Generative AI an academic equalizer? The differential impact of AI-assisted learning on self-efficacy and intrinsic motivation among university students

Generative AI tools have become more common in universities, but studies on the psychology of such use for all students remain insufficiently researched at this time point. This study investigated whether AI-assisted Learning (AIL) is associated with college Students’ intrinsic motivation and Self-efficacy, and if these relationships vary based on Academic performance. A 2 × 2 quasi-experimental design was employed with 200 STEM undergraduates, who were classified into high- and low-achievement groups and assigned to either a DeepSeek-assisted writing condition or a traditional-support writing condition. Intrinsic Motivation and Self-efficacy of Participants after completing the Scientific Paper. The data were analysed by CFA, ANOVA/ANCOVA, mediation analysis and moderated-mediation analysis. The results indicated that the post-tasks’ intrinsic motivation and self-efficacy of students under an AI-accompanied tutoring were much higher than those without it. Further analysis revealed a more pronounced impact of the Group Differences on lower achievers compared to higher ones. Also, intrinsic motivation partly explained why a Writing Support Type was associated with self-efficacy. According to the results, generative AI has equitising characteristics in higher education and provides more robust emotional assistance for weaker learners of initial knowledge.