Abstract
In recent years, the rapid development of AI technology and application tools has made it obvious that design education can be applied to generative AI applications, and many image-generating AI tools are now available at different levels of technology. The theme of this study is to explore the design of visual interfaces for image-generating AI aids in a technology acceptance model - a research evaluation using the Stable Diffusion Online and Uizard platforms. There were 39 students from the Department of Design, and four experimental tasks were performed. This study used the technology acceptance model, which consists of a three-dimensional questionnaire survey on sensory usefulness, sensory ease of use, and attitudes towards use. The data analysis of the collected questionnaires will use reliability analysis, narrative statistics, ANOVA analysis, correlation analysis, and linear regression analysis, etc., and the SPSS software will be used to carry out various statistical analyses and validate the results. After the statistical analyses and validation results, the Stable Diffusion Online platform of the Artificial Intelligence for Image Generation (AI-IG) focuses on the creation of images and the style of painting. The image generation AI Uizard platform focuses on frame interface, layout editing, and function location interface. When Image Generation Artificial Intelligence is supplemented with User Experience Design methodology, it will help create a new Image Generation Artificial Intelligence collaboration model that will change the traditional visual interface design process and improve the efficiency, ease of learning, and professionalism in visual interface design. When introducing image generation AI tools in user experience and interface design, users and design students need to strengthen the semantic manipulation of cues, figurative or abstract graphic construction methods, which will be able to produce high-quality visual interface design works.
Keywords
Technology Acceptance Modelling; Generative Artificial Intelligence; Visual Interface
DOI
https://doi.org/10.21606/iasdr.2025.310
Citation
Chen, C.,and Feng, C.(2025) Exploring Image Generation Artificial Intelligence-Assisted Visual Interface Design with Technology Acceptance Model: The Case of Stable Diffusion Online and Uizard Platform, in Chang, C.-Y., and Hsu, Y. (eds.), IASDR 2025: Design Next, 02-05 December, Taiwan. https://doi.org/10.21606/iasdr.2025.310
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Conference Track
Track 12 - Design Education
Exploring Image Generation Artificial Intelligence-Assisted Visual Interface Design with Technology Acceptance Model: The Case of Stable Diffusion Online and Uizard Platform
In recent years, the rapid development of AI technology and application tools has made it obvious that design education can be applied to generative AI applications, and many image-generating AI tools are now available at different levels of technology. The theme of this study is to explore the design of visual interfaces for image-generating AI aids in a technology acceptance model - a research evaluation using the Stable Diffusion Online and Uizard platforms. There were 39 students from the Department of Design, and four experimental tasks were performed. This study used the technology acceptance model, which consists of a three-dimensional questionnaire survey on sensory usefulness, sensory ease of use, and attitudes towards use. The data analysis of the collected questionnaires will use reliability analysis, narrative statistics, ANOVA analysis, correlation analysis, and linear regression analysis, etc., and the SPSS software will be used to carry out various statistical analyses and validate the results. After the statistical analyses and validation results, the Stable Diffusion Online platform of the Artificial Intelligence for Image Generation (AI-IG) focuses on the creation of images and the style of painting. The image generation AI Uizard platform focuses on frame interface, layout editing, and function location interface. When Image Generation Artificial Intelligence is supplemented with User Experience Design methodology, it will help create a new Image Generation Artificial Intelligence collaboration model that will change the traditional visual interface design process and improve the efficiency, ease of learning, and professionalism in visual interface design. When introducing image generation AI tools in user experience and interface design, users and design students need to strengthen the semantic manipulation of cues, figurative or abstract graphic construction methods, which will be able to produce high-quality visual interface design works.