Identifying and Comparing Interaction Features of Different Topic Categories in Online Learning Discussions Supported by Danmaku

Abstract

With its interactive features, danmaku, a live-chat functionality allowing viewers to post messages right on the screen while watching videos, has numerous potentials of enhancing online learning interaction. In this paper, danmaku data generated by learners in one lecture of a high-school math course was retrieved. Coding based on content analysis was conducted to identify the interaction relationship, social network was then modeled, and results were compared between co-learner presence and idea exchange discussions. It was found that co-learner presence and idea exchange discussions showed differences in conversation structure, network topology and high-degree nodes. This study enhances the understanding of the interaction in MOOC learning facilitated by danmaku and provide evidence and basis for making use of danmaku discussions to better facilitate learning interaction.