GazeMOOC:基于XR内容的MOOC注视数据驱动视觉分析系统

Proceedings of the 27th ACM Symposium on Virtual Reality Software and Technology Pub Date : 2021-12-08 DOI:10.1145/3489849.3489923

Hao Wang, Yaqi Xie, Mingqi Wen, Zhuo Yang

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引用次数: 1

摘要

新型冠状病毒疫情后，MOOC被广泛使用，更加流行。为了提高学习效果，MOOC正在借助虚拟化身、虚拟场景、实验等XR技术不断发展。本文提出了一种新的可视化分析系统GazeMOOC，它可以评估学习者在XR内容的MOOC中的学习参与度。对于相同的MOOC内容，对所有学习者的注视数据进行记录和聚类。通过区分分心学习者和主动学习者的注视数据，GazeMOOC可以帮助评估MOOC内容和学习者的学习参与度。

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

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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Proceedings of the 27th ACM Symposium on Virtual Reality Software and Technology

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