contact with 

wider learning communities comprised of learners of all ages. Finally, 

learners can take ownership over learning, adjusting it to meet their 

personal needs. Access to the variety of multimedia resources accommodates 

learners' different learning styles and preferences for assessment, 

as well as transcends common barriers to education for disabled 

learners. As personal information management systems, these devices 

enhance learners' communication, collaboration, and time management: 

skills that are crucial for success in any workplace today. 

Market Driven Education 

The future of mobile learning will serve to transform pedagogical practices 

from the traditional dissemination of information, control of 

learning processes, and evaluation of comprehension, to the creation of 

unbounded dynamic learning opportunities that will unleash the creative 

minds of life long learners who can ensure the economic prosperity 

and security of the nation in the 21st Century. 

The United States Department of Defense is America's largest single 

consumer of higher education, yet the military is dissatisfied with the 

learning outcomes of prominent online learning service providers that 

fall short on professor involvement and professional guidance for their 

soldiers. An effective response to this clarion call for providing service 

men and women with quality education is not only necessary for na- 

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tional security, but also a moral responsibility that academic institutions 

should not leave unanswered. 

The force of the future will require life-long learning. The 

speed and complexity of our missions will only increase 

with modernization, and critical thinking skills, in addition 

to technological knowledge, will be required at every level 

of command. In a multipolar world with complex missions, 

subjects like history, geography, languages, diplomacy, 

economics and many others will become key to mission 

success .... We will seek efficiencies in all of our programs, 

so I call upon each of you to use an entrepreneurial 

spirit to find new ways to accomplish our goals and to use 

the resources available as efficiently as possible. And as our 

force becomes more mobile and deploys with greater frequency, 

we must become even better at using technology, 

such as distance learning, to leverage the delivery of our 

voluntary education services. (pang, 1997, p. 20) 

Due to force reductions and budget constraints in recent years, the 

military is urging institutions of higher education to develop smarter, 

harder working, and more competent career oriented men and women 

in their ranks. Record numbers of enlistees are enrolling in courses 

resulting in a nearly 300 percent increase in tuition assistance expenditures 

over the last six years (Baker, 2007). In response to the concomitant 

scrutiny upon authorized of education service providers, Vickers 

(2007) identified six parameters to successfully market education programs 

to the Department of Defense: 

1. Content - provide measurable skill based competencies through a 

comprehensive curriculum that promotes critical thinking, problem-solving, 

and analysis 

2. Context - provide interactive learning experiences that engage 

instructors and peers in collaboration and analytical discussion. 

3. Modality - utilize the latest technologies to provide flexible, location 

free, synchronous and asynchronous instruction through interactive 

rich media that serve to create a vital learning community. 

4. Modularity - design instructional modules in "digestible chucks" 

with measurable leaning outcomes that support self-paced completion 

in face of unscheduled deployments and training requirements 

5. Scalability - provide the technological infrastructure and faculty 

support to enable personalized learning and professional support 

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6. Efficacy - demonstrate capacity to deliver seamless enrollment, 

matriculation and learning outcomes for students located anywhere 

in the world with minimal disruption to their present job. 

A 2007 report from the Head Quarters of Air Force Education indicated 

that over the last three years enrollment in distance learning 

courses nearly doubled to 44 percent, with a 20 percent decline in traditional 

classroom instruction (Vickers, 2007). The prevailing distance 

education and online instruction methods have proven ill equipped to 

contend with this global consumer. Innovation in instructional technologies 

through the adaptation of wireless and mobile devices is an 

immediate means of meeting this unprecedented demand. 

In the civilian sector of the UK, a seminal research project for innovation 

in learning strategies examined experiential learning in the workplace 

using mobile technologies. In 2003, Anglia Ruskin University 

launched the BA (Honors) Learning, Technology and Research (BA 

LTR) fully online degree program that integrated work and online 

higher education learning (Arnold, 2007). This innovative program 

sought to capitalize upon the students' work experience as a vehicle for 

reflection and learning about what they do and development of additional 

skills and competencies that serve to enhance their work life and 

benefit their employers. Utilizing various technologies, the learners 

became competent researchers exploring areas of knowledge relevant 

to their specialties. Because this action research based learning initiative 

was self-directed and inquiry-led, the learners discovered the concrete 

application and relevance of knowledge in the workplace. The learning 

outcomes were tangible rather than abstract, which motivated them to 

attain their learning goals. The students designed the content of their 

learning needs in alignment with the educational requirements of the 

program, their personal goals, and their job skills, thereby developing 

the critical thinking, problem-solving, decision-making, and learningdesign 

skills that serve their day-to-day lives. 

