Adaptive E-Learning System Based on Semantic Search and Recommendation in the Arab World

Abstract

The success of any e-learning system depends on the retrieval of relevant learning contents according to the requirement of the learner (user). This leads to the development of the adaptive e-learning system to provide learning materials considering the requirements and understanding capability of the learner. This chapter aims to propose the system of personalized semantic search and recommendation of learning contents on the e-learning Web-based systems. Semantic and personalized search of learning contents is based on expansion the query keywords by using of the semantic relations and reasoning mechanism in the ontology. Personalized recommendation of learning objects is based on the learner profile ontology to guide what learning contents a learner should study. For the Arab world, to achieve the learning for all goals and meet the learner’s requirements, it must build more inclusive, including the personalization services, and has semantic learning content in the learning systems. The authors’ proposed system is efficient, more effective, and more learner-friendly in the Arab sector because it responds to every learner and his needs individually with a timely and precise adaptation of learning materials.