Gen-AI-tecture: using generative AI to support architectural students in design tasks

TL;DR

This study evaluates how generative AI tools influence architectural students' creativity, inclusivity, and AI skills, providing guidance for integrating AI into design education to enhance learning outcomes.

Contribution

It offers evidence-based insights into embedding generative AI workflows in architectural pedagogy, promoting inclusive, flexible, and constructivist learning practices.

Findings

Enhanced creative fluency in students.

Broadened participation among diverse learners.

Increased confidence in AI-supported design processes.

Abstract

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.