生成式AI如何嵌入设计学习：一项14个教学日的密集纵向研究揭示AI使用与自我效能感的双向动态

ORIGINAL RESEARCH article

Front. Psychol.

Sec. Educational Psychology

Abstract

Generative AI is increasingly embedded in design education, yet little is known about how students' subsequent instructional day engagement with generative AI is dynamically associated with their learning-related capability beliefs. Drawing on self-efficacy theory, this study examined the reciprocal associations across successive instructional days between daily generative AI use in design learning and daily design-learning self-efficacy, and further investigated whether baseline hassles were associated with individual differences in these dynamics. A 14-instructional-day diary study was conducted with 260 Chinese undergraduate design students, yielding 3,558 observed person-day assessments out of 3,640 possible assessments. The data were analyzed using bivariate dynamic structural equation modeling within a Bayesian estimation framework. The results showed significant autoregressive effects for daily generative AI use (β = .198, 95% CrI [.154, .237]) and daily design-learning self-efficacy (β = .138, 95% CrI [.100, .175]). At the within-person level, higher-than-usual generative AI use on one instructional day positively predicted design-learning self-efficacy on the subsequent instructional day (β = .043, 95% CrI [.006, .077]), while higher-than-usual design-learning self-efficacy also positively predicted generative AI use on the subsequent instructional day (β = .059, 95% CrI [.023, .095]). At the between-person level, baseline hassles were associated with higher average generative AI use (β = .135), lower average design-learning self-efficacy (β = −.254), and a stronger cross-lagged association from generative AI use to subsequent self-efficacy (β = .458). Gender did not significantly predict the main random effects. These findings indicate a modest reciprocal subsequent instructional day association between generative AI use and design-learning self-efficacy and suggest that this relationship may be more pronounced among students experiencing greater baseline hassles.

Keywords

design learning, diary study, dynamic structural equation modeling, Generative AI, self-efficacy

Received

23 August 2026

Accepted

28 September 2026

Copyright

© 2026 Li, Yang and Bao. 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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