Using Semantic Web Technologies in a Web Based System for Personalized Learning AI Course

Abstract

Utilization of semantic web technologies in educational systems is rapidly expanded, bringing new and more efficient teaching and learning capabilities. Semantic Web Based Educational Systems (SWBEs) rely on semantic web technologies and are proved to be more intelligent and personalized to the students learning needs. In this paper, we present a semantic web based adaptive educational system that is developed to assist the students in learning the challenging subjects of the Artificial Intelligence course. The system utilizes ontologies to represent the domain of the course's curriculum and the student model. Also, the Semantic Web Rule Language (SWRL) rules are used for making decisions on the learning activities to propose to the student according to his/her profile and knowledge level. The evaluation results indicate quite promising performance regarding the system's learning capabilities and functionality.