As we struggle to contend with a shape-shifting world, being dramatically 

transformed by scientific and technological innovations, economic 

and political upheavals, and global interdependence, students of the 

future need to develop competencies of self-directed learning, creativity, 

and adaptation to their context. The subject-specific curriculum of 

traditionally conceptualized liberal studies programs located in reified 

institutions of higher education cannot adequately address the knowledge 

needs of the 21 st Century global market. To remain relevant, 

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higher education needs to escape its hermetically sealed walls of the 

classroom, leverage the mobile learning technologies in partnership 

with employers to prepare students for 21 st Century realities. 

Resistance to Change 

Despite pervasive belief that online education is reaching students not 

served by traditional face-to-face programs, as well as general agreement 

that it is critical to the long-term strategy of their institutions, and 

recognition of the demand from potential students and acceptance by 

potential employers, Allen and Seaman (2006) report that of the responses 

from over 2,200 colleges and universities, nearly 40 percent of 

Chief Academic Officers contend that online learning is an inferior 

means of educating, and less than 28 percent of faculty accepted the 

value and legitimacy of online education. Whether citing lack of student 

discipline, difficulty of teaching online, or costs of developing courses 

as significant barriers to widespread adoption of online learning, a 

seminal work from 16th Century points to an additional source of this 

resistance to change: 

[I]t must be considered that there is nothing more difficult to 

carry out, nor more doubtful of success, nor more dangerous 

to handle, than to initiate a new system. For the initiator has 

enemies in all those who profit by the old system, and only 

lukewarm defenders in all those who would profit by the new 

system, this luke warmness arising partly from the fear of their 

adversaries who have the past in their favor; partly from the 

incredulity of mankind, who do not truly believe in anything 

new until they have had actual experience of it ... (Machiavelli, 

1532/1992) 

The history of institutional reform points to the unfortunate truth of 

Machiavelli's "Law of innovation." Despite international attention to 

changing educational systems across the world, the implementation of 

innovation is often met with retrenchment, hostility, and fear. 

The technology of e-Iearning has been exhaustively researched, successful 

innovations thoroughly documented, millions of students have enrolled, 

and billions in profits reaped by private for-profit online educational 

programs. Yet many purveyors of learning in the hallowed halls 

of academia begrudgingly plod forward into the 21 st Century's technological 

revolution. Meanwhile, the pioneers of pedagogical innovation 

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sprint into the future, calling back to their colleagues to join them in 

celebration of their discoveries and the potential of technology. Despite 

cynical resistance, these pioneers persist in documenting the benefits of 

e-Iearning and learning outcomes in hopes of change. It may be that 

finally their day has come. In the current environment, mobile technology 

is becoming embedded in everyday practice, a ubiquitous presence 

in all realms of professional and private life. In conjunction with national 

policy commitments to make college education accessible to all 

our citizens, even the most recalcitrant cannot deny that traditional 

methods are failing to meet demand of quality education and consistent 

learning outcomes and must recognize the utility technology. We are in 

the throws of axial change, in which new paradigms of pedagogical 

practice need to be embraced. 

Current research confirms that new methods of education are working. 

Chen et al. (2006) report that "distance learners are generally as engaged 

and often more engaged than their campus-based counterparts, with 

the exception of engagement in active and collaborative learning activities. 

In addition, the self-reported gains of distance learners tend to be 

greater than those reported by their campus-based counterparts" (p. 4). 

With the adoption of wireless devices and potential for enhanced collaborative 

engagement, learning communities of mobile learners are on 

the horizon. Chen and colleagues also report that distance learners were 

more academically challenged, engaged in more reflective thinking, 

gained more practical competencies, achieved greater understanding of 

self and other, and found the educational experience to be more enriching 

and satisfying. 

Studies confirm the positive outcomes of high grades, satisfaction, and 

persistence that result from this quality of engagement in both face-toface 

and online learning (Grahm et aI., 2001; Richard & Swan 2003; 

Nelson Laird et aI., 2005), yet Jones et aI. (2006) identifiy key motivating 

factors of mobile learning that inspire student engagement: 

• control (over goals) 

• ownership 

• fun 

• communication 

• learning-in-context 

• continuity between contexts 

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Because the informal activities in mobile learning allow the students to 

experience freedom in the design of their work and the control over 

their own goals and interests, the learning process creates a learner 

centered locus of control and ownership of learning, which enhances 

their intrinsic motivation to accomplish their tasks and become passionate 

about the topics of study. 

