The potential of artificial intelligence to enhance self-regulated learning: A three-level meta-analysis

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Authors: Junsheng Wu, Jiahe Gu, Dan Sun, Xiong Yuhan, Hexiang He, Peiyao Zhang, Zi Yan
Cited by: 1
References: 101

Abstract

As artificial intelligence (AI) technologies rapidly advance in education, their potential to support learners’ self-regulated learning (SRL) has gained increasing attention. This meta-analysis synthesized 95 effect sizes from 28 empirical studies to evaluate the overall impact of AI interventions on SRL and examine moderating variables. The results showed that AI interventions significantly improved learners’ SRL. Further analysis indicated that intervention duration and subject domain moderated effectiveness. A multiple-moderator model within the three-level framework also showed that these two variables significantly affect outcomes. Overall, the findings offer guidance for educators and policymakers and support integrating AI technologies into educational practice to enhance learners’ SRL strategies.

Fields of Study & Subjects

Innovative Teaching and Learning Methods AI in Service Interactions Neuroscience Education and Cognitive Function

Publication details

Journal / source
Journal of Research on Technology in Education
Publisher
Informa UK Limited
Pages
1–22
Publication date
1 May 2026
Language
EN