利用智能手表来评估学生对在线视频课程的感知难度和兴趣

Proceedings of the 11th International Conference on Education Technology and Computers Pub Date : 2019-10-28 DOI:10.1145/3369255.3369291

Jinhan Choi, Jeongyun Han, Woochang Hyun, Hyunchul Lim, S. Huh, Sohyun Park, B. Suh

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引用次数: 5

摘要

在线视频已经成为传播教育材料的流行媒介。分析视频交互日志可以提供有价值的教育见解。然而，对于小型的在线课程，由于样本规模较小，分析在线日志往往不足以对学生的学习行为进行建模。在本研究中，我们旨在探索利用商业智能手表来增强此类模型构建的可行性。我们收集了在线视频互动日志和智能手表的生理数据，并建立模型来估计学生在观看在线视频讲座时的感知难度和兴趣。结果表明，智能手表数据可以显著提高他们感知难度和兴趣的解释方差量，分别提高100%和64%。我们希望这一结果可以为智能手表在学生在线视频学习中的应用提供参考。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Leveraging Smartwatches to Estimate Students' Perceived Difficulty and Interest in Online Video Lectures

Online videos have become a popular medium for delivering educational materials. Analyzing video interaction log can provide valuable educational insights. However, for small-sized online courses, due to the small size of samples, analyzing online log is often not enough for modeling students' learning behaviors. In this study, we aim to explore the feasibility of utilizing commercial smartwatches to augment building of such models. We collected online video interaction log as well as physiological data from smartwatches and built models to estimate the perceived difficulty and interest of students while watching online video lectures. The results show that smartwatch data could significantly improve the amount of explained variance in their perceived difficulty and interest by 100% and 64% respectively. We hope the result could inform the application of a smartwatch for students' in online video learning.

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Proceedings of the 11th International Conference on Education Technology and Computers

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