Purpose This meta-analysis aims to comprehensively review the impact of Generative Artificial Intelligence (Gen-AI) on college students’ critical thinking (CT) by quantitatively integrating the results of relevant empirical studies to obtain the overall effect. Design/methodology/approach This meta-analysis synthesized data from 39 empirical studies published between 2023 and 2025. Effect sizes were calculated using random-effects models, and moderator analyses were conducted to examine potential influencing factors, including Gen-AI literacy level, disciplines, knowledge types, pedagogical approaches, user roles, Gen-AI interface types, Gen-AI roles, and Gen-AI task types. Findings The results indicated that Gen-AI had a moderately positive effect on CT (g = 0.591). Further analysis identified five significant moderating variables: disciplines, knowledge types, pedagogical approaches, Gen-AI roles and Gen-AI task types. Specifically, Gen-AI has the greatest positive impact on college students’ CT in STEM, procedural knowledge, inquiry-based learning, as a peer, and in the context of performing reflective and metacognitive tasks. These results suggest that within the overall contribution range of Gen-AI to college students’ CT, in some cases they may be more effective. Originality/value Previous research reviews, when exploring students’ higher-order thinking, did not make a clear distinction among the different types of thinking within them. Therefore, it is necessary to separate CT from broad learning outcomes or higher-order thinking and analyze its relationship with Gen-AI separately.
Xi Jiang (Mon,) studied this question.