The potential of artificial intelligence to enhance self-regulated learning: A three-level meta-analysis
Junsheng Wu, Jiahe Gu, Dan Sun, Xiong Yuhan, Hexiang He, Peiyao Zhang, Zi Yan
Foshan University Education University of Hong Kong
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摘要与影响
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.
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