アダプティブなラーニングバス推薦アルゴリズムに関する比較解析

抄録

　　Adaptive learning path recommendation system efficiently guides learners by constructing appropriate learning sequences from a set of recommended learning materials to reach their goals. As a vital role in adaptive learning path, recommendation algorithms could be grouped into three categories: intelligent optimization, data mining and knowledge-based algorithm.　　This paper summarizes the strategies of relevant algorithms in the learning path recommendation, as well as their strengths and weaknesses. This paper also compares and analyzes their performance to discuss their practical application value in learning path recommendation.