Methodology for the application of generative artificial intelligence tools in higher design education

Abstract

The rapid development of Generative Artificial Intelligence (GAI) technologies across both theoretical and practical domains is fundamentally transforming the epistemological and pedagogical foundations of higher design education. This study provides a comprehensive analysis of the methodological integration of generative AI tools, including ChatGPT, Claude, Midjourney, and DALL·E, in fostering creative thinking, critical analysis, and practical skills among design students in higher education institutions. The research examines the transition of studio pedagogy from traditional forms toward hybrid and dialogical models, the reinterpretation of Donald Schön’s concept of reflection-in-action within algorithmic environments, and the evolving role of the educator in AI-assisted learning processes. Methodologically, the study is grounded in a modified Technological Pedagogical Content Knowledge (TPACK) framework and a four-component Information and Communication Competence (ICC) model. The findings indicate that the systematic and purposeful implementation of GAI tools can increase students’ visual design production and productivity by approximately 14%; however, it may also lead to reduced diversity of ideas and an overreliance on algorithms for cognitive functions. To mitigate these risks, the study proposes the concepts of epistemic vigilance and process-oriented hybrid assessment mechanisms as essential components of contemporary design education.