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TRUVACE RECORD VERSION
record: TRV-2026-2752
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-11-12T17:19:18.056846Z
status: published
lens: g_space
sector: education
headline: Effects of generative artificial intelligence on students' learning motivation: evidence from a meta-analysis
dek: Background: The use of generative artificial intelligence (GenAI) in the education setting has expanded quickly. GenAI may enhance learning motivation by providing immediate feedback, adaptive support, and multimodal resources, yet empirical findings remain inconsistent. Aims: To address the controversy of current studies, a meta-analysis was conducted to examine the overall effect of GenAI on students' learning motivation and test whether effects differed across study contexts. Methods: A random-effects meta-an…
gain_title: A meta-analysis of 42 controlled studies with 6,059 students found those learning with generative AI scored higher on motivation than comparison groups (Hedges' g = 0.764), though effects varied widely between studies.
problem_title: (none)
trace_subject: (none)
gain_reading: A meta-analysis of 42 controlled studies with 6,059 students found those learning with generative AI scored higher on motivation than comparison groups (Hedges' g = 0.764), though effects varied widely between studies.
gain_evidence: The random-effects model showed a positive average effect of GenAI on students’ learning motivation (Hedges’ g = 0.764). | A random-effects meta-analysis synthesized 56 effect sizes from 42 controlled experimental and quasi-experimental studies involving 6,059 participants.
problem_reading: (none)
problem_evidence: (none)
quick_read: Researchers at East China Normal University and Qingdao University pooled 56 effect sizes from 42 controlled and quasi-experimental studies, covering 6,059 students, published between 2023 and 2025. Students who learned with generative AI showed higher motivation than comparison groups, with an average Hedges' g of 0.764 (95% CI 0.566 to 0.962), which the authors describe as moderate to large.

Results varied a great deal between studies (I2 = 93.7%), and the 95% prediction interval ran from -0.689 to 2.217. The authors say the pooled figure is a positive average rather than proof of a stable effect in every classroom, and that the findings do not support the claim that GenAI reliably raises motivation everywhere.

Effects looked larger among university students (g = 0.886) than secondary (0.360) or primary pupils (0.311), larger in language learning (0.946) than science (0.109), and larger on mobile devices (0.782) than computers (0.303). These subgroup comparisons are exploratory, because the factors are study-level traits rather than manipulated conditions.
limitation: The very high heterogeneity (I2 = 93.7%) means the average effect does not hold across all contexts, and the subgroup differences are exploratory because they reflect study-level characteristics rather than manipulated conditions.
tag: Evidence-backed gain
key_points: The review pooled 56 effect sizes from 42 studies with 6,059 participants; sample sizes ranged from 32 to 486 students. | Average effect on learning motivation was g = 0.764 (95% CI 0.566 to 0.962), with heterogeneity I2 = 93.7% and a prediction interval from -0.689 to 2.217. | Effects were larger in collectivist contexts (g = 0.815, 49 effect sizes) than individualist ones (g = 0.367, 7 effect sizes). | University students showed g = 0.886, versus 0.360 for secondary and 0.311 for primary students; language studies (0.946) outpaced science (0.109, not significant). | Mobile-device use (g = 0.782) beat computer use (g = 0.303); GenAI function, intervention length, motivation type, student gender and publication year were not significant moderators. | Leave-one-out checks kept the pooled effect between 0.695 and 0.840, and Egger's test (p = 0.057) gave no clear evidence of publication bias. | Included studies scored 18 to 23 out of 24 on a 12-item quality scale (mean 20.38).
rundown: The authors searched Web of Science, ERIC, ProQuest, EBSCO and Scopus for studies from January 2023 to November 2025, finding 2,365 records plus 74 from citation chasing. After removing 541 duplicates and screening, 42 studies met the criteria: students from primary school to university, a GenAI-supported group, a non-GenAI comparison group and a quantitative motivation score.

Two authors independently coded every study and rated quality (Cohen's kappa 0.83 for quality ratings, 0.91 for coding). Effects were computed from post-test means and standard deviations. A three-level model was tested for dependent effect sizes, but a simpler two-level random-effects model was kept because the extra variance component did not improve fit.

The pooled effect was positive for both intrinsic and extrinsic motivation, but the difference between the two was not significant. Language-learning studies made up 32 of the 56 effect sizes and university samples 43, so the average leans heavily on those settings.

The authors caution that the moderator results show association, not cause, and call for future work on the instructional, learner and contextual conditions in which GenAI best supports motivation.
sources:
- peer_reviewed | Frontiers in Psychology | https://doi.org/10.3389/fpsyg.2026.1832451 | 2026-09-24
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