Revisiting the effects of artificial intelligence in education: A meta-analysis of academic achievement and student motivation

Abstract

This meta-analytic study examines the impact of artificial intelligence (AI) applications in education on students' academic achievement and motivation. A total of 215 independent effect sizes (achievement: n = 172; motivation: n = 43) were synthesized using a random-effects model. Results indicate a strong positive effect on academic achievement (d = 0.80, 95% CI [0.68, 0.91]) and a moderate positive effect on motivation (d = 0.64, 95% CI [0.46, 0.82]). Significant heterogeneity was observed among the included studies. Moderator analyses revealed that achievement outcomes varied by subject domain and intervention duration, while motivation outcomes were influenced by educational level and AI tool type. These variations highlight the role of instructional and contextual factors. Overall, the findings suggest that the effectiveness of AI depends on its pedagogical design and implementation, providing important implications for the development and integration of AIsupported learning environments.