Effects of AI-Supported Education on Academic Achievement : A Meta-Analysis

This meta-analysis examined the effect of AI-supported education on academic achievement in Korea. A total of 24 experimental and quasi-experimental studies published in KCI-indexed journals from 2017 to February 2026 were analyzed. Hedges’ g was calculated from post-test means, standard deviations, and sample sizes, and effects were pooled using a random-effects model. The overall effect was positive and significant, Hedges’ g = 0.89, 95% CI [0.56, 1.22], p < .001. AI intervention type showed the clearest moderator pattern, with adaptive tutoring showing the largest point estimate. Education level, subject area, study design, and publication year were not significant moderators. The findings suggest a positive effect of AI-supported education, but should be interpreted cautiously because of high heterogeneity, small subgroup sizes, and possible publication bias.

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Publication Details

Journal
Journal of Fisheries and Marine Sciences Education
Published
2026-08-26
DOI
https://doi.org/10.13000/jfmse.2026.8.38.4.686
Primary Topic
Diverse Interdisciplinary Research Innovations
Type
article
Field-Weighted Citation Impact
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article

Effects of AI-Supported Education on Academic Achievement : A Meta-Analysis

Gyun HEO, Sung-Hee KWAK
Journal of Fisheries and Marine Sciences Education
Diverse Interdisciplinary Research Innovations
article

Effects of AI-Supported Education on Academic Achievement : A Meta-Analysis

Gyun HEO, Sung-Hee KWAK
article en

Abstract

This meta-analysis examined the effect of AI-supported education on academic achievement in Korea. A total of 24 experimental and quasi-experimental studies published in KCI-indexed journals from 2017 to February 2026 were analyzed. Hedges’ g was calculated from post-test means, standard deviations, and sample sizes, and effects were pooled using a random-effects model. The overall effect was positive and significant, Hedges’ g = 0.89, 95% CI [0.56, 1.22], p < .001. AI intervention type showed the clearest moderator pattern, with adaptive tutoring showing the largest point estimate. Education level, subject area, study design, and publication year were not significant moderators. The findings suggest a positive effect of AI-supported education, but should be interpreted cautiously because of high heterogeneity, small subgroup sizes, and possible publication bias.

Journal of Fisheries and Marine Sciences EducationVol. 38(4)
Quality Education
Openalex Percentile: Top 6%
Diverse Interdisciplinary Research Innovations
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