MIND模型是一个微学习AI集成的教学设计,用于增强学习成果
Wali Khan Monib1, Atika Qazi2, Rosyzie Anna Apong3
1Centre for Lifelong Learning, Universiti Brunei Darussalam, Gadong, BE1410, Brunei Darussalam. walikhan.szu@gmail.com.
Scientific reports
|November 20, 2025
概括
与传统方法相比,新的微学习AI集成教学设计 (MIND) 模型显著改善了学习成果. 这种人工智能增强的方法提高了知识的获取和应用,证明了其在现代教育中的有效性.
科学领域:
- 教育技术的教育技术
- 教学设计的教学设计.
- 教育中的人工智能
背景情况:
- 微型学习正因人工智能进步和各种学习者需求而获得引力.
- 现有的教学设计框架很难优化微学习的结果.
- 需要创新的模型来提高微型学习的有效性.
研究的目的:
- 开发和验证一个新的微学习AI集成教学设计 (MIND) 模型.
- 为了比较MIND模型与ADDIE模型对微型学习的有效性.
- 评估MIND模型对各种学习成果和学习者人口统计学的影响.
主要方法:
- 采用混合方法方法,使用微型学习模块进行干预.
- 实验组使用了MIND模型,对照组使用了ADDIE模型.
- 进行了定量分析 (ANCOVA,t-test,Kruskal-Wallis) 和定性主题分析.
主要成果:
- 在增强知识的获取,理解和应用方面,MIND模型显著优于ADDIE模型.
- 在MIND模型组中,学习成果在性别,就业状况和地区之间一致.
- 定性数据表明,MIND开发的模块促进了媒体丰富,互动,参与和动机.
结论:
- MIND模型是一个有效的教学设计框架,用于优化微学习结果.
- 该模型在各种学习者群体中展示了包容性和可访问性.
- MIND模型提供了一种可适应的方法,用于将先进技术集成到正式,非正式和非正式的学习环境中.
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