Associative Recommendation of Learning Contents Aided by Eye-Tracking in a Social Media Enhanced Environment

摘要

In this paper, an approach to presenting the learning resources, especially those existing user-generated contents associated with learners' activities, as the recommendation to satisfy their current requirements in a social media enhanced learning system, is proposed. Users' attentions are caught and analyzed from the browsing behaviors of learners on a webpage through an eye-tracking device.