Empowering students through generative AI and cultural diversity in interdisciplinary fashion design education

Purpose This study aims to examine how integrating cultural diversity and generative AI into coursework can enhance students’ creativity, critical thinking and innovation, enabling them to design culturally aware products for the global market. Design/methodology/approach Grounded in Stanford’s design thinking framework, the proposed course designs were developed to incorporate a range of cutting-edge artificial intelligence (AI) tools. A portion of the curriculum was pilot-tested in actual college courses with 52 students to assess its effectiveness in achieving the intended learning outcomes. Findings Integrating generative AI and cultural diversity in a fashion design course enhanced students’ creativity, critical thinking, cultural awareness and teamwork. AI tools simplified research and design tasks for those with fewer technical skills, allowing them to focus on innovation, whereas cultural diversity fostered collaboration and the exchange of ideas for global markets. This approach could also apply to Science, Technology, Engineering, and Mathematics (STEM) fields like engineering, where AI supports coding and design to improve learning and develop globally relevant solutions. This study had some limits. It used a small group of students from one school, so the results may not fit all. Some AI tools produced errors or were difficult to use, highlighting the need for clarity about AI’s limitations and careful attention to cultural appropriateness in generated results. Future studies should have more students, better AI tools and focus on fair use. Originality/value This research integrates generative AI with cultural diversity in a fashion design course to develop product design and development skills for the global market – a combination rarely examined in existing studies. It demonstrates how AI can empower students from diverse backgrounds to collaborate creatively while honoring cultural authenticity.

Authors

Institutions

Publication Details

Journal
Research Journal of Textile and Apparel
Published
2025-09-26
DOI
https://doi.org/10.1108/rjta-02-2025-0017
Primary Topic
Crafts, Textile, and Design
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Empowering students through generative AI and cultural diversity in interdisciplinary fashion design education

Jennifer Lee
Research Journal of Textile and Apparel
Crafts, Textile, and Design
article

Empowering students through generative AI and cultural diversity in interdisciplinary fashion design education

Jennifer Lee
article en

Abstract

Purpose This study aims to examine how integrating cultural diversity and generative AI into coursework can enhance students’ creativity, critical thinking and innovation, enabling them to design culturally aware products for the global market. Design/methodology/approach Grounded in Stanford’s design thinking framework, the proposed course designs were developed to incorporate a range of cutting-edge artificial intelligence (AI) tools. A portion of the curriculum was pilot-tested in actual college courses with 52 students to assess its effectiveness in achieving the intended learning outcomes. Findings Integrating generative AI and cultural diversity in a fashion design course enhanced students’ creativity, critical thinking, cultural awareness and teamwork. AI tools simplified research and design tasks for those with fewer technical skills, allowing them to focus on innovation, whereas cultural diversity fostered collaboration and the exchange of ideas for global markets. This approach could also apply to Science, Technology, Engineering, and Mathematics (STEM) fields like engineering, where AI supports coding and design to improve learning and develop globally relevant solutions. This study had some limits. It used a small group of students from one school, so the results may not fit all. Some AI tools produced errors or were difficult to use, highlighting the need for clarity about AI’s limitations and careful attention to cultural appropriateness in generated results. Future studies should have more students, better AI tools and focus on fair use. Originality/value This research integrates generative AI with cultural diversity in a fashion design course to develop product design and development skills for the global market – a combination rarely examined in existing studies. It demonstrates how AI can empower students from diverse backgrounds to collaborate creatively while honoring cultural authenticity.

Research Journal of Textile and Apparel
Fashion Institute of Technology (US)
Openalex Percentile: Top 75%
Crafts, Textile, and Design
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.