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Frontiers in Psychology· Huijuan Qin·· 3 小时前AI 评分24

Frontiers in Psychology 研究:AI 辅助学习中的成就情绪、学业自我效能感与学习投入及 AI 依赖的有调节中介分析

Achievement emotions in AI-assisted learning, academic self-efficacy, and learning engagement and AI dependence among university students in statistics-related programs: a moderated mediation study

AI 导读

一项针对石家庄三所高校 700 名应用统计相关专业本科生的横断面调查发现,AI 辅助学习中的积极成就情绪通过学业自我效能感同时关联更强的学习投入(β=.395)和更低的 AI 依赖(β=-.176),AI 素养调节了情绪—效能感路径(β=.152)。但积极情绪对 AI 依赖的直接关联为正(β=.447),总关联在各素养水平下仍为正,属不一致中介而非保护作用。

正文

ORIGINAL RESEARCH article

Front. Psychol.

Sec. Educational Psychology

  • 1. Hebei Open University, Shijiazhuang, China

  • 2. Hebei University of Economics and Business, Shijiazhuang, China

Abstract

Background: Generative artificial intelligence (AI) tools have become part of everyday coursework for university students, yet the emotional and motivational conditions under which these tools support or undermine learning remain poorly understood. Drawing on the control-value theory of achievement emotions, this study examined whether academic self-efficacy mediates the links of positive achievement emotions in AI-assisted learning with learning engagement and AI dependence, and whether AI literacy moderates the first stage of these pathways. Methods: A cross-sectional survey was conducted with 700 undergraduate students (386 female; M_age = 19.81 years, SD = 1.27) majoring in applied statistics and related programs at three universities in Shijiazhuang, China. Participants completed measures of positive and negative achievement emotions, academic self-efficacy, learning engagement, AI dependence, and AI literacy. Confirmatory factor analysis preceded a first-stage moderated mediation analysis with bias-corrected bootstrap confidence intervals (5,000 resamples), controlling for negative emotions, gender, and year of study. Results: The six-factor measurement model fitted the data well, χ²(50) = 55.62, p = .271, CFI = .998, RMSEA = .013, SRMR = .017. Positive achievement emotions predicted higher self-efficacy (β = .374), which in turn predicted stronger engagement (β = .395) and lower AI dependence (β = -.176), all p < .001, with AI literacy entered in every equation. AI literacy moderated the emotion-efficacy association (β = .152, p < .001): the conditional indirect association with engagement rose from .088 to .208 across ±1 SD of AI literacy, and that with AI dependence fell from -.039 to -.093. The direct association with AI dependence was positive (β = .447, p < .001), and the conditional total association remained positive (.355 to .408). Both indexes of moderated mediation were significant. Conclusion: Positive emotional experiences in AI-assisted coursework show beneficial and costly associations simultaneously, and self-efficacy statistically accounts for opposing parts of each. The total association with dependence remained positive at all literacy levels, so the results describe inconsistent mediation rather than protection. AI literacy marks where the emotion-engagement pathway is strongest.

Keywords

Academic self-efficacy, achievement emotions, AI Dependence, AI literacy, higher education, Learning engagement, moderated mediation

Received

10 September 2026

Accepted

25 September 2026

Copyright

© 2026 Qin and Liu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence:

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来源:Frontiers in Psychology · frontiersin.org

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