AI-enabled personalized STEM education yields a statistically significant overall effect of g = 0.455, which its authors class as small, compared with traditional non-AI instruction in K-12 schools¶
Claim · All claims
Evidence · 1 study · quant-synthesisr2·q4·i2medium
Currency · newest study 2025 · checked against its sources 2026-10-20 (automated, 1 of 1 entry) · not reviewed by a person
Subclaims¶
Reading the evidence codes
q is the design tier, i the impact, n the sample, and the kind with its r
the rigour judged within that kind: what each code means.
This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.
q4 i2 Across 99 effect sizes from 32 RCTs, students learning STEM with AI technologies scored 0.455 standard deviations above students learning without AI technologies. → Li 2025
Evidence¶
Li 2025¶
Li, S., Zeng, C., Liu, H., Jia, J., Liang, M., Cha, Y., Lim, C. P., & Wu, X. (2025). A meta-analysis of AI-enabled personalized STEM education in schools. International Journal of STEM Education. https://doi.org/10.1186/s40594-025-00566-y
q4 · i2 · quant-synthesis · r2
Random-effects meta-analysis of 99 independent effect sizes extracted from 32 randomized controlled trial studies of AI-enabled personalized K-12 STEM education. The pooled effect size was "g = 0.455 (p < 0.001)", which the authors classify as a small effect under Cohen's benchmarks.
"The overall effect size of AI-enabled personalized STEM education in K-12 schools is g = 0.455 (p < 0.001), with a 95% confidence interval of 0.327–0.583."
Discussion¶
Related Claims¶
- School level significantly moderates effects: AI-enabled personalized STEM education is more effective in junior and senior high school than in kindergarten — related
- Intelligent tutoring systems improve achievement over non-individualised instruction — related
- Gen-AI has a moderate positive overall effect on students' higher-order thinking (g = 0.609) across 29 experimental and quasi-experimental studies — related
- Learning with intelligent tutoring systems yields a moderate, statistically significant overall advantage in achievement over non-ITS modes of instruction — related
- AI-supported instruction has a moderate positive effect on student achievement in STEM education (g = 0.670 under a random effects model) — related
- AR/VR tools show the largest effect among AI application types (g = 1.765), while ITS and personalized educational games show small effects — related
- GAI-related and GAI-unrelated AI tools show no significant difference in their moderating effects on K-12 STEM learning outcomes — related
- Students improved significantly from pre- to post-test in both topics, with a medium effect in experimental design and a small effect in graphing — related
- Subject significantly moderates effects, with AI-enabled personalized STEM education most effective in comprehensive courses (g = 2.161) — a narrower finding that bears on this claim
- Learning-by-design shows medium- to large-sized positive effects on student achievement in K-12 STEM education, per meta-analysis cited by the review
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
ai-personalized-stem-overall-effect-g0455 |
title |
AI-enabled personalized STEM education yields a statistically significant overall effect of g = 0.455, which its authors class as small, compared with traditional non-AI instruction in K-12 schools |
description |
AI-enabled personalized STEM education yields a statistically significant overall effect of g = 0.455, which its authors class as small, compared with traditional non-AI instruction in K-12 schools |
status |
review |
evidence_strength |
moderate |
newest_evidence |
2025 |
source_checked |
2026-10-20 |
generated |
by process:wiki-ingest on 2026-10-15 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — li-2025 |
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