ArticleFrontiers in psychology2026
The impact of artificial intelligence perception on university students' academic engagement: the mediating role of academic motivation and the moderating role of academic self-efficacy.
Article in Frontiers in psychology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- The psychological mechanisms and behavioral determinants of academic integrity in the age of artificial intelligence.Frontiers in psychology · 2026Article
- Family-school autonomy support for children's responsible use of generative artificial intelligence: a self-determination theory synthesis and developmental research agenda.Frontiers in psychology · 2026Review
- Artificial intelligence anxiety and academic burnout among Chinese postgraduate students: perceived stress and rumination as serial mediators.Frontiers in psychology · 2026Article
- The relationship between college students' AI technology dependence and learning burnout: a chain mediation analysis of technology acceptance and AI self-efficacy.Frontiers in psychology · 2026Article
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Authors and funding
7 authors.
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Abstract
Objective: To test whether academic motivation mediates the association between artificial intelligence (AI) perception and university students' academic engagement, and whether academic self-efficacy moderates the direct and indirect associations. Design: Cross-sectional, single-wave, self-administered questionnaire survey; all variables were assessed once at a single time point in a convenience sample of university students in Anhui, China. Method: A convenience sample of 1,484 university students in Anhui Province completed an anonymous questionnaire measuring AI perception, academic engagement, academic motivation, and academic self-efficacy. Descriptive statistics, correlations, and regression-based mediation and moderated mediation analyses were conducted. Results: AI-related perceptions were negatively associated with academic engagement, and academic motivation partially mediated this association. Academic self-efficacy moderated both the direct association and the indirect pathway via motivation: when self-efficacy was lower, the negative association between AI-related perceptions and engagement was stronger and the motivation-engagement association was weaker; when self-efficacy was higher, the opposite pattern emerged, and the indirect effect via motivation was stronger. Conclusion: AI-related perceptions were inversely associated with academic engagement partly through academic motivation, and these associations varied by academic self-efficacy. Given the cross-sectional, self-report design, the findings are correlational and require longitudinal or experimental verification.
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