One of today's hot topics in the field of education is the learning support system. With the progress of networks and multimedia technologies, various types of web-based training (WBT) systems are being developed for distance- and self-learning. Most of the current learning support systems synchronously reproduce lecture resources such as videos, slides, and digital-ink notes written by the teacher. However, from the perspective of support for student learning, these systems provide only keyword retrieval. This paper describes a more efficient learning support system that we developed by introducing lecture information and student arousal levels extracted from biological data. We also demonstrate the effectiveness of the proposed system through a preliminary experiment.
['Yurie Iribe', 'Shuji Shinohara', 'Kyoichi Matsuura', 'Kouichi Katsurada', 'Tsuneo Nitta']
Self-learning System Using Lecture Information and Biological Data