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Antonella Esposito Moreno, M. A., Fost, N. C. and Christakis, D. A. (2008) “Research Ethics in the MySpace Era”, Pediatrics, Vol. 121 No. 1 January 2008, pp. 157-161, http://pediatrics.aappublications.org/cgi/content/abstract/121/1/157 (accessed on 15/01/2011). Paccagnella, L. (1997) “Getting the seats of your pants dirty: strategies for ethnographic resarch on virtual communities” [online] Journal of Computer Mediated Communication vol. 3, n.1, http://jcmc.indiana.edu/vol3/issue1/paccagnella.html#bio (accessed on 15/01/2011). PLENK 2010 – Personal Learning Environments and Knowledge, ‘How this course works’, http://connect.downes.ca/how.htm (accessed on 15/01/2011). Siemens, G. (2010) “Reflections on open courses”, blog post August 19 th 2010, in Connectivism. Networked and social learning, http://www.connectivism.ca/?p=267 (accessed on 10/01/2011). Tracy, F. and Carmichael, P. (2010) “Research ethics and participatory research in an interdisciplinary technology-enhanced learning project”, International Journal in Research & Method in Education, vol. 33, n. 3, pp. 245-257. Vieweg, S. (2010) “The Ethics of Twitter Research”, presented at workshop Revisiting Research Ethics in the Facebook Era:Challenges in Emerging CSCW Research, The ACM Conference, Savannah, Georgia, US, http://www.cc.gatech.edu/~yardi/ethics-cscw2010_files/AcceptedPapers.htm (accessed on 09/01/2011). Whiteman, N. (2009) “Internet Research”, Research Methods Lecture Pack, Mres in Educational and Social Research, Institute of Education, pp. 57-67. 224

Making Constraints and Decisions Explicit to Support Project-Based Collaborative Learning Gert Faustmann Department of Cooperative Studies, Berlin School of Economics and Law, Germany gert.faustmann@hwr-berlin.de Abstract: Learning projects serve as motivational instruments to transfer knowledge and competences relating to real world problems. Yet, the learning effect varies among participants. The anticipated results of a project and their relation to real life questions are formed by complex requirements and, while the project advances, the complexity of the results emerging increases. Furthermore, project groups often consist of participants with little experience in the subject of the project. While the project progresses, the overview of requirements and results already developed is lost. The learning effect can now be raised by making the requirements on the expected project results as well as the decisions for existing results explicit. In this way, participants understand the decisions of others engaged in the ongoing project and they are able to align the existing results with the requirements imposed on them. Additionally, new ways of collaborative learning are possible when, for instance, the task is to develop constraints on or between the respective project results. Former research developed a concept to keep less experienced project members in the productive process while forcing other project members to give arguments for their results. The current work describes an approach which aims to integrate the requirements on results in the learning process. While arguments were to include digital documents or specific parts of these documents for clarification purposes, the incorporation of explicit requirements is now also manifested in digital documents. The requirements can then be related not only to single result documents, but also to whole sets of expected documents. The paper gives an example of a software development project where some design documents have to be developed. It shows how constraints on these documents are presented and how these constraints affect the collaborative learning process. Keywords: project-based learning, cscl, arguments, digital documents, learning process 1. Introduction The integration of learning projects into teaching is a common instrument and improves the ability of students to solve real world problems (Doppelt 2003). Yet, certain problems arise when practicing project based learning:First, the participants’ knowledge of the project in relation to the project task often differs. While this is a key reason for implementing a “collaborative” approach in learning, for some learners the learning effect may stagnate, because the project advances and the results become more complex making it more difficult for them to understand the new results and their relationship. Without any explicit help the students will not be able to contribute to the project. Second, in nearly all domains the expected results share complex requirements and dependencies, which themselves can be seen as knowledge about the domain space. We can distinguish between requirements that are related to just a single project result (e.g. the amount of pages for one specific text document) and overall requirements, that are related to more than one result (e.g. use UML diagrams for designing a software system). Especially the latter are difficult to learn because they often contain implicit knowledge of a domain (as in the above example, which diagram types have to be used and how they interact). We take a generic approach in order to tackle both sides of the problem. While the participants work in a learning project and contribute result documents, they are committed to add further documents that explain these results. These documents can be arbitrary digital documents allowing to add information of any form. So other project members better understand how the existing results were developed. To manage the complexity of the project constraints, the teacher can choose to add documents that influence the later development of the result documents. These constraint documents support the learners in constructing the overall results. With the introduction of supporting documents for expected and existing results of a project, it is possible to think of new learning processes that integrate these documents in different learning phases. The paper starts with an account of existing approaches that incorporate any kind of metadata into learning processes for reasons of supporting the learners in understanding the project’s results. Then an example for a learning project from the field of software programming is introduced. This will be the basis for defining the different document types and the way they are used in this concept. Afterwards some new approaches on how to organize the learning process will be presented. The paper ends 225

