Living meta-analysis of 24 studies estimates moderate positive effect (g=0.40) of generative AI on mathematics learning, with benefits when used to complement rather than replace instruction.
LLAMA LIMA: A Living Meta-Analysis on the Effects of Generative AI on Learning Mathematics
2 Pith papers cite this work. Polarity classification is still indexing.
abstract
The capabilities of generative AI in mathematics education are rapidly evolving, posing significant challenges for research to keep pace. Research syntheses remain scarce and risk being outdated by the time of publication. To address this issue, we present a Living Meta-Analysis (LIMA) on the effects of generative AI-based interventions for learning mathematics. Following PRISMA-LSR guidelines, we continuously update the literature base, apply a Bayesian multilevel meta-regression model to account for nested and cumulative data, and publish updated versions on a preprint server at regular intervals. This paper reports results from the third version, including 24 studies, 3 of which were newly included since the second version. The analyses indicate a positive effect (g = 0.40) with a wide credible interval [0.14, 0.67], reflecting the still limited evidence base. Results indicate no publication bias. Moderator analyses indicate moderate evidence that generative AI is more beneficial when it complements regular instruction rather than replacing teachers.
years
2026 2verdicts
UNVERDICTED 2representative citing papers
Generative AI may break the education-based recovery mechanism for technological displacement, as evidence shows performance gains without learning gains and current measurements miss the knowledge dimension of cognition.
citing papers explorer
-
LLAMA LIMA: A Living Meta-Analysis on the Effects of Generative AI on Learning Mathematics
Living meta-analysis of 24 studies estimates moderate positive effect (g=0.40) of generative AI on mathematics learning, with benefits when used to complement rather than replace instruction.
-
Can the Recovery Mechanism Survive AI? Skill Formation, Labor, and What Current Measurement Misses
Generative AI may break the education-based recovery mechanism for technological displacement, as evidence shows performance gains without learning gains and current measurements miss the knowledge dimension of cognition.