Sectional Review Recommendations based on Learner's Comprehension in Video-based Learning

Abstract

This paper proposes a video-based learning environment that can evaluate learners’ understanding and provide them with recommendations for reviewing sectionsthat they did not understand sufficiently. For such recommendations, the system needs to recognize the video content and identify the parts the learners did not understand. This study develops the function with Kit-build concept map that allows for the automatic evaluation of the learners' concept maps and for review recommendations of the video sections the learners did not understand. To verify the function, we used the system as homework to prepare for a lecture. From the learners’ log information; although only a few learners used this mechanism, they had a higher improvement rate in their concept maps when they use the function than they did not. This result shows the possibility of the use of KBmaps in self-learning with video lectures used in MOOCs, flipped learning and so on.