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Cited by 104Creativity in Education and NeuroscienceArtificial Intelligence in EducationDesign Education and Practice

The DOI matches its Crossref record; 71 of the 77 references it cites were found in a registry or an index, and 6 are not checked yet.

The influence of generative artificial intelligence on creative cognition of design students: a chain mediation model of self-efficacy and anxiety

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Hwang, Younjung, Wu, Yi·2025·Frontiers in Psychology
DOI 10.3389/fpsyg.2024.1455015PMC PMC11808137
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Abstract

Introduction: This study investigated the role of generative Artificial Intelligence (AI) in enhancing the creative cognition of design students, examining the mediating effects of self-efficacy and anxiety reduction. Methods: A quantitative approach was employed, collecting data through online surveys from 121 design students at universities in southern China. The study utilized scales for AI knowledge and perception, self-efficacy, anxiety, and creative cognition, adapted from previous studies and evaluated on 5-point Likert scales. Data analysis was conducted using SPSS 24.0 for exploratory factor analysis and PROCESS v3.5 for mediation analysis. Results: The findings confirmed that AI positively impacted students’ innovative thinking (* β * = 0.610, * p * < 0.001). Self-efficacy (standardized * β * = 0.256, 95% CI [0.140, 0.418], * p * < 0.001) and anxiety reduction (standardized * β * = 0.093, 95% CI [0.018, 0.195], * p * < 0.05) positively mediated the relationship between generative AI and creative cognition. Additionally, a serial mediation effect through self-efficacy and anxiety reduction was observed (standardized * β * = 0.053, 95% CI [0.012, 0.114], * p * < 0.05). Discussion: Our empirical analysis demonstrates that AI positively affects design students’ innovative thinking, with self-efficacy and anxiety reduction serving as significant mediators. These findings provide valuable insights for educators and policymakers, suggesting that AI-integrated design curricula can significantly foster creative cognition, promote academic achievement, and enhance designer capabilities. Understanding AI’s impact on students’ creative processes is crucial for developing effective teaching strategies in today’s evolving educational landscape.

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Research works printed but not linked: 3

  1. Kim, 2022, The artificial intelligence literacy scale for middle school students, J. Korea Soc. Comput. Inf., 27, 225, 10.9708/jksci.2022.27.03.225 · DOI
  2. Maddux, 2013, Self-efficacy, adaptation, and adjustment: Theory, research, and application
  3. Wang, 2021, Analysis and research on students' anxiety symptoms in art design teaching, Psychiatr. Danub., 33, 376

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Metadata

Authors
Hwang, Y., & Wu, Y.
Affiliations
  • Hunan University (CN)
  • Hainan University (CN)
Corresponding author
Wu, Yi
ORCID
Venue
Frontiers in Psychology
Publisher
Frontiers Media SA
Published
2025-01-27
Volume
15
Pages
1455015-1455015
ISSN
1664-1078 (ISSN-L)
DOI
10.3389/fpsyg.2024.1455015
PMC
PMC11808137
OpenAlex
W4406850244
Cited by
104
References
72
Citations by year
2026: 77 · 2025: 27
FWCI
108.93
Type
journal article
Language
en
Open access
Licence
Locations
  • Frontiers in Psychology (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Creativity in Education and Neuroscience
  • Social Sciences › Education › Artificial Intelligence in Education
  • Physical Sciences › Engineering › Mechanical Engineering › Design Education and Practice
Keywords
generative AI, creative cognition, design students, self-efficacy, anxiety, innovative thinking, serial mediation, design education

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