GenAI's motivational effect varies by subject domain, largest for language learning and smallest for science (exploratory)¶

Claim · All claims
Evidence · 1 study · quant-synthesis r3 · q3
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q3 i? Between-subgroup differences across subject domains were significant (QBET = 23.785, df = 4, p < 0.05), with language studies showing the largest pooled effect (g = 0.946) and science the lowest (g = 0.109, CI crossing zero). → Fang L 2026

Evidence¶

Fang L 2026¶

Fang L, Li Z, Xiong B and Lu Z (2026). Effects of generative artificial intelligence on students' learning motivation: evidence from a meta-analysis. Front. Psychol. 17:1832451. https://doi.org/10.3389/fpsyg.2026.1832451

q3 · i? · quant-synthesis · r3

Exploratory subgroup analysis of subject domain within the meta-analysis. The article reports "QBET = 23.785" with pooled effects for language (k = 32), mathematics (k = 4), pedagogy (k = 6), information (k = 8), and science (k = 3), the last with a confidence interval crossing zero.

"Observed between-subgroup differences across subject domains were found ( QBET = 23.785, df = 4, p < 0.05), with language-related studies showing the largest pooled effect (g =0.946, 95% CI = [0.630, 1.262]), followed by mathematics (g = 0.711, 95%CI = [0.356, 1.066]) and pedagogy (g = 0.697, 95% CI = [0.261, 1.133]), then information (g = 0.291, 95% CI = [0.047, 0.535]), and lowest in science (g = 0.109, 95% CI = [−0.107,0.325])."

Discussion¶

Learner Variables¶

• Domain Context — moderator: an instructional effect differs with it

Related Claims¶

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