Concept Assessment System Integrated with a Knowledge Map Using Deep Learning

Abstract

Many students face cognitive overload and conceptual and navigational disorientation in massive open online courses. We used the learning logs of videos, the difficulty of exercises, the discrimination of exercises, and the student's ability, combined with deep learning, to determine the student's familiarity and mastery of video content. We then determined a knowledge node score, which we integrated with a knowledge map. The map could be personalized to recommend videos and exercises according to the knowledge nodes that had a low score. Therefore, students could learn where they needed to improve and adjust their learning accordingly. Moreover, teachers and teaching assistants could observe students' knowledge maps to understand their performance and help them accordingly.