An Intelligent Agent for Personalized E-Learning

When people browse the learning materials on a Web site, the sequence of content they browse might not have any particular relations. Therefore, the proposed research tries to build an intelligent agent for discovering a specific learner´s interests in different knowledge fields dynamically, instead of finding the sequence of content he browses. Naive Bayesian classifier (NBC for short) is used as the approach of prospecting and analyzing learner´s interests. Push technology is applied to do recommendation of new coming learning materials based on the suggestion obtained by NBC. The simulation results show the power of the proposed intelligent agent.