This study explores how to integrate the generative artificial intelligence (AI) tool Midjourney into the fashion design process, emphasizing the visualization of sporty fashion concepts. The research applied Midjourney at every stage of the fashion design process: mood board, fashion sketch, flat drawing, production package, fashion show presentation, and store display and sales. Specifically, sporty fashion was selected as the theme, and customized prompts were developed from prior research and design principles to generate visual outputs for each stage. Furthermore, three apparel design experts evaluated the AI-generated images to assess Midjourney’s practical applicability and effectiveness in each phase of the fashion design workflow. Expert evaluations revealed that Midjourney was particularly effective in the early stages, offering diverse and visually engaging imagery that supported creative ideation and mood expression. The tool allowed quick exploration of different silhouettes during the sketching stage but was imprecise in detailed forms and proportions. Limitations became more evident in the flat drawing and work instruction stages, where outputs failed to accurately reflect material textures and technical construction. Prompt refinements and referencebased prompts were tested but often resulted in inconsistent or stylized outputs. Additionally, continuity between stages was missing. Midjourney shows potential as a creative tool, but experts highlight its limitations for practical industry application. Further research is needed to improve prompt optimization and training data for enhanced accuracy and usability in AI-assisted fashion design workflows.

This study aimed to explore the impact of AI image generators on the affective factors of college-level English learners and the correlations among these factors. During a four-week instructional period, 65 participants were asked to use Midjourney as an AI tool for their user experiences. Affective factors including interest, confidence, and participation were measured through pre- and post-surveys. Using Jamovi for analysis, significant improvements were discovered across all affective factors. Noteworthy improvements occurred in confidence, indicating a favorable impact by AI-generated images on English learning. Additionally, correlation analysis demonstrated significant positive relationships between interest and confidence, as well as confidence and participation. This confirms the interconnected nature of these affective elements in the learning process. The findings suggest that the educational use of image-generating AI tools can beneficially influence English learners’ affective domains. The study calls for further investigation into the pedagogical applications of image AI to foster a more interactive, engaged, and self-assured attitude towards language learning.