“I’m Not as Good as AI”: The Impact of Generative AI Use on Learning Anxiety and Self-Efficacy
Year: 2026
Type: article
Abstract: This study investigates whether metacognitive prompting for responsible generative AI (GenAI) use can enhance students’ psychological sustainability in AI-assisted learning. Using a face-to-face classroom experiment (N = 148; 74 prompting, 74 control), we examined how metacognitive prompts embedded in a GenAI-assisted academic task influence learning anxiety and academic self-efficacy, and whether anxiety mediates the effect on self-efficacy. Manipulation checks indicated that the prompting condition produced significantly higher metacognitive engagement than the control condition (t(146) = 7.50, p < 0.001, d = 1.23). Hypothesis tests showed that metacognitive prompting reduced learning anxiety (b = −0.68, p < 0.001) and increased academic self-efficacy (b = 0.40, p = 0.008). Learning anxiety was negatively associated with self-efficacy (b = −0.42, p < 0.001). Mediation analyses using bootstrap confidence intervals revealed a significant indirect effect of prompting on self-efficacy via reduced anxiety (ab = 0.26, 95% CI [0.12, 0.43]), indicating partial mediation. These findings suggest that responsible GenAI use can be supported through instructional design. Brief metacognitive prompts may help students regulate AI use, reduce learning anxiety, and maintain academic self-efficacy. More broadly, the study contributes to sustainable education and educational technology research by showing that classroom scaffolds can support student agency and well-being in AI-assisted learning.
Source: Sustainability
DOI: 10.3390/su18083869
Authors: Tao Jiang, Yan Xu
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: gold
Estimated APC paid: $2,896
OpenAlex ID: W7154356168