aceModerate evidence
More
Review of 28 studies finds AI tools improve students' self-regulated learning
Study title: The potential of artificial intelligence to enhance self-regulated learning: A three-level meta-analysis
- Evidence type
- Systematic review or meta-analysis
- Sources
- 1 sourcePeer-reviewed
- Published
- 1 min read
- Truvace record
- TRV-2026-2790cite or check it
Study title: The potential of artificial intelligence to enhance self-regulated learning: A three-level meta-analysis
A three-level meta-analysis in the Journal of Research on Technology in Education pooled 95 effect sizes from 28 empirical studies. It found that AI interventions significantly improved learners' self-regulated learning, meaning their ability to manage their own study strategies.
Read the study 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.…
The gain
A meta-analysis pooling 95 effect sizes from 28 empirical studies found that AI interventions significantly improved learners' self-regulated learning.
In brief
Intervention duration and subject domain moderated how well the AI interventions worked, and a multiple-moderator model within the three-level framework confirmed that both variables significantly affect outcomes. The authors say the findings offer guidance for educators and policymakers on integrating AI into practice.
Main points
- The meta-analysis synthesized 95 effect sizes drawn from 28 empirical studies.
- It used a three-level meta-analytic framework to handle multiple effect sizes per study.
- AI interventions significantly improved learners' self-regulated learning overall.
- Intervention duration moderated how effective the AI interventions were.
- Subject domain also moderated effectiveness.
- A multiple-moderator model showed both duration and subject domain significantly affect outcomes.
The full story
The study evaluated the overall impact of AI interventions on self-regulated learning (SRL) by combining 95 effect sizes from 28 empirical studies. A three-level framework accounts for several effect sizes coming from the same study.
Moderator analyses found that how long an intervention ran and which subject it was applied to shaped how much it helped. A multiple-moderator model showed both variables significantly affect outcomes.
The authors conclude the findings support integrating AI technologies into educational practice to strengthen learners' SRL strategies, and say they offer guidance for educators and policymakers.
Sources
1 on file- Journal of Research on Technology in Educationdoi:10.1080/15391523.2026.2643171
Talk it over
Who gets this benefit, and who was left out of the study or story?
Review of 28 studies finds AI tools improve students' self-regulated learninghttps://truvace.com/item/the-potential-of-artificial-intelligence-to-enhance-self-regulated-learning-a-th
Who gets this benefit, and who was left out of the study or story?
The gain A meta-analysis pooling 95 effect sizes from 28 empirical studies found that AI interventions significantly improved learners' self-regulated learning.
Answer in the threadHow do we know? What can this kind of evidence show, and what can’t it?
The evidence This rests on a systematic review or meta-analysis, from Journal of Research on Technology in Education.
Answer in the threadWhat does it leave open? What else would you want to know before acting on it?
Answer in the threadHave you seen AI used this way where you study, work or live? Did it go the same way?
Answer in the thread
The questions are the same on every record. The details under them are taken from this record as written.
What readers say