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关于人工智能赋能高等教育中自我调节学习的定性系统综述。

A qualitative systematic review on AI empowered self-regulated learning in higher education.

作者信息

Lan Min, Zhou Xiaofeng

机构信息

Zhejiang Key Laboratory of Intelligent Education Technology and Application, Zhejiang Normal University, Jinhua, 321004, Zhejiang, China.

College of Education, Zhejiang Normal University, Jinhua, Zhejiang Province, China.

出版信息

NPJ Sci Learn. 2025 May 3;10(1):21. doi: 10.1038/s41539-025-00319-0.

Abstract

This systematic review explores the burgeoning intersection of Artificial Intelligence (AI) applications and self-regulated learning (SRL) in higher education. Aiming to synthesize empirical studies, we employed a qualitative approach to scrutinize AI's role in supporting SRL processes. Through a meticulous selection process adhering to PRISMA guidelines, we identified 14 distinct studies that leveraged AI applications, including chatbots, adaptive feedback systems, serious games, and e-textbooks, to support student autonomy. Our findings reveal a nuanced landscape where AI demonstrates potential in facilitating SRL's forethought, performance, and reflection phases, yet also highlights whether the agency is human-centered or AI-centered leading to variations in the SRL model. This review underscores the imperative for balanced AI integration, ensuring technological advantages are harnessed without undermining student self-efficacy. The implications suggest a future where AI is a thoughtfully woven thread in the SRL fabric of higher education, calling for further research to optimize this synergy.

摘要

本系统综述探讨了高等教育中人工智能(AI)应用与自我调节学习(SRL)之间新兴的交叉领域。为了综合实证研究,我们采用定性方法来审视人工智能在支持自我调节学习过程中的作用。通过严格遵循PRISMA指南的筛选过程,我们确定了14项不同的研究,这些研究利用人工智能应用,包括聊天机器人、自适应反馈系统、严肃游戏和电子教科书,来支持学生的自主性。我们的研究结果揭示了一个细微差别明显的局面,即人工智能在促进自我调节学习的前瞻性、表现和反思阶段显示出潜力,但也突出了代理是以人类为中心还是以人工智能为中心,这导致了自我调节学习模式的差异。本综述强调了平衡整合人工智能的必要性,确保在不损害学生自我效能感的情况下利用技术优势。这些启示表明,未来人工智能将成为高等教育自我调节学习结构中一条精心编织的线索,呼吁进行进一步研究以优化这种协同作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/45a4/12049540/60d9ef77a58b/41539_2025_319_Fig1_HTML.jpg

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