From Appropriate Use to Dependence: How AI Attitudes and Use Motivations Shape University Students’ AI Dependence

Whether students develop dependence on generative artificial intelligence (AI) technologies largely depends on their attitudes toward using such tools. Existing studies have primarily explained the formation of AI dependence from the perspectives of usage attitudes and technological characteristics, while paying limited attention to the psychological mechanisms through which attitudes exert their influence. Grounded in Self-Determination Theory, the present study examines how different types of use motivation mediate the relationship between students’ AI attitudes and AI dependence. A total of 405 university students completed a comprehensive questionnaire measuring AI attitudes, use motivations, and AI dependence. The results indicate that: (i) AI attitudes do not directly predict AI dependence; instead, their effects are transmitted through multiple motivational pathways, with intrinsic motivation inhibiting AI dependence, whereas identified regulation facilitates its development; (ii) three distinct AI dependence profiles were identified: dependent, moderate, and conservative users. These profiles exhibited clear stratification, with dependent users showing the highest scores across all dimensions and conservative users the lowest; and (iii) individuals with stronger motivations are more likely to be classified into the dependent user profile, with external motivation playing a particularly salient role. These findings enrich the literature on AI technology dependence and offer practical implications for higher education administrators, tool developers, and educational researchers.