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A meta-analysis of AI-assisted self-regulated learning

Truvace record
TRV-2026-2721raw data (JSON)
Version
v1Published
First published
Evidence type
Systematic review or meta-analysis
Sources
1 sourcePeer-reviewed
sha256
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This meta-analysis examines the effects of artificial intelligence (AI)-based pedagogical interventions on learners’ self-regulated learning and its subdomains, including cognitive, metacognitive, and resource management strategies. In addition, the study investigates whether these effects vary across four groups of moderators concerning research context, intervention design, AI, and self-regulated learning. A systematic search of databases identified an initial pool of 5,741 potentially relevant studies, of whi…

The gain

A meta-analysis of 34 experimental and quasi-experimental studies (91 effect sizes) found AI-based teaching interventions improved students' self-regulated learning strategies by Hedges' g = 0.76 compared with control groups.

What this doesn’t fix

Results varied widely between studies (I² = 88.34%), higher education dominated the evidence base (25 of 34 studies), and the authors treat the moderator findings as exploratory and tentative.

Sources

1 on file
  1. Online Learningdoi:10.24059/olj.v30isi2.5691
    Peer-reviewed2026-11-06

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v1

Truvace Impact Record TRV-2026-2721, v1: “A meta-analysis of AI-assisted self-regulated learning.” Truvace, 2026-11-12. /record/TRV-2026-2721 (accessed on the day you copy it). sha256 d78c5a7f9d26e761…

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