动态更新研究，发现AI辅助数学教学效果显著，但需教师配合。
LLAMA LIMA: A Living Meta-Analysis on the Effects of Generative AI on Learning Mathematics
- 持续更新文献，用贝叶斯模型分析27项研究结果。
- 整体效应中等偏上（g=0.49），无发表偏倚。
- 教师指导与AI结合时效果更佳，其他因素尚不明确。
生成式AI在数学教育中的能力迅速发展，传统研究综述难以跟上进展且易过时。为此，我们开展一项持续更新的元分析（LIMA），基于PRISMA-LSR指南，持续纳入新文献，采用贝叶斯多层元回归模型处理嵌套与累积数据，并定期在预印本平台发布更新版本。本文报告第四版结果，涵盖27项研究，其中5项为本轮新增。分析显示总体效应为正（g = 0.49，95% 置信区间 [0.24, 0.75]），无发表偏倚。调节分析表明，当生成式AI与教师教学结合时，其益处显著高于替代教师的模式；其他调节因子证据仍不充分。
原文摘要 · Abstract (English)
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 Research syntheses remain scarce and risk being outdated by the time of publication.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 fourth version, including 27 studies, 5 of which were newly included since the third version. Analyses indicate an overall positive effect (g = 0.49, CrI [0.24, 0.75]) and no publication bias. Moderator analyses indicate strong evidence that generative AI is substantially more beneficial when it is implemented together with teacher instruction rather than replacing teachers. For other moderators, evidence is still inconclusive.
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