Students’ Generative AI Use in Studio-Based Design Education: Selective Use, Design Judgment, and Studio Context
TL;DR
Students’ selective and context-dependent AI use can be interpreted as boundary-setting around when and how AI participates in the design process, and value is suggested in a judgment-centered, process-based approach to AI pedagogy that emphasizes accountability and reflective decision-making.
Abstract
Generative artificial intelligence (AI) is rapidly reshaping studio-based design education, yet relatively little is known about how students decide when and how AI should support their design process. This study examined students’ use, adaptation, and perceptions of generative AI, with particular attention to task-specific use, contextual adaptation, and factors associated with AI-related decision-making. An online survey of 112 undergraduate and graduate design students combined structured questionnaire items with optional open-ended responses to examine AI use across studio tasks, project stages, and learning contexts. Students reported higher AI use for concept development, research, and written articulation than for visual refinement, technical documentation, and later stages of design development. Students also reported becoming more selective in their AI use as projects progressed, while instructor expectations, peer influence, and concern about negative judgment were associated with students’ AI-related decisions. Qualitative responses further highlighted authorship, learning, and professional responsibility as important considerations. Together, these findings suggest that students’ selective and context-dependent AI use can be interpreted as boundary-setting around when and how AI participates in the design process. Rather than viewing AI use simply as technology adoption, the findings suggest value in a judgment-centered, process-based approach to AI pedagogy that emphasizes accountability and reflective decision-making.