This study explores the use of Midjourney (V6) by fashion design undergraduates for AI-supported ideation, focusing on how outcomes differ based on fashion-domain competence and prompt/parameter instruction. A focused ethnographic, comparative case-study design was used to observe a short collection-development module. Data included Discord prompt and parameter logs, generated image outputs (mood boards, look proposals, and pattern drafts), one-on-one interviews, classroom observation notes, and expert co-coding and qualitative evaluation. Participants were organized into four groups by crossing Basic vs. Advanced Fashion competence (BF/AF) with Basic vs. Advanced Prompt training (BP/AP): BF-BP, AF-BP, BF-AP, and AF-AP. BF-BP depended on repetitive/imaginary use and generic descriptors, resulting in visually appealing yet conceptually fragmented and low-feasibility results. AF-BP leveraged a richer domain vocabulary to improve item-level adequacy but struggled to maintain collection-level consistency, leading to the use of external editing tools such as Photoshop and Illustrator for portfolio-level refinement. BF-AP quickly mastered commands and parameters (e.g., /describe, --chaos, --stylize, --ar, --tile, --no, --sref, --cref), generating appealing concept imagery while failing to convert outputs into wearable garments and cohesive collections. AF-AP combined advanced fashion knowledge with strategic parameter sequencing— broad exploration, followed by consistency control and selective refinement—achieving the most coherent, feasible outcomes and positioning AI as an early-stage accelerator rather than a substitute for core design and making skills. Overall, this study proposes “parameter literacy” as a domain-specific extension of GenAI literacy and offers a parameter–process mapping (divergent generation, consistency control, and editing/refinement) to enhance fashion curricula.

Abstract
Ⅰ. Introduction
Ⅱ. Theoretical Background
    1. Creativity in design and educational uses ofgenerative AI
    2. Midjourney prompt and parameter system
Ⅲ. Research Methodology
    1. Research participants and scope
    2. Data collection and analysis procedures
Ⅳ. Results
    1. Group-based findings: four types of studentsin AI-supported ideation
    2. Parameter–process mapping and educationalimplications
Ⅴ. Conclusion
References

• Koh Woon Kim(Assistant Professor, Dept. of Fashion Design, Duksung Women’s University, Korea) | 김고운 (덕성여자대학교 의상디자인전공 조교수) Corresponding author