# LLAMA LIMA: A Living Meta-Analysis on the Effects of Generative AI on Learning Mathematics

arXiv: https://arxiv.org/abs/2601.18685 · HTML: https://mlsanity.com/paper/2601.18685/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 88 references that are in the map.
- First posted on arXiv 26 Jan 2026.

## Builds on (most cited first, 2 of 2)

- [BrickSmart: Leveraging Generative AI to Support Children's Spatial Language Learning in Family Block Play](https://mlsanity.com/paper/2504.11138/) (2025)
- [Large Language Models Don't Make Sense of Word Problems. A Scoping Review from a Mathematics Education Perspective](https://mlsanity.com/paper/2506.24006/) (2025)

## Built on by (most cited first, 1 of 1)

- [Toward Measuring AI's Effects on Skill Formation: The Stock-Formation Gap](https://mlsanity.com/paper/2605.16283/) (2026)

## Abstract (arXiv)

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 Research syntheses remain scarce and risk being outdated by the time of publication. We present a Living Meta-Analysis (LIMA) on the effects of generative AI-based interventions for learning mathematics. We update the literature base every two months and apply a cumulative Bayesian multilevel meta-regression model. This paper reports results from the fifth version, including 34 studies, 7 of which were newly included since the fourth version. Results indicate an increasingly positive effect (g = 0.57, CrI [0.36, 0.79]) and no evidence in favor of a publication bias. Moderator analyses indicate that effects vary by integration mode and intervention duration: Larger effects were observed when generative AI supplemented teacher instruction and in longer interventions. Moderate evidence for stronger effects was observed in studies involving younger learners and more recent technology. For other moderators, evidence is still inconclusive.