While these affective components may be the most compelling draw 

for students to engage mobile learning, with careers on the line and 

institutional reputations at stake, educators are cautious to adopt these 

instructional innovations because these positive outcomes are not consistent 

across all age groups (Association of American Colleges and 

Universities, 2007). The unstructured nature of online courses appeals 

to the older students, who have the self-discipline, maturity, and dedication 

to manage self-directed learning. Currently, a vast majority of 

online learners are "adults," aged 25 or older. Of the students surveyed 

in Chen et al.'s (2006) study, 65 percent were categorized as adults, with 

median ages of 25 for first year students and 32 for seniors. Furthermore, 

a 2006 report from the University of North Carolina General 

Administration indicated roughly 25,000 students across the 16 campuses 

were taking online courses in the Fall semester, representing a 

250 percent increase in three years. Over 10,000 of these students were 

designated distance only learners, of which more than 90 percent were 

categorized as "adults", with a median age range of 31-40 years (Board 

of Governors, 2006). If these two examples are representative of the 

biographical and academic characteristics of online learners, then the 

reports of student success rates should not be generalized, nor serve as 

an useful argument for adopting mobile technologies to promote educational 

excellence with younger students. 

Assessment of Learning 

Allen and Seaman (2006) reported that nearly two-thirds (63.6%) of the 

2,200 institutions surveyed believe that online courses require students 

to become more disciplined, suggesting that control of the process and 

assessment of learning is required to assure success in education. This 

factor was the cited as the greatest barrier to the widespread adoption 

of online learning across the nation. This perception is not surprising, 

and a frustrating reality for many educators who must contend with the 

casualties of our public education systems. Subjected to an educational 

pipeline that pushes children through a mechanistic and impersonal 

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regimen of disciplines, most of these college bound youth are conditioned 

to passive learning in controlled educational environments. 

Compounded by the federally mandated No Child Left Behind standards-based 

education reform act of 2001, pedagogical practices that 

inspire creative engagement and passion for learning were shelved as 

teachers grappled to comply with the outcome-based assessments. Because 

of the antiquated public education systems and failed reforms of 

the past decade, many college students do not feel ownership of their 

learning, rebel against the system of educational oppression, and seek 

only to achieve a grade. Higher education is a merely a means to an end 

- the certificate that will grant them their freedom to enter into a complex 

world for which they are woefully unprepared. 

Yet, perhaps the research about the positive learning outcomes of mobile 

learning point to the need to re-evaluate the measures currently 

used to assess student success in college. The standard dimensions of 

enrollment, persistence, and degree attainment that empirically measure 

student flow into and through college to a degree or certificate (Ewell 

and Wellman, 2007) do not document the deeper learning that Nelson 

Laird et al. (2005) discuss or the quality and content of learning and 

learners' positive educational experiences (Grahm et aI., 2001; Richard 

& Swan 2003; Nelson Laird et aI., 2005; Chen et al., 2006; Jones et al., 

2006). 

The National Leadership Council for Liberal Education 

and America's Promise believes that the policy commitment 

to expanded college access must be anchored in an 

equally strong commitment to educational excellence. Student 

success in college cannot be documented - as it usually 

is - only in terms of enrollment, persistence, and degree 

attainment. These widely used metrics, while important, 

miss entirely the question of whether students who 

have placed their hopes for the future in higher education 

are actually achieving the kind of learning they need for a 

complex and volatile world. (Association of American Colleges 

and Universities, 2007, p. 11) 

The Liberal Education and America's Promise (LEAP) initiative is an 

example of an attempt to focus on the learning outcomes that are key 

to economic vitality and individual opportunity in the 21 st century. 

While this initiative will continue through 2015, the formative investigation, 

representing over 1,100 colleges and universities, suggests key 

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factors for success to include "an education that intentionally fosters, 

across multiple fields of study, wide-ranging knowledge of science, 

cultures, and society; high-level intellectual and practical skills; an active 

commitment to personal and social responsibility; and the demonstrated 

ability to apply learning to complex problems and challenges" 

(Association of American Colleges and Universities, 2007). 

