Recent advances in generative AI (GenAI) technologies have reshaped student learning in higher education. However, most studies treat AI usage as a generalized construct, overlooking differences across various disciplines, educational levels, and regions. This gap is particularly relevant in China, where regional disparities in access and readiness may influence student engagement with AI tools. This study examines how university students in China perceive, utilize, and are influenced by generative AI tools across various disciplines and regions, while also assessing the accuracy and disciplinary relevance of AI-generated responses in professional coursework. The study includes four mixed-methods investigations: a national survey of students’ AI usage patterns and attitudes; an evaluation of ChatGPT’s responses to subject-specific questions based on semantic similarity and expert scoring; behavioral clustering and analysis of one-month AI usage logs to identify distinct user profiles; and an exploration of AI tools’ impact on academic performance and long-term outcomes. Findings show significant variation in AI engagement across disciplines and regions. Students in economically developed areas report higher usage and broader application, while those in central and western regions have more limited access. Students’ academic performance can be improved to varying degrees through AI-driven learning, with engineering and natural sciences students primarily using AI for technical tasks, while humanities and arts students employ it for linguistic and creative support. Evaluation of ChatGPT’s responses reveals moderate accuracy, with disciplinary variations. Despite generally positive attitudes, both students and experts express concerns about content reliability, over-reliance on AI, and its potential to hinder independent thinking and creativity.
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