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在教学过程中识别心率变化
Jan Francisti1, Zoltán Balogh1,2, Jaroslav Reichel1
1Department of Informatics, Faculty of Natural Sciences and Informatics, Constantine the Philosopher University in Nitra, Nitra, Slovakia.
Scientific reports
|October 4, 2023
概括
这项研究表明,物联网 (IoT) 设备如何在在线学习期间通过心率来非侵入性地跟踪学生的兴奋. 这些数据可以帮助教师调整方法以改善学习成果.
科学领域:
- 教育技术的教育技术
- 物理计算生理学计算
- 人与计算机的交互
背景情况:
- 物联网 (IoT) 为非侵入性生理监测提供了新的方法.
- 了解学生的参与和激发对于有效的教学至关重要,特别是在远程学习环境中.
研究的目的:
- 调查使用常见的物联网设备进行非侵入性生理数据采集.
- 通过使用生理学数据,在教学过程中识别学生兴奋水平的变化.
- 探索心率,兴奋和学习结果之间的相关性.
主要方法:
- 收集学生在远程学习活动期间的生理数据,特别是心率 (HR).
- 记录时间标记数据,将HR与特定教学活动相关联.
- 利用物联网设备进行可访问和非侵入性数据收集.
主要成果:
- 展示了使用物联网设备监测生理反应的可行性.
- 确定了与在线课程期间学生兴奋水平相关的心率变化的模式.
- 建立了生理激发和学习参与之间的潜在联系.
结论:
- 拟议的系统可以识别学生兴奋的转变,为提高教学效率提供了一条途径.
- 实时监测兴奋可以使教师调整教学策略,以提高学生的理解.
- 这种方法支持数据驱动的改善教育交付和学习成功.
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