A Semantic Approach to Intelligent and Adaptive Learning Based on Web Learning Objects

Tutoring systems are computer-based learning systems. In order to be “intelligent” they must present “humanlike” tutoring capabilities. Tutoring systems should be able to adjust the content and delivery to students’ characteristics and needs by analyzing and anticipating their effective responses and behaviors. There is ongoing research to improve the effectiveness of dialogue and feedback for intelligent tutoring systems. This research aims at the possibility of developing learning materials from an Introduction course in Web Technology as learning objects and how this can be incorporated into a web based adaptive learning and testing system. The approach is to use the current semantic web technologies to model knowledge concepts and the relationships among them, along with a format suitable for computer reasoning and support intelligent learning and personalized learning experience by integrating assessments into learning process. Keywords; Semantic, Artifical Intelligence, Learning Objects, Knowledge Representation, Adaptive Learning, Inteligent Tutoring Systems