When Trust Becomes Substitution: Generative-AI Trust, Over-Reliance, and Learner Autonomy Among University Students
Keywords:
generative AI, trust calibration, over-reliance, learner autonomy, higher education, response surface analysis, latent class analysisAbstract
Generative artificial intelligence (GenAI) has become a routine study companion for university students, yet the conditions under which trust in these tools turns into over-reliance that erodes learner autonomy remain poorly specified. This study models trust, over-reliance, and learner autonomy jointly with the 2025 Stack Overflow Developer Survey, analysing 1,308 university students from 102 countries and a contrast group of 9,860 professional developers. Over-reliance is operationalized through task-level delegation that separates substitution (core learning tasks done mostly by AI) from augmentation (tasks done partially with AI), and learner autonomy is measured through four facets: problem-solving confidence, comprehension ownership, epistemic agency, and self-directed resource diversity. Trust predicted substitution but not augmentation. Polynomial regression with response surface analysis showed that substitution was higher when trust exceeded students' own appraisal of AI capability than in the reverse configuration (a3 = 0.146, p = .005), establishing calibration rather than trust level alone as a driver of over-reliance. Trust and substitution both predicted lower epistemic agency, and causal mediation analysis confirmed a significant indirect path (ACME = −0.034, 95% CI [−0.061, −0.012]). Students and professionals reported identical trust, yet students reported problem-solving confidence loss at nearly twice the professional rate (43.8% vs. 23.0%), a gap unchanged after reweighting professionals to the students' reliance profile. Latent class analysis identified four reliance profiles, among which dependent delegators (15.9%) showed the weakest epistemic agency. The findings position trust calibration and reliance mode as actionable levers for autonomy-preserving GenAI integration in higher education.
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