面部表情识别揭示了学生在线课堂上的参与度:与六个参与度测量的相关性
PloS one
|October 22, 2025
概括
面部表情,特别是快乐,与在线第二语言 (L2) 学习中的情感参与相关. 这种新的方法可以更好地评估学生对数字教育的参与度.
科学领域:
- 教育技术的教育技术
- 应用语言学 应用语言学
- 心理学 心理学 心理学
背景情况:
- 传统的学生参与在线学习的评估是有限的,未能捕捉动态和多维的方面.
- 情绪因素在第二语言 (L2) 获取环境中尤为重要.
- 现有的方法在与同步在线学习环境所需的时间灵敏度作斗争.
研究的目的:
- 引入和验证一种新的多方法框架,用于在线学习中对时间敏感的参与度评估.
- 调查实时面部表情 (快乐) 与中文L2学习者的各种参与度之间的相关性.
- 探索面部表情识别作为评估在数字L2教育中的情感参与的工具的实用性.
主要方法:
- 一个多方法框架,结合实时面部表情识别,动态自我报告和观察措施.
- 对来自中国L2学习者的同步在线课堂数据的分析.
- 自动检测到的快乐表达和六个已确定的参与度 (静态和动态) 之间的相关性分析.
主要成果:
- 在幸福表达和自我报告的情感参与之间发现了显著而强大的相关性.
- 面部表情识别捕获了动态参与波动,与回顾性自我报告和观察相对应.
- 没有观察到与行为参与,认知参与或流体验有显著的相关性.
结论:
- 面部表情,特别是快乐,是在线L2学习中情感参与的有价值指标.
- 面部表情识别可以在全面的,多方法的参与评估框架内作为一个有针对性的工具.
- 这种方法增强了对数字教育的参与度评估,特别是在L2环境中.
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