Abstract
In design education, AI-assisted visualisation tools are challenging established sketching practices during ideation, influencing how students generate, iterate, and develop ideas. Empirical research on their impact on students’ creative processes is essential to guide pedagogical integration. Guided by the Design Tool Characteristics (DTCs) framework, this study analyses the survey data (n = 55) from two undergraduate design cohorts (2024–2025) using an AI sketch rendering tool during studio-based ideation. Findings reveal a central fidelity–flexibility paradox: AI’s high-fidelity outputs accelerated divergent visualisation, yet its perceived low flexibility and limited control constrained iterative refinement. This tension between rapid generation and limited creative agency challenges conventional low-commitment sketching workflows, advancing theoretical understanding of how tool characteristics shape creative engagement. Based on the findings, we propose pedagogical strategies to support stage-appropriate AI use, cultivate AI literacies, enhance creative engagement, and inform the development of AI tools that support both divergent exploration and convergent refinement.
Keywords
Generative AI, Design visualisation, Ideation; Design education
DOI
https://doi.org/10.21606/drs.2026.1571
Citation
Zhang, W., Ranscombe, C., and Coutts, E. (2026) The fidelity-flexibility paradox: Student creative experience with AI-assisted visualisation in design ideation, in Simeone, L., Gray, C. M., Verhoeven, A., de Götzen, A., Bakırlıoğlu, Y., Zohar, H., Stead, M., and Buwert, P. (eds.), DRS2026: Edinburgh, 8–12 June, Edinburgh, United Kingdom. https://doi.org/10.21606/drs.2026.1571
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Included in
The fidelity-flexibility paradox: Student creative experience with AI-assisted visualisation in design ideation
In design education, AI-assisted visualisation tools are challenging established sketching practices during ideation, influencing how students generate, iterate, and develop ideas. Empirical research on their impact on students’ creative processes is essential to guide pedagogical integration. Guided by the Design Tool Characteristics (DTCs) framework, this study analyses the survey data (n = 55) from two undergraduate design cohorts (2024–2025) using an AI sketch rendering tool during studio-based ideation. Findings reveal a central fidelity–flexibility paradox: AI’s high-fidelity outputs accelerated divergent visualisation, yet its perceived low flexibility and limited control constrained iterative refinement. This tension between rapid generation and limited creative agency challenges conventional low-commitment sketching workflows, advancing theoretical understanding of how tool characteristics shape creative engagement. Based on the findings, we propose pedagogical strategies to support stage-appropriate AI use, cultivate AI literacies, enhance creative engagement, and inform the development of AI tools that support both divergent exploration and convergent refinement.