A Personalized E-Learning System Based on User Profile Constructed Using Information Fusion

In this paper, we describe a personalized e-learning system which can automatically adapt to the interests and levels of learners. The system is designed based on the IEEE Learning Technology Systems Architecture (IEEE LTSA) to achieve high scalability and reusability. A feedback extractor with fusion capability is proposed to combine multiple feedback measures to infer user preferences. User profile, which stores user preferences and levels of expertise, is collected by user profiler to deliver personalized information using the collaborative filtering algorithm.