The research of personalized learning system based on learner interests and cognitive level

Based on learners´ personalization features, the personalized learning system can actively recommend learning contents for learners to learn, which fully reflects the thought and idea of modern education. Nowadays, it has become one of the hot research topics in the domain of learning system development. This paper constructs vector space model for learning resources in knowledge base and also constructs learner interest model and learner cognitive level model, and mines learning resources which the learners are interested in by tracking the learners´ learning behaviors, so that we can update the interest model. In the learning process, according to learner interest model and learner cognitive level model, the system can recommend learning resources based on content filtering or collaborative filtering recommendation technology, which can effectively improve the efficiency and quality of learning. In the end, this paper verifies the effectiveness of the proposed method by comparison experiment.