Research on the educational application of generative artificial intelligence images in the design of semiotics learning models
Ming-Yu Hsiao, Simo Zhang · 2023
Generative Artificial Intelligence (AI) has emerged as a novel technology with profound implications for education and deep learning, particularly due to its advancements in image generation. This progress has had a disruptive impact on the design industry, where designers are increasingly embracing generative AI images as innovative tools and techniques to enhance design ideation and creative expression. Integrating generative AI images into design education has become an inevitable trend, as it guides students in developing a deeper understanding of design aesthetics. However, the current application of generative AI images in design education lacks innovative use grounded in design theory. Therefore, the incorporation of generative AI images within the framework of design theory becomes crucial to interpret and refine design processes and design thinking. This research aims to explore the application of generative AI images in design semiotics, utilizing design theory as its foundation. By integrating design processes and incorporating design case studies, the study seeks to analyze how generative AI images can be effectively applied in design semiotics. Ultimately, the research strives to establish a pedagogical approach for the application of generative AI image-based design semiotics.