AI Insight
This study examined how different types of academic stress relate to AI dependence among 580 art students, finding that both challenge stressors (motivating pressures) and hindrance stressors (obstructive pressures) increase reliance on generative AI tools, but through different psychological mechanisms. Challenge stressors led to AI dependence primarily through reduced creative self-efficacy and increased positive experiences with AI, while hindrance stressors operated mainly through positive AI experiences. The research demonstrates that not all academic stress drives problematic AI use in the same way, suggesting the need for differentiated intervention strategies.
Why it matters
These findings provide evidence-based guidance for educators concerned about art students becoming overly dependent on AI tools. Understanding that challenge-related and hindrance-related stress lead to AI overreliance through distinct pathways enables institutions to develop targeted interventions, such as bolstering creative confidence for students facing challenging workloads versus addressing the appeal of AI experiences for those facing administrative obstacles.
Understand the Science
BackgroundDespite growing concerns about art students’ over-reliance on generative AI tools, existing research has largely treated academic stress as a uniform construct, overlooking the possibility that different types of stressors may drive AI dependence through distinct psychological pathways.MethodsBased on the Interaction of Person-Affect-Cognition-Execution (I-PACE) model, this study examines the relationships between Challenge-Hindrance stressors (CHS) and AI dependence among art students. It explores the mediating roles of creative self-efficacy and positive experiences. A questionnaire survey was conducted among 580 art students using the Challenge-Hindrance Stress Scale, the Creative Self-Efficacy Scale, the Positive Experiences Scale, and the AI Dependence Scale.ResultsPath analysis revealed that both challenge stressors (β = 0.245, p < 0.001) and hindrance stressors (β = 0.322, p < 0.001) were positively associated with AI dependence; challenge stressors were negatively associated with creative self-efficacy (β = −0.155, p = 0.003) and positively associated with positive experiences (β = 0.268, p < 0.001); the negative association between hindrance stressors and creative self-efficacy was significant (β = −0.107, p = 0.043). Mediation analysis indicated that creative self-efficacy played a significant mediating role only in the path involving challenge stressors (indirect effect = 0.023, 95% CI [0.007, 0.044]) and was not significant in the path involving hindrance stressors; positive experiences significantly served as a mediator in the relationships between both challenge stressors (indirect effect = 0.042, 95% CI [0.020, 0.068]) and hindrance stressors (indirect effect = 0.019, 95% CI [0.003, 0.039]) on AI dependence. The chain mediation effects did not reach significance in either path.ConclusionThe study found asymmetry in the dual pathways by which Challenge and Hindrance stressors relate to AI dependence. These findings extend the I-PACE model to the issue of AI dependence in arts education and provide empirical evidence and intervention insights for targeted prevention of problematic AI use.