Bleeding Edge for Consumers 

While the marvels of wireless devices are second nature to the youth 

generation, who navigate the mountains of technological innovation 

with the proficient expertise of an Alpinist, the experience for progressively 

older generations is far more treacherous, if not absolutely defeating. 

While many effectively adapt into their lives these changes, 

some seek to merely adopt what is necessary to function in this increasingly 

convoluted world. Yet, others are resigned to sit back as the torrent 

of technological change passes them by. The culture of technology 

is widening the gap between generations. 

Modern children have a different perception of technology 

to older people. They re-appropriate it for their own uses, 

they have different expectations of it, and it is an integral 

part of their everyday world. These social, psychological, 

experiential and technical differences are often not fully 

understood, and even more rarely utilized, by existing or 

proposed systems, and yet they need to be if the systems 

are to have a more significant impact (Beale, 2006, p. 13). 

In our response to the national mandate to increase access to education, 

institutions must attempt bridge this gap as these technologies 

become embedded into mainstream instructional practices. We must 

remain cognizant that the "cutting edge" of innovation can be the 

''bleeding edge" for the consumers. Lack of familiarity with devices, 

software conflicts and unpredictable failures can change a wonderful 

learning opportunity into a nightmare of frustration for the unseasoned 

user. Infrastructural development, as well as user training and technical 

support need to be the primary concerns and top priorities for any 

successful launch of mobile learning initiatives. 

Additionally, in the current environment, when students are often reluctant 

to incur the expense of books, bearing the cost of the wireless 

devices is an undeniable barrier to mobile learning. Before chasing after 

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the latest fad in wireless innovation, the students return on investment 

and learning outcomes need to remain the primary focus in determining 

the value of change. 

Furthermore, emotional factors can affect the acceptance of any technology. 

While formative research on the integration of mobile devices 

has proven beneficial in supporting learning activities, communication, 

and enjoyment aones et al., 2006), some studies have shown that learners 

perceive it as invasion into their private lives, personal choices, and 

freedoms aISe Development Group, 2005; Beale, 2006). For many 

learners, education is responsibility that is compartmentalized: a distinctly 

separate activity from their private lives. "We need to ensure that 

we understand more about the roles of technology in supporting the 

interactions between formal and informal learning, and in the understandable 

personal needs of people to tum things off, to be out of contact, 

and so on" (Beale, 2006, p. 13). 

Learning Curve for Faculty 

These changes in technology pose a particular challenge for faculty, 

who are focused upon their disciplines of expertise and are already 

burdened by an unrelenting workload. The demands of their jobs to 

remain current in their field, research and publish, contribute to the 

community, as well as teach and mentor students, overload their schedules. 

Developing competence in the use of new pedagogical innovations 

is often perceived as an additional burden for which they have 

little time. To overcome these hindrances, they need to be convinced of 

the potential of any new practice, the nature of its use, and whether it 

has a chance to be institutionalized, before they will direct their attention 

to it. Whether "adapters," "adopters," or "resisters" of wireless 

technologies, these innovations in pedagogical practice require faculty 

to remain on the edge of an accelerated learning curve. "A further and 

more potent challenge for practitioners, however, lies in identifying 

when and how mobile technologies are best deployed, including the 

appropriate matching of devices with learners and learning outcomes in 

the effective design of learning activities" aISe Development Group, 

2005, p. 15). 

Furthermore, many are concerned with privacy and rights of ownership 

of recorded media. Beale (2006) contends that "the new technologies 

allow us to develop full digital records of our lives and experiences, and 

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those of others, and yet doing that may well impinge on both the actual 

enjoyment of those experiences in the first place, and on the rights of 

others to have their experiences without being recorded or observed by 

others. In addition, the security and privacy of our own experiences 

needs to be understood and respected, since determining rights over 

this material is complex, especially if it involves others." With fully 

documented recordings of courses, what need is there for continued 

employment of faculty? The economies of scale that recorded media 

enable, may limit the long-term demand for faculty. Additionally, some 

have expressed concern about the "marginalization of curriculum areas 

less amenable to the introduction of mobile and wireless formats" 

aISC Development Group, 2005, p. 47). In sum, some faculty fear that 

the changes new technologies entail will serve to undermine job security 

and radically alter the conditions of academic life. 

