To Use or to Refuse? Re-Centering Student Agency with Generative AI in Engineering Design Education

• URL: http://arxiv.org/abs/2510.19342v1
• Date: Wed, 22 Oct 2025 08:06:48 GMT
• Title: To Use or to Refuse? Re-Centering Student Agency with Generative AI in Engineering Design Education
• Authors: Thijs Willems, Sumbul Khan, Qian Huang, Bradley Camburn, Nachamma Sockalingam, King Wang Poon,
• Abstract summary: This pilot study traces students' reflections on the use of AI in a 13-week foundational design course enrolling over 500 first-year engineering and architecture students at the Singapore University of Technology and Design.<n>Students were required to reflect on whether the technology was used as a tool (instrumental assistant), a teammate (collaborative partner), or neither.<n>Students learned to use AI for innovation rather than just automation and to reflect on agency, ethics, and context rather than on prompt crafting alone.
• Score: 14.581313362006272
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This pilot study traces students' reflections on the use of AI in a 13-week foundational design course enrolling over 500 first-year engineering and architecture students at the Singapore University of Technology and Design. The course was an AI-enhanced design course, with several interventions to equip students with AI based design skills. Students were required to reflect on whether the technology was used as a tool (instrumental assistant), a teammate (collaborative partner), or neither (deliberate non-use). By foregrounding this three-way lens, students learned to use AI for innovation rather than just automation and to reflect on agency, ethics, and context rather than on prompt crafting alone. Evidence stems from coursework artefacts: thirteen structured reflection spreadsheets and eight illustrated briefs submitted, combined with notes of teachers and researchers. Qualitative coding of these materials reveals shared practices brought about through the inclusion of Gen-AI, including accelerated prototyping, rapid skill acquisition, iterative prompt refinement, purposeful "switch-offs" during user research, and emergent routines for recognizing hallucinations. Unexpectedly, students not only harnessed Gen-AI for speed but (enabled by the tool-teammate-neither triage) also learned to reject its outputs, invent their own hallucination fire-drills, and divert the reclaimed hours into deeper user research, thereby transforming efficiency into innovation. The implications of the approach we explore shows that: we can transform AI uptake into an assessable design habit; that rewarding selective non-use cultivates hallucination-aware workflows; and, practically, that a coordinated bundle of tool access, reflection, role tagging, and public recognition through competition awards allows AI based innovation in education to scale without compromising accountability.

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