Evaluating Creative Methods in AIGC-Assisted Fashion Design Sketch Generation: Mind Mapping, Brainstorming, and SCAMPER

초록

Featured Application: This study provides practical guidance for integrating structured creative thinking methods with AIGC tools in fashion design workflows. The findings can be applied in design education to improve students’ ideation efficiency and originality, as well as in the fashion industry to optimize early-stage sketch generation and concept development. In particular, the results support the use of brainstorming for rapid idea expansion, mind mapping for structured refinement, and SCAMPER for concept variation, offering a systematic human–AI collaborative framework for enhancing creative design processes. This study examines the impact of three creative thinking methods—mind mapping, brainstorming and SCAMPER—on the generation of fashion sketches using artificial intelligence-generated content (AIGC). While AIGC is becoming more prevalent in design practice, little research has examined how various ideation strategies influence the quality and originality of AI-generated results. For this study, ten professional designers created prompts using each method and generated fashion sketches via an AIGC platform. A total of 204 valid responses to the evaluation were collected, assessing the outputs across five dimensions: design support capability, quality, originality, detail refinement, and market acceptability. The results show that brainstorming most effectively enhances design quality and visual detail, while mind mapping yields the highest market acceptability. SCAMPER stimulates originality but performs less favorably in terms of refinement and visual coherence. These findings demonstrate that creative thinking methods significantly influence AIGC-assisted design and highlight the importance of aligning ideation strategies with the cognitive preferences and task objectives of designers. Despite limitations relating to the relatively small sample size of participating designers and reliance on a single AIGC platform, this study is the first to provide a systematic comparison of these three creative thinking methods within the context of AIGC-assisted fashion design. The findings offer new insights into the integration of structured creative thinking with AIGC tools in both design education and professional practice, while future research is encouraged to expand the diversity of participants, design tasks, and generative systems. © 2026 by the authors.

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