The Hidden Cost of AI-Supported Learning Collaboration: How It Undermines Self-Efficacy and Amplifies Anxiety in Unaided Tasks

Abstract

This study examines the relationship between Artificial Intelligence (AI)-supported learning collaboration and students’ experiences in unaided contexts, clarifying the underlying psychological mechanism. A survey was conducted with students from two comprehensive universities in central China (n = 212). The extent of AI participation in learning was measured, with reduced learning self-efficacy modeled as a mediating variable. Data analysis employed Partial Least Squares Structural Equation Modeling (PLS-SEM) using SmartPLS 4.0. Findings reveal that greater AI participation correlates with lower learning self-efficacy, which subsequently relates to heightened anxiety in both unaided reading and writing contexts. The mediation analysis suggests that shifts in self-appraisal constitute a key pathway linking AI participation to domain-specific anxieties. This study extends self-efficacy theory to contexts involving learner-AI collaboration and differentiates reading anxiety from writing anxiety as distinct constructs. Implications suggest that instruction should integrate supported phases with AI-free tasks and ensure learners’ contributions remain visible to maintain mastery experiences and preserve confidence.

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