从能力、社交到自我发展，看大模型如何影响学生学习
A Meta-Analysis of LLM Effects on Students across Qualification, Socialisation, and Subjectification
- 基于教育三维度框架，分析188项研究的实证结果
- 辅导类干预下大模型显著提升学业表现，长期反思性活动助社交发展
- 自主性培养效果弱，需设计支持参与和主体性的教学机制
大型语言模型（LLMs）被越来越多视为教育解决方案，但现有评估常局限于狭窄的成绩指标。本文以Biastia的教育三重维度——资格化（qualification）、社会化（socialisation）与主体化（subjectification）为理论框架，对133项实验与准实验研究（k = 188）进行元分析。总体而言，大模型对学生学习的影响呈正向但不均衡。在资格化方面，当大模型作为持续性辅导工具时效果显著；社会化成果则集中于长期、反思性干预中；而主体化（关联自主性与学习者成长）仍较脆弱，仅在小规模、长期研究中观察到改善。该目的导向视角表明：设计是决定性因素——缺乏参与与主体性支持的干预，会强化可测量内容，忽视教育的深层目标。对人机交互与教育研究而言，关键问题不是大模型是否有效，而是它们开启了何种未来，或否定了哪些可能。
原文摘要 · Abstract (English)
Large language models (LLMs) are increasingly positioned as solutions for education, yet evaluations often reduce their impact to narrow performance metrics. This paper reframes the question by asking "what kind of impact should LLMs have in education?" Drawing on Biesta's tripartite account of good education: qualification, socialisation, and subjectification, we present a meta-analysis of 133 experimental and quasi-experimental studies (k = 188). Overall, the impact of LLMs on student learning is positive but uneven. Strong effects emerge in qualification, particularly when LLMs function as tutors in sustained interventions. Socialisation outcomes appear more variable, concentrated in sustained, reflective interventions. Subjectification, linked to autonomy and learner development, remains fragile, with improvements confined to small-scale, long-term studies. This purpose-level view highlights design as the decisive factor: without scaffolds for participation and agency, LLMs privilege what is easiest to measure while neglecting broader aims of education. For HCI and education, the issue is not just whether LLMs work, but what futures they enable or foreclose.
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