The Clustering Analysis System Based on Students' Motivation and Learning Behavior

MOOCs offer a wide range of courses and include high-quality video lectures that feature professors from universities across the world. Such innovative use of video-based learning has attracted attention from researchers and practitioners in the education field. Therefore, we conducted questionnaire surveys to obtain student learning motivations and learning styles during such a course. The purpose of this study is to propose a method that can use questionnaire results and predefined group types to classify students in the early stages of a class. We found a link between learning motivation and learning behavior. As the class progressed, we executed a daily clustering system. The questionnaire results provided only a preliminary reference which forms the basis for student grouping. With a greater sample, we could also better optimize the definition of groups and add new groups.