Development of A Multi-Agent Based Adaptive E-Learning Environment
Project no. 1359 · Status: Kapanmış · 2018
Summary
In this project, a multi-agent-based adaptive e-learning system that supports personalization based on learning styles is proposed. Considering that the importance of distance education has increased with the effect of the Covid-19 pandemic, it is aimed to propose an adaptive e-learning system solution that offers more effective learning experiences by taking into account the individual differences in the learning processes of the students. The Felder and Silverman learning style model was used to represent individual differences in students’ learning processes. In the proposed system, it is aimed to recommend learning materials that are suitable for learning styles and previous knowledge levels of the students. With the multi-agent-based structure, an effective control mechanism is devised to monitor the interaction of students with the system and to observe the learning levels of each student. The purpose of this control mechanism is to provide a higher efficiency in the subjects the students study compared to non-personalized e-learning systems. This project focuses on proposing an adaptive e-learning system architecture and the development of the first prototype of it. In order to test the effectiveness of the proposed system, personalized course materials should be prepared according to the learning styles of the students. In this context, it is planned as future work to use the proposed system within the scope of a course in which the educational content is personalized.