Learning Support through Personalized Review Material Recommendations

Abstract

Recent enrichment of digital learning environments has made it possible to obtain learning logs (data) on learners' learning behavior. In this situation, it is possible to recommend learning contents which are appropriate for individual learner by analyzing learning data. Our study develops a learning support system which recommends personalized review materials based on the results of quizzes and learning activities recorded by e-textbooks. In this paper, we explain the details of the system and report experimental results.