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Impact of artificial intelligence integration in STEM education on learners’ academic performance: A meta-analytic review

Truvace record
TRV-2026-2781raw data (JSON)
Version
v1Published
First published
Evidence type
Systematic review or meta-analysis
Sources
1 sourcePeer-reviewed
sha256
7341e5f003c8…check it

The integration of artificial intelligence (AI) technologies into science, technology, engineering, and mathematics (STEM) education has attracted growing scholarly interest due to its potential to improve instructional quality and academic outcomes. This study quantitatively evaluated the effect of AI integration in STEM education on learners’ academic achievement using a meta-analytic approach. Following PRISMA guidelines, empirical studies published between 2015 and 2026 were retrieved from Web of Science, IE…

The gain

A meta-analysis of 15 controlled studies found students taught STEM subjects with AI tools scored higher than control groups, with a pooled effect of g = 1.57 (95% CI 0.985 to 2.156), shrinking to 0.89 after a publication-bias adjustment.

What this doesn’t fix

The review included only 15 studies, no formal risk-of-bias assessment was done, heterogeneity was substantial (I² = 73%), and the trim-and-fill adjustment cut the pooled effect from 1.57 to 0.89.

Sources

1 on file
  1. International Journal of ADVANCED AND APPLIED SCIENCESdoi:10.21833/ijaas.2026.07.020
    Peer-reviewed2026-07-01

What the review found when it combined the studies

These are the review’s own pooled results, copied from its abstract. Truvace did not recalculate them.

  • Learner academic achievement in STEM education with AI-based interventions compared with control

    Hedges' g 1.57 (95% CI 0.985 to 2.156)

    15 studies

    The review’s own words
    The results showed a statistically significant positive effect of AI-based STEM interventions on academic achievement (g = 1.57, 95% CI [0.985, 2.156], Z = 5.256, p < 0.001).

Code checks every number above against the review’s text before it is shown. The short labels are an AI model’s reading of that text, so the review’s own sentence sits under each one. A pooled figure is only as strong as the studies behind it. How Truvace uses pooled results

Cite this record

v1

Truvace Impact Record TRV-2026-2781, v1: “Impact of artificial intelligence integration in STEM education on learners’ academic performance: A meta-analytic review.” Truvace, 2026-11-12. /record/TRV-2026-2781 (accessed on the day you copy it). sha256 7341e5f003c8c1dd…

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  1. Publishedv17341e5f003c8…

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