International Journal of
Information and Education Technology

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.

Keywords—learning-Artificial Intelligence (AI) collaboration, learning self-efficacy, unaided reading anxiety, unaided writing anxiety, AI-supported learning

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Cite: Jiaxin Feng and I. G. P. Sudiarta, "The Hidden Cost of AI-Supported Learning Collaboration: How It Undermines Self-Efficacy and Amplifies Anxiety in Unaided Tasks," International Journal of Information and Education Technology, vol. 16, no. 3, pp. 718-727, 2026.

Copyright © 2026 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).