SynthesisFrontiers in psychology2026
Exploring the effect of GenAI on learning outcomes in higher education: a three-level meta-analysis.
Synthesis in Frontiers in psychology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: As generative artificial intelligence (GenAI) becomes increasingly integrated into higher education, greater clarity is needed regarding its impact on student learning. Methods: This study conducted a three-level meta-analysis of 36 empirical studies, synthesizing 132 effect sizes from 7,229 participants. Learning outcomes were classified using the Learning Outcomes Thematic Group (LOTG) framework, and seven study-level moderators were examined. Results: The results indicate a significant medium overall effect of GenAI on learning outcomes ( Discussion: These findings suggest that GenAI is most effective when embedded in interactive and collaborative pedagogies. The study introduces a GenAI-Learning Alignment Perspective and outlines implications for instructional design, assessment practices, and teacher professional development.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.