Personalized Course Retrieval Using Literature Based Method in e-Learning System

Abstract

Nowadays, many educational institutions offering elearning courses. Moreover, these courses unable to cope up with the individuals difference among learners. The learning efficiency of students increased by providing personalized course material based on characteristics such as knowledge ability, learning style, motivation in e-learning system. In this paper, we propose a new literature based method to identify learning style, motivation and knowledge ability of students automatically and dynamically using simple rules and finally offering the personalized course material based on these three factors. We used recorded data of learners' behavior during their interaction with learning objects, forums and a mapping rule to infer motivation, knowledge ability and learning styles with respect to the Felder-Silverman Learning Style Model.