Gen-AI-tecture: using generative AI to support architectural students in design tasks
Provides evidence-based guidance for integrating generative AI into architectural pedagogy, addressing the need for inclusive and effective AI-supported learning in design education.
The study embedded a locally executed, discipline-specific generative AI tool into architectural design education, finding enhanced creative fluency, broader participation across diverse learner profiles, and strengthened confidence in AI-supported design processes.
The "Gen-AI-tecture" project embeds a locally executed, discipline-specific tool into a mixed-methods focus-group design, structured around three research objectives: (a) to evaluate how generative AI tools impact students' creativity in design-thinking processes and outcomes, (b) to assess whether these tools enhance inclusivity in learning processes, and (c) to examine how they develop students' AI-handling skills with a view to boosting future employability. Findings indicate enhanced creative fluency, broadened participation across diverse learner profiles, and strengthened confidence in AI-supported design processes. The study contributes evidence-based guidance for integrating generative-AI workflows into architectural pedagogy, demonstrating how such tools can operationalise constructivist principles of learner-led meaning-making, support connectivist understandings of learning as participation in human-AI networks, and advance universal learning theories by promoting more inclusive, flexible and accessible educational practices for contemporary learners.