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TRUVACE RECORD VERSION
record: TRV-2026-2835
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-11-12T17:32:58.369437Z
status: published
lens: g_space
sector: education
headline: The Impact of Artificial Intelligence on Elementary School Students’ Learning: A Meta-Analysis
dek: This study reviewed, evaluated and synthesized the available evidence to investigate the impact of Artificial Intelligence (AI) on elementary school students’ learning. A meta-analysis was conducted synthesizing evidence from experimental and quasi-experimental studies conducted from 2020 to 2024. Out of 272 studies, 12 studies were included in the meta-analysis. The results of the meta-analysis found a positive impact of AI on elementary school students’ learning, g = 0.91, CI 95% [0.55, 1.27]. This effect size…
gain_title: A meta-analysis of 12 experimental and quasi-experimental studies from 2020 to 2024 found AI raised elementary school students' learning with a pooled effect of g = 0.91 (95% CI 0.55 to 1.27).
problem_title: (none)
trace_subject: (none)
gain_reading: A meta-analysis of 12 experimental and quasi-experimental studies from 2020 to 2024 found AI raised elementary school students' learning with a pooled effect of g = 0.91 (95% CI 0.55 to 1.27).
gain_evidence: The results of the meta-analysis found a positive impact of AI on elementary school students’ learning, g = 0.91, CI 95% [0.55, 1.27].
problem_reading: (none)
problem_evidence: (none)
quick_read: A meta-analysis pooled 12 experimental and quasi-experimental studies from 2020 to 2024, chosen from 272 screened, and found a positive effect of AI on elementary school students' learning. The pooled effect size was g = 0.91, with a 95% confidence interval of 0.55 to 1.27.

The authors call that effect size particularly large and suggest it may be explained by the small sample sizes of the included studies and potential publication bias. The figure should therefore be read as an upper-end estimate rather than a settled benefit.

Subgroup results differed: AI had less effect in Mathematics, while chatbots and automated formative assessment systems were the most effective types. The authors say long-term effects on learning still need study.
limitation: The authors say the unusually large effect may be explained by the small sample sizes of the included studies and potential publication bias, and long-term effects remain unexamined.
tag: Evidence-backed gain
key_points: The meta-analysis screened 272 studies and included 12 experimental or quasi-experimental studies published from 2020 to 2024. | The pooled effect of AI on elementary students' learning was g = 0.91, 95% CI 0.55 to 1.27. | The authors describe the effect size as particularly large. | They link the size to small samples in the included studies and potential publication bias. | AI had less effect in Mathematics than in other subjects. | Chatbots and automated formative assessment AI systems were the most effective types. | The authors call for studies of long-term impact on learning.
rundown: The review set out to synthesize the available evidence on how AI affects elementary school students' learning. It restricted itself to experimental and quasi-experimental designs from 2020 to 2024, and 12 of 272 studies met the inclusion criteria.

The headline result is a pooled Hedges' g of 0.91 with a confidence interval of 0.55 to 1.27. The authors say this indicates AI integration has the potential to support learning, but they treat the size cautiously because the included studies had small samples and publication bias is possible.

A moderator analysis found variation by subject and tool type. AI had less effect in Mathematics, while chatbots and automated formative assessment systems were the most effective. The authors recommend future studies examine long-term impact.
sources:
- peer_reviewed | Computers in the Schools | https://doi.org/10.1080/07380569.2025.2520787 | 2025-06-19
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