learning - Academic Conferences Limited

Michaela Drozdová et al.
each individual student in the course. On the basis of students’ personal characteristics identification,
they will be provided with learning material in the form which shall be most convenient to them.
The model of learning being created is based on a new paradigm – the personalization of learning
environment. In an ideal case, this environment consists of three parts: a student part, a learning
materials database part and a part representing the system of adaptive algorithm.
Our goal is to create adaptive eLearning environment – an environment in which the student learns
through directed self-study form. Suitable instruments for this form of teaching are so called Learning
Management Systems - LMS. These are systems incorporating teaching supports, features to support
learning management and, finally, an information system registering students, their activities and
results (Kostolányová, 2010).
For an adaptive system being able to respect the diversity of users, it cannot be anonymous (Takács,
2010). The collection of data about a student will be implemented in several phases. The most
important part is the student self-assessment, i.e. testing before entering the course. The second type
of students testing during the study course (testing will be classified as dynamic changing
characteristics, crucial for adjustments of the proposed course route).
In such an extensive project we first concentrated on students and their characteristics, as they are
the key subjects. Especially their learning preferences which will influence the creation of the adaptive
course route the most.
2. Student part of adaptive system
To enable the learning management system to react on different students, we have to choose,
describe and suitably store the student’s qualities and other attributes, which influence the process of
his/her learning.
We can gain one group of qualities straight from students with the help of a suitable questionnaire and
the second group of qualities we gain by long time monitoring of their study activities. The second
group can serve as feedback not only during the current learning, but also for the alteration of the
student’s qualities, possibly for monitoring of his/her development.
It can be generally said that each person is a truly an individual with various points of view. There is
an abundant literature available dealing with learning styles and also describing their classification. By
analyzing and studying the already published classifications by various authors (Gregorc, 1979),
(Kolb, 1984). (Mareš, 1998) we have come to the following characteristics that may be taken into
account in the area of eLearning. We have divided these characteristics into several groups:
The group of characteristics called the sensual perception describes the form of information most
convenient for the student – visual type, auditive type, kinesthetic type and verbal type. For this group
of characteristics we used the VARK questionnaire (Fleming, 2009) based on (Fleming, 1992). The
acronym VARK stands for Visual, Aural, Read/write, and Kinesthetic sensory modalities that are used
for learning information.
Another group of characteristics called the social aspects deals with the company most convenient to
the student within the learning process – whether the student prefers learning with his classmates,
with a teacher or by himself. For this group of characteristics the Czech version of LSI (Learning Style
Inventory) questionnaire was used (Mareš, 1993).
The group of characteristics called the affective characteristics deals with student’s feelings and
attitude which influence the learning process. The most important characteristic of this category is
motivation. For this group a part of the Czech version of LSI questionnaire was used (Mareš, 1993).
The most extensive group of characteristics is called the tactics of learning. These describe the
“technology“ of the way the student learns. The method of the student’s learning is described by the
order of learning, which can be done either subsequently in mutually related blocks (pole rule) or in
almost random manner, without connections, with large skipping (pole latitude). To describe this
characteristic a part of the ILS (Index of Learning Styles) questionnaire was used (Felder, 2009).
According to the way of learning we divide the tactics to theoretical deduction and experimentation.
To describe these characteristics a part of the ILS questionnaire was used (Felder, 2009). According
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