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

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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