Effect of GenAI Dependency on University Students’ Academic Achievement: The Mediating Role of Self-Efficacy and Moderating Role of Perceived Teacher Caring
Wenxiu Jia, Li Pan, Siobhan Neary
Abstract
Generative artificial intelligence (GenAI) holds significant potential to enhance university students' learning. However, over-reliance on it to complete academic tasks poses a risk to academic achievement by potentially encouraging cognitive outsourcing. Despite this growing concern and an expanding body of research on GenAI usage, the mechanisms through which GenAI dependency and perceived teacher caring affect their academic achievement and self-efficacy remain underexplored. Based on the theory of media system dependence, this study explores the mechanisms through which university students' dependency on GenAI affects their academic outcomes, focusing on the mediating role of self-efficacy and moderating role of perceived teacher caring. A survey was conducted with 418 university students from Chinese public universities who had used GenAI for an extended period. The results revealed that GenAI dependency positively predicts false self-efficacy and negatively predicts academic achievement, exhibiting a significant Dunning-Kruger effect. Perceived teacher caring moderates the relationship between GenAI dependency and self-efficacy. High perceived teacher caring mitigates the Dunning-Kruger effect but has a weak moderating effect on academic achievement. These findings enhance the explanatory power of the media system dependency theory in educational contexts and reveal the pathways through which GenAI dependency and teacher caring affect learning processes and outcomes. This study expands the theoretical implications of teacher caring in the digital age and provides empirical evidence to aid higher education administrators in optimising AI governance and teachers in improving instructional interventions.