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.
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CITATION STYLE
Wang, H., Xie, Y., Wen, M., & Yang, Z. (2021). GazeMooC: A gaze data driven visual analytics system for MOOC with XR content. In Proceedings of the ACM Symposium on Virtual Reality Software and Technology, VRST. Association for Computing Machinery. https://doi.org/10.1145/3489849.3489923
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