Date
Publisher
arXiv
Architectural design education relies heavily on visual ideation and representation to support collaborative learning in studio environments. Recent advances in generative artificial intelligence (GenAI) and extended reality (XR) offer new opportunities for rapid idea exploration and immersive spatial visualization. This exploratory mixed-methods classroom study investigated how GenAI-assisted multi-user XR influenced collaborative architectural conceptual design. We developed GenARch, a pipeline that integrates GenAI-based visual generation with collaborative XR environments, and deployed it in an undergraduate architectural design studio. Twenty-seven students formed seven self-selected design teams; four teams incorporated GenARch into their usual course workflow to support collaborative ideation and visualization, while three teams continued the same course workflow without GenARch. Pre- and post-intervention surveys assessed design self-efficacy, attitudes toward collaborative learning, and teamwork; a seven-member panel evaluated team design presentations; and GenARch teams participated in group interviews. The quantitative results showed larger relative declines in confidence and outcome expectancy for the GenARch condition and a positive difference-in-differences estimate for perceived conflict management, while panel-rated presentation outcomes were not significantly different between conditions. Interviews indicated complementary roles for the technologies: GenAI supported idea externalization and visual reference generation, whereas XR supported spatial, contextual, and scale-based evaluation. Students also reported challenges related to control, dimensional fidelity, shared attention, and motion comfort. These findings highlight both opportunities and limitations when GenAI and XR are incorporated into collaborative design education.
Study at a glance
- Question: How does integrating generative AI and extended reality affect collaborative conceptual architectural design in studio education?
- Setting and data: Undergraduate architectural design studio, September 2025, 27 sophomore architectural engineering students in seven self-selected teams.
- Method: Mixed methods combining a team-level randomized experiment (difference-in-differences analysis), pre- and post-surveys, blinded panel rubric ratings, and semi-structured group interviews.
Why it matters
The combined use of generative AI and extended reality in architectural design education remains at an early stage. Technical affordances do not automatically produce educational benefits without integration into authentic collaborative workflows.
Key findings
- Students using the GenARch pipeline experienced larger relative declines in design self-efficacy confidence and outcome expectancy, alongside a significant relative gain in perceived conflict management.
- Blinded panel ratings of final design presentations showed no statistically significant differences between GenARch teams and control teams across any evaluation criteria.
- Interviews revealed that generative AI aided rapid visual ideation and extended reality supported spatial scale evaluation, but students encountered challenges with scale fidelity, control, and motion comfort.
Summary drafted with AI from the full paper and may contain errors. See the full paper for details.
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