Education of the 21 st Century 

While changes in pedagogical practices are often disconcerting, "without 

a serious national effort to recalibrate college learning to the needs 

of the new global century, however, too few of these students will reap 

the full benefits of college" (Association of American Colleges and 

Universities, 2007, p. 7). This is an especially disheartening prediction, 

considering that we are already experiencing the consequences of our 

lethargy to embrace change. Among the Organization for Economic 

Cooperation Development (OECD) nations, the US currently ranks 

19th in rates of high school completion and has fallen from 1st to 7th in 

college completion for young adults. Over the past twelve years, 

OECD countries have on average increased the number of college 

graduates by 36 percent, while the US produced only a 5 percent increase 

(Ewell and Wellman 2007). More than twenty years ago, India 

invested public expenditures into revitalizing their educational institutions, 

promoting literacy and access to education in order to transition 

into a technological economy. While currently facing their own challenges 

of growth and the paralysis of their traditional institutions (Kapur 

& Mehta 2004), the state funded promotion of math, science, and 

engineering curricula over the years generated a technology workforce 

that rivals the US. The aftermath of the Dot com crash in 2001 and the 

international outsourcing of technology experts and computer programmers 

to countries like India was a tragic awakening to powerful 

influence of the technology markets and the vulnerability of the US 

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workforce to the highly skilled and educated competition in the global 

marketplace. 

Universities and colleges will continue to work in fiercely 

competitive markets, regionally, nationally and globally and 

will have to exploit innovative mobile technologies within 

their corporate strategies. Efficiency will be a major driver 

for the continued implementation of large-scale technology-supported 

learning. The agenda to widen participation 

will increase diversity amongst the student population. 

More students will enter higher education without formal 

qualifications and increasingly they will have substantial 

part time jobs in order to fund their education. The issue 

of retention will consequently be significant and technology-based 

solutions will be required to deliver learning and 

support to wherever students are, whenever they want it 

arsc Development Group, 2005, p. 46). 

Sharples (2006) suggests that the rich social networking and media 

sharing that young people generate through software and mobile technologies 

are invaluable resources for "developing transferable skills that 

employers prize, such as knowledge working, media production and 

collaborative working. Soon they will be able to carry out all these activities 

on the move, through powerful converged devices that combine 

personal media player, phone, camera and games console" (p. 22). 

While there currently exists a dynamic tension between the legitimacy 

of informal networked interaction as a form of learning and the structured 

patterns of discourse in formal classroom education that supports 

curriculum (Sharples, 2006), capitalizing upon the proliferation of mobile 

social networking activities can serve as a powerful means of sustaining 

interest and participation, peer support, and retention in school. 

Over time, as learners are unshackled from institutional settings that 

separate them from their day-to-day activities, learning will become 

embedded in daily life, promoting unbounded cross-fertilization of 

ideas in applied contexts. 

Embracing New Paradigms of Pedagogy 

Winter (2006) points to changing our perspective on mobile learning 

applications as mediating tools in the learning process as a means of 

resolving this tension between informal and formal learning and sug- 

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gests that wireless and mobile technologies "are not ends in themselves 

and should be related to other learning tools that students and teachers 

are already using, and/or tools that have arisen as a result of technological 

development" (p. 7). Focusing upon "mediated" rather than 

mobile learning reframes attention from the devices to the context of 

learning and guides what the learner is constructing. From this perspective, 

designing effective learning activities would address questions of: 

1. The learner and their personal relationships (peer groups, 

teachers, etc.) 

2. What is the leaner learning (topic, relationship to prior experience, 

etc.)? 

3. Where and when are learners learning? (p. 7) 

Winter (2006) contends that "by answering these questions, the application 

will be designed from the ground up to form the basis for a distributed 

learning network. This construct sees mobile learning as part 

of a greater whole in which learning tools, activities, contexts and people 

are distributed over time and space" (p. 7). Addressing these questions 

will generate new ideas about both the kinds of learning students 

need and the new paradigms of pedagogical practices that will enable 

students to develop the kinds of interpersonal skills and practical competencies 

required by the 21 st Century workplace (Association of 

American Colleges and Universities, 2007). Perhaps, as JISC Development 

Group (2005) suggests, "Mobile and wireless technologies could 

transform the concept of learning, by shifting the focus from knowing 

about something to knowing how to fmd things out. Skills of information 

literacy could be more vital than factual knowledge for the 21st 

century learner" (p. 47). Whatever form these practices take, the challenge 

for the 21 st century is for educational communities to continuously 

revisit and re-evaluate essential learning outcomes as the guidepost 

for innovation. 

