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在智能学习环境中,人机反能否提高学习者的学习成绩? 一个元分析.
Mengyi Liao1, Kaige Zhu1, Guangshuai Wang2
1School of Education, Pingdingshan University, Pingdingshan, Henan, China.
Frontiers in psychology
|January 25, 2024
概括
在智能学习环境中,人机反可以显著改善学习过程和学习结果. 影响有效性的关键因素包括反方向,形式和技术,强调双向,多主体和情绪反策略.
科学领域:
- 教育技术的教育技术
- 人与计算机的交互
- 学习科学 学习科学
背景情况:
- 在智能学习环境中,人机反会影响学习者的参与和发展.
- 关于这种反的稳定性和有效性的现有研究往往是矛盾的.
- 了解优化人机反的条件对于增强学习至关重要.
研究的目的:
- 系统地分析人机反对学习绩效的影响.
- 识别在智能学习中缓解人机反效果的边界条件.
- 综合了在教育中关于人机交互的经验研究中的发现.
主要方法:
- 对2010年至2022年间发表的随机对照试验进行了全面的元分析.
- 在主要的学术数据库中进行了搜索:科学网,EBSCO,PsycINFO和Science Direct.
- 使用随机效应模型来评估主要效应和异质性,并分析缓和效应以确定边界条件.
主要成果:
- 该元分析包括35篇与2222名参与者的文章,揭示了人机交互反的显著积极影响.
- 反显著提高了学习者的学习过程 (d = 0.594) 和学习成果 (d = 0.407).
- 积极的影响是由所采用的反技术的方向,形式和类型所调节的.
结论:
- 建议使用双向和多主体的反机制来优化学习表现.
- 建议优先考虑提供情绪反和反循环的技术.
- 专注于反过程,避免过度依赖机器,培养学习者的自主性.
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