GazeMOOC: A Gaze Data Driven Visual Analytics System for MOOC with XR Content

VRST(2021)

引用 1|浏览2
暂无评分
摘要
ABSTRACT MOOC is widely used and more popular after COVID-19.In order to improve the learning effect, MOOC is evolving with XR technologies such as avatars, virtual scenes and experiments. This paper proposes a novel visual analytics system GazeMOOC, that can evaluate learners’ learning engagement in MOOC with XR content. For same MOOC content, gaze data of all learners are recorded and clustered. By differentiating gaze data of distracted learners and active learners, GazeMOOC can help evaluate MOOC content and learners’ learning engagement.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要