Abstract
Generative AI (GenAI) is reshaping design education, leading to the emergence of new university policies and evolving student practices. This study offers a comparative review of 17 institutional policies and 38 empirical studies on design students’ engagement with GenAI. Using inductive analysis, we developed a synthesized set of themes that capture both regulatory guidance and practical usage. Our findings indicate that while institutional policies emphasize responsible use, general-purpose recommendations, and abstract competency aims, student practices are characterized by situated judgment, iterative workflows, and profession-oriented skill development. These contrasts point to areas where institutional frameworks may fall short in addressing the specific pedagogical and disciplinary realities of design education. By highlighting both alignments and emerging mismatches, this review provides a structured basis for improving policy-practice coherence and supporting more context-sensitive integration of GenAI into creative education.
Keywords
Generative AI; Design education; University policies; Student practices
DOI
https://doi.org/10.21606/iasdr.2025.900
Citation
Mao, L., Tang, Z., Qi, M., Ho, J.C., Bruyns, G., Lee, K.,and Zhou, Z.(2025) Investigating the Usage of Generative AI in Design Education: Bridging University Policies and Student Practices, in Chang, C.-Y., and Hsu, Y. (eds.), IASDR 2025: Design Next, 02-05 December, Taiwan. https://doi.org/10.21606/iasdr.2025.900
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Conference Track
Track 12 - Design Education
Investigating the Usage of Generative AI in Design Education: Bridging University Policies and Student Practices
Generative AI (GenAI) is reshaping design education, leading to the emergence of new university policies and evolving student practices. This study offers a comparative review of 17 institutional policies and 38 empirical studies on design students’ engagement with GenAI. Using inductive analysis, we developed a synthesized set of themes that capture both regulatory guidance and practical usage. Our findings indicate that while institutional policies emphasize responsible use, general-purpose recommendations, and abstract competency aims, student practices are characterized by situated judgment, iterative workflows, and profession-oriented skill development. These contrasts point to areas where institutional frameworks may fall short in addressing the specific pedagogical and disciplinary realities of design education. By highlighting both alignments and emerging mismatches, this review provides a structured basis for improving policy-practice coherence and supporting more context-sensitive integration of GenAI into creative education.