This study investigated the visualization accuracy and educational applicability of generative artificial intelligence (AI) tools in fashion design education by comparing images generated from the same blouse sketch using GPT-based tools, LOOK AI, and Stable Diffusion under identical prompt conditions. Thirty-two professional fashion designers evaluated the generated outputs using a structured 10-item assessment scale, focusing on silhouette accuracy, detail representation, structural clarity, and overall visual completeness. Statistical differences among the tools were analyzed using one-way analysis of variance followed by post-hoc comparisons. The results revealed significant differences (p<.05) in key evaluation criteria: silhouette accuracy, detail implementation, structural interpretability, and overall completeness. LOOK AI excelled in representing structural elements such as seams, pleats, and pattern logic, indicating its strength in design-oriented applications and technical visualization tasks. In contrast, Stable Diffusion received higher ratings for overall visual balance and aesthetic coherence, despite showing relatively lower structural fidelity. GPT-based outputs received lower ratings for structural accuracy but were seen as valuable for promoting critical AI literacy via prompt-based exploration, iterative refinement, and reflective evaluation. These findings suggest that differences among AI tools should not be interpreted in terms of absolute superiority but as distinct educational affordances. Accordingly, this study proposes a three-axis instructional framework that integrates structure-oriented learning, creative visualization, and critical inquiry-based learning.

Abstract
I. Introduction
Ⅱ. Review of Literature
    1. The importance of structural accuracy infashion visualization and the reproduction limitationsof generative AI
    2. Visual literacy and the educational significanceof AI-Based tools
Ⅲ. Research Method
Ⅳ. Results
    1. Differences in visual representation characteristicsamong three AI Tools
    2. Implications
Ⅴ. Conclusion
References

• Sujin Lim(Lecturer, Department of Textiles Arts and Fashion Design, Hongik University, Korea) Corresponding author