| Summary: | 碩士 === 國立中央大學 === 資訊工程學系 === 105 === With the popularity of network and mobile devices, more and more students start to have the self-learning class by watching videos in massive open online courses (MOOCs). Students can gain new knowledge whenever and wherever they have a network and a mobile device. But because the teacher can not teach face to face with the students, which makes teachers unable to grasp the students’ learning situation and further intervening students. So how to provide students with learning status information to give teachers is an important issue.
According to the research, students spend most of their time on watching videos on the MOOCs platforms. To solve the problems above, we could make use of the action logs which MOOC platforms record while students using the system. In this study, we uses learning analysis to understand the relationship between students’ video viewing behavior and students’ achievement, so that teachers can find out the students’ status of learning through the students’ video viewing behavior. Through the multiple correspondence analysis and Lag-sequential Analysis, this study finds out the key video viewing behavior patterns which reflecting on students’ achievement. Through the analysis results provided by this study, teachers can find out the poor learning of the students to intervening, to avoid students give up learning due to learning difficulties.
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