Integrating AI-Based Moodboard in Fashion TVET Curriculum: A Pilot Study in Digital Ideation Skills
Keywords:
AI-Assisted Design, Moodboard Generation, Digital Ideation Skills, Fashion Education, Technical and Vocational Education (TVET), Generative AI, Curriculum Innovation, Human-AI Co-CreationAbstract
The potential for artificial intelligence (AI) in new learning paradigms has developed exponentially, promising revolutionary opportunities in fashion design education. The paper discusses the application of AI-driven moodboard software in the Malaysian Technical and Vocational Education and Training (TVET) curriculum with special emphasis on the development of fashion design students' digital ideation skills. Based on a comprehensive five-year literature review and framed within an action research paradigm, this research suggests piloting an intervention at Arau Community College, integrating generative AI with semantic image filtering technologies within a fashion ideation module. The article presents a mixed-methods approach involving text-to-image generation, digital curation tools, and semantic labelling systems for enhancing student creativity, enhancing ideation fluency, and fostering digital capabilities. Expected outcomes are increased visual expression, efficiency in design processes, and greater student participation. The research responds to teaching issues like excessive dependence on artificial intelligence, ethical issues, and the requirement for structured incorporation. The results of this initial research are intended to guide large-scale curricula changes that integrate traditional design sensibilities with emerging AI-led solutions, propelling fashion education to meet Industry 4.0 needs.
References
Ansone, A., Z?l?te-Supe, Z., & Daniela, L. (2025). Generative artificial intelligence as a catalyst for change in higher education art study programs. Computers, 14(4), 154.
Bonnardel, N., & Zenasni, F. (2010). The impact of technology on creativity in design. Creativity and Innovation Management, 19(2), 180–191.
Cassidy, T. (2011). Mood boards as a design tool: The influence of source imagery on new design. Journal of Fashion Marketing and Management, 15(3), 308–325.
Chipambwa, W., & Chikwanya, E. V. (2022). Design communication: Fashion design students’ perspectives on digital vs physical mood boards. GRID International Conference Proceedings.
Cross, N. (2006). Designerly ways of knowing. Springer.
Davis, M. (2021). Teaching digital visual literacy through AI tools. Design Education Review, 14(1), 56–72.
Feldner-Busztin, E. (2024). Is fashion education ready for AI? The Interline.
Hassan, R. (2024, October 13). Align TVET with AI. The Star (Education).
Hodgson, A., & Spours, K. (2018). Vocational education and training for future-ready skills. TVET Journal, 6(1), 10–29.
Jin, Y., Yoon, J., Self, J., & Lee, K. (2024). Understanding fashion designers’ behavior using generative AI for early-stage concept ideation and revision. Archives of Design Research, 37(3), 25–45.
Jouffroy, J. (2021). Fashion design in the age of AI. Journal of Creative Technologies, 9(2), 45–61.
Kimbell, L. (2011). Rethinking design thinking: Part I. Design and Culture, 3(3), 285–306.
Koch, J., Taffin, N., Lucero, A., & Mackay, W. E. (2020). SemanticCollage: Enriching digital mood board design with semantic labels. In Proceedings of DIS ’20 (pp. 815–828). ACM.
Lee, J. (2024). AI technology integrated education model for empowering fashion design ideation. Sustainability, 16(17), 7262. (Time Mikkonen, J. (2023). Advent of GAN — How does a generative AI create a moodboard? Nordes 2023: Nordic Design Research Conference.
Loveless, A. (2007). Creativity, technology and learning–a review of recent literature. Futurelab Series Report.
McCormack, J., Gifford, T., & Hutchings, P. (2019). Autonomy, Authenticity, Authorship and Intention in Computer Generated Art. In ICCC (pp. 144-151).
Nguyen, T., & Vo, D. (2023). Blended learning and AI for design education. Asian Education Studies, 5(1), 21–34.
Oxman, N. (2016). Age of Entanglement. Journal of Design and Science, 1(1).
Resnick, M., & Rosenbaum, E. (2013). Designing for tinkerability. In Design, make, play (pp. 163-181). Routledge.
Rizzi, G., & Bertola, P. (2025). Exploring the generative AI potential in the fashion design process. European Journal of Cultural Management and Policy, 15, 13875.
Sawhney, N., Balcom, D., & Smith, R. (2009). Authoring personal histories: Exploring the timeline as a framework for meaning making. In CHI (pp. 1–10).
Shneiderman, B. (2020). Human-centered artificial intelligence: Reliable, safe & trustworthy. International Journal of Human–Computer Interaction, 36(6), 495-504.
Trinidad, J. E. (2020). Ethical use of AI in design education. Educational Philosophy and Theory, 52(10), 987–999.
Zhou, J., & Chen, Y. (2022). Prompt engineering for generative AI. AI Education Journal, 3(4), 50–67.
