A systematic review of AI-driven intelligent tutoring systems (ITS) in K-12 education.

IF 3.6 1区心理学 Q1 EDUCATION & EDUCATIONAL RESEARCH

npj Science of Learning Pub Date : 2025-05-14 DOI:10.1038/s41539-025-00320-7

Angélique Létourneau, Marion Deslandes Martineau, Patrick Charland, John Alexander Karran, Jared Boasen, Pierre Majorique Léger

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Abstract

The use of artificial intelligence in education (AIEd) has grown exponentially in the last decade, particularly intelligent tutoring systems (ITSs). Despite the increased use of ITSs and their promise to improve learning, their real educational value remains unclear. This systematic review aims to identify the effects of ITSs on K-12 students' learning and performance and which experimental designs are currently used to evaluate them. The 28 studies analyzed in this systematic review included a total of 4597 students (N = 4597) and used quasi-experimental designs with varying intervention durations. Overall, our findings suggest that the effects of ITSs on learning and performance in K-12 education are generally positive but are found to be mitigated when compared to non-intelligent tutoring systems. However, additional research with longer interventions and increased sample sizes with greater diversity is warranted. Additionally, the ethical implications of using AI for teaching should be investigated.

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K-12教育中ai驱动的智能辅导系统（ITS）系统综述。

人工智能在教育中的应用在过去十年中呈指数级增长，特别是智能辅导系统（ITSs）。尽管信息技术系统的使用越来越多，而且它们有望改善学习，但它们真正的教育价值仍不清楚。本系统综述旨在确定信息技术对K-12学生的学习和表现的影响，以及目前用于评估这些影响的实验设计。本系统综述分析的28项研究共包括4597名学生（N = 4597），采用准实验设计，干预时间不同。总体而言，我们的研究结果表明，在K-12教育中，智能教学系统对学习和表现的影响总体上是积极的，但与非智能教学系统相比，这种影响有所减弱。然而，有必要进行更长时间的干预和更多样化的增加样本量的额外研究。此外，应该调查使用人工智能进行教学的伦理影响。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

npj Science of Learning Multiple-

CiteScore

5.40

自引率

7.10%

发文量