January 2012 Volume 15 Number 1 - Educational Technology ...

Learning is a cognitive activity that differs from a student to a student. Analyzing adaptability in an e-learning
system has explicitly pointed out the importance of the modeling learners’ cognitive characteristics, particularly
learning styles as the most explored cognitive features.
There are several different learning style models presented in literature 0; however, Felder-Silverman Learning
Styles Model (FSLSM) is often used for providing adaptability regarding learning styles in e-learning environments
0. Felder-Silverman model describes a single student along four dimensions 0: 1) Active and reflexive learning style;
2) Sensitive and intuitive learning style; 3) Visual and verbal learning style;4) Sequential and global learning style.
Research objectives
The primary goal of the study was to develop an efficient method for creating adaptive distance education courses in
the Moodle LMS. The courses will be organized and adapted to groups of students. Adaptation is based on students’
characteristics, particularly learning styles. The following steps were used:
Defining main phases and requirements in developing personalized e-education systems;
Clustering students by their learning styles;
Personalization and adaptation of e-learning courses.
The key idea of this paper is based upon adaptation of courses within the existing Moodle LMS, in order to eliminate
the need for developing new modules or designing entirely new solutions. The e-learning system used in the research
and described in this paper is used by a large number of users/students daily. The idea was to perform adaptation in
such a way to make process economically justified, not time consuming, bearing in mind the environment in which
the courses were conducted.
Personalization we would achieve in our system is a personalization for a group, not for a person. We claim that this
approach is appropriate for three reasons:
1. When the courses are attended by a large number of students, due to the numerous differences in their individual
characteristics, the personalization for each student individually is not justified. Taking into consideration the
existing differences, some common features can be identified and then they can be assigned into respective
groups on the basis of these features.
2. Group personalization can be achieved at the beginning of the course. Therefore, a student will be provided with
an adapted online course during the whole learning process.
3. Group personalization is cheap and efficient. Teachers need to adapt learning materials and activities to typical
groups of students instead of to each student. This is particularly efficient when a large number of students
attend the course.
If the adaptation is done at the beginning of the learning process, some of the AHS disadvantages will be overcome.
By using students’ learning styles it is possible to define typical learning groups and to assign new students into the
groups at the beginning of their courses. The data needed for classifying the new students into these groups can be
gathered promptly, by using an appropriate questionnaire or a test, and analyzed with some of the business
intelligence tools 0. Each group of students will be provided with specific teaching materials and activities, suited to
their learning style. This approach enables adaptation controlled by teacher, and also adaptation that does not depend
upon the version of Moodle LMS. It is not necessary to change or add modules. The adaptation is achieved through
the customization of Moodle LMS. Personalization is not performed for all the characteristics, but only for those the
research findings designate as the most important. It is in such a way that the economic and time efficiency of the
adaptation process is achieved.
In the proposed model, there are no automated adaptation mechanisms. However, the activities the course organizers
have to perform to carry out the course adaptation can be automated to a certain extent.
Method for Moodle course adaptation
In order to improve the process of personalization in e-learning systems and improve its effectiveness, its main
phases and requirements have to be identified first 0. The steps shown in Figure 1. should not be conducted
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