Making Constraints and Decisions Explicit to Support<br />

Project-Based Collaborative Learning<br />

Gert Faustmann<br />

Department of Cooperative Studies, Berlin School of Economics and Law,<br />

Germany<br />

gert.faustmann@hwr-berlin.de<br />

Abstract: Learning projects serve as motivational instruments to transfer knowledge and competences relating to<br />

real world problems. Yet, the <strong>learning</strong> effect varies among participants. The anticipated results of a project and<br />

their relation to real life questions are formed by complex requirements and, while the project advances, the<br />

complexity of the results emerging increases. Furthermore, project groups often consist of participants with little<br />

experience in the subject of the project. While the project progresses, the overview of requirements and results<br />

already developed is lost. The <strong>learning</strong> effect can now be raised by making the requirements on the expected<br />

project results as well as the decisions for existing results explicit. In this way, participants understand the<br />

decisions of others engaged in the ongoing project and they are able to align the existing results with the<br />

requirements imposed on them. Additionally, new ways of collaborative <strong>learning</strong> are possible when, for instance,<br />

the task is to develop constraints on or between the respective project results. Former research developed a<br />

concept to keep less experienced project members in the productive process while forcing other project members<br />

to give arguments for their results. The current work describes an approach which aims to integrate the<br />

requirements on results in the <strong>learning</strong> process. While arguments were to include digital documents or specific<br />

parts of these documents for clarification purposes, the incorporation of explicit requirements is now also<br />

manifested in digital documents. The requirements can then be related not only to single result documents, but<br />

also to whole sets of expected documents. The paper gives an example of a software development project where<br />

some design documents have to be developed. It shows how constraints on these documents are presented and<br />

how these constraints affect the collaborative <strong>learning</strong> process.<br />

Keywords: project-based <strong>learning</strong>, cscl, arguments, digital documents, <strong>learning</strong> process<br />

1. Introduction<br />

The integration of <strong>learning</strong> projects into teaching is a common instrument and improves the ability of<br />

students to solve real world problems (Doppelt 2003). Yet, certain problems arise when practicing<br />

project based <strong>learning</strong>:First, the participants’ knowledge of the project in relation to the project task<br />

often differs. While this is a key reason for implementing a “collaborative” approach in <strong>learning</strong>, for<br />

some learners the <strong>learning</strong> effect may stagnate, because the project advances and the results<br />

become more complex making it more difficult for them to understand the new results and their<br />

relationship. Without any explicit help the students will not be able to contribute to the project.<br />

Second, in nearly all domains the expected results share complex requirements and dependencies,<br />

which themselves can be seen as knowledge about the domain space. We can distinguish between<br />

requirements that are related to just a single project result (e.g. the amount of pages for one specific<br />

text document) and overall requirements, that are related to more than one result (e.g. use UML<br />

diagrams for designing a software system). Especially the latter are difficult to learn because they<br />

often contain implicit knowledge of a domain (as in the above example, which diagram types have to<br />

be used and how they interact).<br />

We take a generic approach in order to tackle both sides of the problem. While the participants work<br />

in a <strong>learning</strong> project and contribute result documents, they are committed to add further documents<br />

that explain these results. These documents can be arbitrary digital documents allowing to add<br />

information of any form. So other project members better understand how the existing results were<br />

developed. To manage the complexity of the project constraints, the teacher can choose to add<br />

documents that influence the later development of the result documents. These constraint documents<br />

support the learners in constructing the overall results. With the introduction of supporting documents<br />

for expected and existing results of a project, it is possible to think of new <strong>learning</strong> processes that<br />

integrate these documents in different <strong>learning</strong> phases.<br />

The paper starts with an account of existing approaches that incorporate any kind of metadata into<br />

<strong>learning</strong> processes for reasons of supporting the learners in understanding the project’s results. Then<br />

an example for a <strong>learning</strong> project from the field of software programming is introduced. This will be the<br />

basis for defining the different document types and the way they are used in this concept. Afterwards<br />

some new approaches on how to organize the <strong>learning</strong> process will be presented. The paper ends<br />

225

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