Applying Actor-Network Theory to Design Education Incorporating Generative AI
Year: 2026
Type: article
Abstract: In recent years, the use of generative artificial intelligence ( AI) in design education has attracted significant attention. However, few studies have comprehensively analyzed educational environments using generative AI by considering the various actors involved in classrooms, such as educators, students, and educational tools. In this study, we qualitatively analyze a graphic design class incorporating generative AI at a vocational college using Actor-Network Theory (ANT), aiming to model how networks were formed to transform novice design students’ perceptions of design, as well as to interpret the complex interactions between students and generative AI within the educational context. The formation of the network was divided into four phases (problematization, interessement, enrollment, and mobilization), each exploring the roles played by human and nonhuman actors such as ChatGPT, graphic design tools, lecture slides, and educators. Through modeling these influences, this study highlights the potential of ANT to comprehensively capture and interpret the complex interrelationships between humans and tools within design education.
Authors: Riku Okamoto, Yuki Aoki, Toru Nagao
Institution: Chiba Institute of Technology
Language: English
Subfield: Mechanical Engineering
Field: Engineering
Domain: Physical Sciences
SDG: Quality education
Open Access status: hybrid
OpenAlex ID: W7131379697
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