Do large language models stimulate student motivation? A meta-analysis of experimental studies

With the rapid integration of generative artificial intelligence into educational environments, the motivational impact of Large Language Models (LLMs), such as ChatGPT, has become a critical area of inquiry. While LLMs are often promoted for their ability to personalize learning and increase engagement, empirical findings on their actual influence on student motivation remain fragmented. To address this gap, the present study conducts a meta-analysis of 51 experimental and quasi-experimental studies published between 2022 and 2025, systematically investigating the effects of LLM-supported instruction on student learning motivation. The results reveal that: (1) LLMs have a moderate and statistically significant positive effect on student motivation (SMD = 0.48); (2) LLMs more strongly enhance intrinsic motivation (e.g., curiosity, mastery goals) than extrinsic motivation (e.g., external incentives); (3) The greatest gains were observed in the “to accomplish” dimension of intrinsic motivation, reflecting improvements in goal-directed effort and perceived competence; (4) LLMs had limited or even negative effects on integrated regulation, indicating a potential misalignment between AI-generated content and students’ internalized personal values; (5) Moderator analyses showed that motivational outcomes varied significantly depending on the type of LLM integration, educational level, discipline, and intervention duration; (6) Short-term interventions and applications in humanities and social sciences demonstrated stronger positive effects on motivation, although one study involving younger learners reported comparatively large motivational gains, the current evidence base remains insufficient to draw generalized conclusions for this population (k = 1), highlighting an important gap for future research.The results provide timely, evidence-based guidance for educators, developers, and policymakers seeking to responsibly and effectively implement LLMs in educational settings.