A learning grouping algorithm based on user personality

In the traditional school education, learning group promotes learning well, so people want personalized learning system to have the function of group learning automatically. Learning from cognitive psychology, learning style theory and constructivist learning theory, this paper selects learning interest, learning capability, learning style, learning activity, sex and age as the factors of user personality. And establishes user model based on the above factors. In fact, the division of labor and the members´ complementary advantages, which mean a hierarchical relationship, are important to a learning group. And the similarity of learning interest is extremely important to a learning group as well. We propose a learning grouping algorithm based on user personality for users to learn in groups, and the experimental result verifies the effectiveness of the algorithm.