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January 22, 2026Fashion and Textiles7 citationsOpen Access

AI tools and fashion design education: instructor perspectives on student challenges and design process tool support

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HAHyosun AnPai Chai UniversityMPMinjung ParkMetropolitan State University

Key Points

  • The study aims to investigate how AI tools can support fashion design education by identifying student challenges and the instructional role of these tools.
  • Conducted semi-structured interviews with 10 university instructors from South Korea and the United States.
  • Employed thematic analysis to understand educational roles of AI in the design process.
  • Examined four stages of the design process: problem definition, ideation, prototype development, and evaluation.
  • Identified four primary challenges faced by students: design planning, ideation, garment construction, and feedback adaptation.
  • Outlined how various AI tools enhance visualization, creative thinking, and student engagement.
  • Developed a pedagogical framework for integrating AI tools into fashion design education.

Abstract

Abstract Despite growing interest in artificial intelligence (AI) in higher education, research on its pedagogical integration in fashion design education remains limited, with most studies focusing on the technical aspects of AI tools rather than their instructional roles or educational implications. This study explores how AI tools can be effectively integrated into fashion design education by examining student challenges, AI-supported learning competencies, and instructional considerations from the perspectives of instructors. Semi-structured interviews were conducted with 10 university-level instructors from South Korea and the United States who have experience teaching fashion design-related courses. Thematic analysis is employed to examine the educational roles of AI in supporting students across the various design process stages. Findings identify four primary areas where students commonly face difficulties: initial design planning, ideation and creative exploration, technical garment construction, and communication and feedback adaptation. This study presents a pedagogical framework that illustrates how AI tools, including large language models, image generators, simulations, and feedback systems, can enhance visualization, creative thinking, and student engagement. This framework aligns student challenges, AI tool functionalities, and instructional strategies across four stages of the design process—problem definition, ideation and refinement, prototype development, and evaluation—offering practical guidance for the intentional integration of AI in fashion design education that promotes learner autonomy and human–AI collaboration.

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Cite This Study

An et al. (2026) studied this question.

synapsesocial.com/papers/6971bd6a642b1836717e2179https://doi.org/10.1186/s40691-025-00452-9
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