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Author 

Dr. Craig Wishart has a PhD. in Organizational 

Behavior from Case Western Reserve University. 

His research and writing has focused upon sustainable 

community development, education research 

and reform, as well as change processes in personal 

and organizational life. Dr. Wishart has fifteen years 

experience as an organizational consultant in the 

non-profit and business sectors, including a variety of public, private, 

educational, community, and international organizations. He has a 

broad base of experience as a designer and developer of non-profit 

business and academic programs, researcher and designer of organizational 

capacity innovations, designer and facilitator of conferences and 

team building retreats, and is an author of articles and papers for academics 

and practitioners. Currently, he is the MBA Director at Fayetteville 

State University, working to enhance the content, design and delivery 

of the program. His recent research and scholarship in online 

learning guides the e-Iearning changes that signal a significant opportunity 

for growth in the MBA program. 

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Guy, R (Ed.). (2005). 


Santa Rosa, California: Infonning Science Press. (p. 291). 

Editorial Review Board 

Chaka Chaka, Walter Sisulu University (Africa) 

John Traxler, University ofWolverhampton (UK) 

Jorge Barbosa, University of Vale do Rio dos Sinos (Brazil) 

Debora Barbosa, Unilasalle University (Brazil) 

Rodrigo Hahn, UNISINOS (Brazil) 

Solon Rabelllo, University of Vale do Rio dos Sinos (Brazil) 

Lalita Kumar, IGNOU (India) 

Teija Vainio, Tampere University of Technology (Findland) 

Jeremy Dickerson, East Carolina University (USA) 

James Browning, Brunswick Community College (USA) 

Antonio Fernandez, University ofMaIaga (Spain) 

Giovanna Avellis, TECNOPOLIS CSATA (Italy) 

Amarolinda Saccol, University of Vale do Rio dos Sinos (Brazil) 

Craig Wishart, Fayetteville State University (USA) 

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Guy, R (Ed.). (2005). 


Santa Rosa, California: Informing Science Press. (p. 293-296). 

Index 

A 

activity theory, 10,263 

assessment ofiearning, 280 

Assessment Rubric, 68, 71 

audio delivery technologies, 61 

B 

behaviorism, 22 

behaviorist-type, 6 

blended learning, 81, 97 

blended learning strategy, 160, 167, 

171 

Brazil,120 

adoption ofm-Iearning, 103 

Bronco Mobile, 145, 146 

c 

Capability Maturity Model 

Integration, 215 

cellular systems, 16 

classical mobile learning, 79 

Classtalk,22, 143 

cognitivism,24 

collaborative learning,S, 7, 19,32, 

81,89,92,104,160,261,279 

ComGRefe, 120, 121, 125, 135 

CoMobile, 144 

Computer Engineering GRefe. See 

ComGRefe 

computer supported co-operative 

work,182 

ConcertStudeo, 143 

connectivism,lO 

constructivism, 25 

constructivist activity, 6 

content delivery technologies, 60 

context, 26, 275, 276 

definition, 27 

context aware applications, 27 

context aware computing, 119 

converged devices, 250, 285 

Conversational Framework, 9 

corporate m-Iearning cases, 110 

corporate training, 109 

D 

deep HCI, 263 

deictic learning, 97 

design rationale, 257, 259 

dissemination of m-Iearning, 113 

distributed learning, 96 

domain modeling, 259 

E 

economic challenges to 

dissemination, 113 

efficiency, 220 

e-Iearning tool, 159 

error-correcting codes, 16 

e-Vi va proj ect, 20 

experiential learning, 182 

F 

field testing, 145 

first generation (lG) networks, 16 

formal learning, 178, 285 

formative assessment, 23 

functionality,216 

future of mobile learning, 271 

293 

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Future Technology Workshop, 262 

