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 Research syntheses remain scarce and risk being outdated by the time of publication.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.
| Comments: | This is a living publication. See the first page of the PDF for more information |
| Subjects: | History and Overview (math.HO); Machine Learning (cs.LG) |
| Cite as: | arXiv:2601.18685 [math.HO] |
| (or arXiv:2601.18685v3 [math.HO] for this version) | |
| https://doi.org/10.48550/arXiv.2601.18685 arXiv-issued DOI via DataCite |
From: Anselm Strohmaier [view email]
[v1]
Mon, 26 Jan 2026 17:00:52 UTC (293 KB)
[v2]
Sun, 1 Mar 2026 13:57:31 UTC (337 KB)
[v3]
Thu, 21 May 2026 20:08:46 UTC (419 KB)
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