Personalized E-Learning Environment based on Ontology to Improve Students' School Levels

Abstract

Personalization of learning is the core of current research in the E-learning area. For effective learning, a personalized content provided to each student remains necessary. Students who use this educational web-based applications aim at learning knowledge which corresponds to their expectations. However, their school level and interests are different. Thus, the system should recommend to students a learning content that match the most their knowledge levels and is interesting enough to keep their attention. This paper describe a method enabling system to classify students depending on their school levels. This method will allow a semantic classification of profiles integrated within ontology. Accordingly, the system will be able to categorize students in a definite profile based on their school level and make a decision about the interfaces content recommended by each type of profile. To evaluate the effectiveness of the proposed approach, an experiment was conducted on students from middle school. The experimental results show that, such a system recommends to each student a field of study (FoS) whose subjects taught will match the best their skills. The E-Learning content based on those subjects will allow the enhancement of student’s school level.