G 

games based learning, 38 

games consoles, 2, 84, 87, 98 

generation of a value model, 256 

global system for mobile 

communications, 16 

H 

handheld technologies, 5, 57, 59, 81 

health and safety issues, 41 

human-computer interaction, 178, 

182 

Hybrid learning, 97 

informal and lifelong learning, 7, 21 

information systems quality 

measuring, 214 

instant messaging, 32 

iPods, 21, 34, 36, 86 

ISOIIEC 9126, 215 

I 

K 

knowledge management system, 183 

L 

learner analysis, 64 

learner centered education, 274 

learning objects (LOs), 84 

Learning Project, 121, 125 

Liberal Education and America's 

Promise, 281 

M 

maintainability, 221 

MALL (mobile assisted language 

learning), 80, 81 

management issues, 108 

MappiE 24h project, 177, 187,205 

market driven education, 275 

mashups,93 

memory cleanup metric, 236 

meta-learning, 96, 97 

metrics for quality, 224 

midlets, 164 

m-Iearning, 80, 104 

definition, 2, 104,212 

dissemination of, 113 

future of, 271 

quality metrics, 224 

m-Iearning adoption in Brazil, 103 

m-Iearning and organizations, 110 

m-Iearning information systems, 211 

m-Learning pan-European mobile 

learning research project, 20 

m-Iearning software, 112 

m-Iearning systems, 211 

problems, 213 

quality aspects, 215 

m-Iearning technology, 111, 112 

m-Iearning tool, 160 

mobile computing, 119, 124 

Mobile Devices, 16, 18,40,267 

mobile journalism, 177, 179, 182, 

184 

mobile journalism application, 197 

Mobile Journalist Toolkit, 186, 195 

mobile learning. See also m-Iearning 

evaluation, 249 

mobile learning contents, 249 

Mobile Learning Contents, 256, 267 

mobile learning projects, 142 

mobile multimedia computers, 179 

mobile phones, 15,40,83,112,165 

mobile robots, 121, 123, 131 

research, 131 

mobile social software (MoSoSo) 

applications, 80 

mobile technology instruction, 64 

Mobile Web 2.0, 79, 80 

MOBILearn, 261, 264 

MoBIO Threat, 120 

MoBIO Threat learning project, 126 

Moblogs,88 

MoLeNET,3 

Moodie, 58,160,164,170,171 

MoSoSo technologies, 82, 88, 96, 99 

294 

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Index 

MSNs (mobile social networks), 91 

m-VoIP, 82, 93, 98 

m-Web 2.0 learning, 82 

MWlCT,103 

N 

nano-learning, 96 

NFRs. See non-functional 

requirements 

non-functional requirements, 250 

definition, 251 

o 

operant conditioning, 22 

organizational use ofm-learning, 

109 

organizations and m-learning, 110 

organizations, m-learning in, 104 

p 

paradigms of pedagogy, 285 

participatory simulations, 26 

PDAs,2, 15,59,84,90, 111, 144, 

184 

pedagogical challenges to 


pedagogical evaluation, 252, 254, 

261,264 

pedagogical issues, 108 

peer instruction, 23 

Personal Response System, 143 

pervasive computing, 119, 121 

pervasive games, 126, 135 

phenomenography,25 

photojournalism, 180 

podcasting, 33, 36, 90 

portability, 222 

Privacy Rights Management for 

Mobile Applications, 265 

process-oriented view, 259 

product-oriented view, 259 

Q 

quality engineering, 251 

quality function deployment, 253, 

258 

Quality Function Deployment, 267, 

268 

quality in use, 223 

quality of m-learning information 

systems, 211 

R 

radio frequency identification, 129 

Rave Wireless, 145 

Really Simple Syndication, 33, 82, 

94 

reliability, 217 

requirements management tools, 259 

requirements traceability, 253 

Robot Sumo, 134 

RSS. See Really Simple Syndication 

s 

Savannah, 144 

second generation (2G) systems, 16 

selecting mobile technologies for 

instruction, 63 

short message service (SMS), 22, 28 

situated activity, 7 

situated learning, 177, 179, 181,200, 

203 

social and contextual challenges to 


socio-cognitive engineering method, 

262 

software architecture, 251 

software process modeling, 259 

Spain, 159 

T 

technocentric, 6 

text delivery technologies, 62 

third generation (3G) systems, 16 

time division multiple access, 16 

295 

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u 

Undergraduate Course of Reference, 

120 

usability, 218 

user experience, 177, 181, 183, 191, 

192,200 

user experience framework, 192, 202 

user-product interaction, 183 

v 

video delivery technologies, 60 

visual journalism, 185, 186, 194 

vodcasting, 20, 34, 36 

w 

Web 2.0 technologies, 79, 82, 97 

widgetization, 98 

WiTEC,142 

296 

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The Evolution of Mobile Teaching and Learning - Connected-Inge

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