An Ontology-Based Method of Adaptive Learning

In e-learning, to provide personalized service according to learner´s characteristics is becoming a hot area which is concerned by many researchers. Learner model and reasoning algorithm are two important factors of impacting the system´s effects. In this paper, we analyzed learner´s characteristics, proposed an ontology-based learner model and its representation method, described the mechanism of the adaptive learning system based on learner model, given the semantic similarity algorithm, and finally applied it in physics. The experiment shows that the algorithm, on the promise of full consideration and accurate description of learner´s characteristics, is valid and improved the accuracy and effectiveness of learning resources which are recommended.