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Effects of Generative Artificial Intelligence on K-12 and Higher Education Students’ Learning Outcomes: A Meta-Analysis

Truvace record
TRV-2026-2836raw data (JSON)
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v1Published
First published
Evidence type
Systematic review or meta-analysis
Sources
1 sourcePeer-reviewed
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Generative artificial intelligence (GenAI) has significant potential for educational innovation, although its impact on students’ learning outcomes remains controversial. This study aimed to examine the impact of GenAI on the learning outcomes of K-12 and higher education students, and explore the moderating factors influencing this impact. A meta-analysis of 49 articles showed that the mean effect sizes of GenAI on students’ learning achievement and learning motivation were 0.857 and 0.803, respectively, indica…

The gain

A meta-analysis of 49 articles found generative AI use was linked to higher student learning achievement (mean effect size 0.857) and learning motivation (0.803) across K-12 and higher education.

What this doesn’t fix

The effect on learning motivation is partly a novelty effect, and its size decreases as experiments run longer, so early gains may overstate lasting benefit.

Sources

1 on file
  1. Journal of Educational Computing Researchdoi:10.1177/07356331251329185
    Peer-reviewed2025-04-11

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v1

Truvace Impact Record TRV-2026-2836, v1: “Effects of Generative Artificial Intelligence on K-12 and Higher Education Students’ Learning Outcomes: A Meta-Analysis.” Truvace, 2026-11-12. /record/TRV-2026-2836 (accessed on the day you copy it). sha256 1dc787c7a3d07ccb…

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