This study investigates the impact of stage-specific integration of Generative AI (GenAI) on learning processes in studio-based architectural education, assessed through design quality, student performance, and design productivity.
The research reviewed literature on traditional architectural design processes, theories of design education, and the impact of AI-integrated learning. Subsequently, a pilot questionnaire was administered to undergraduate architecture students across all four levels to identify gaps in the use of AI tools within design studios. This was followed by a supervised senior-level project at the Faculty of Engineering, Cairo University (CUFE), comparing performance of an AI-assisted group with a conventional group. Additionally, interviews with the participants were conducted to triangulate quantitative findings.
The findings indicate the AI-assisted group demonstrated a 14% improvement in creativity, design form, and visualization, and deliverable quantity, 14% higher productivity compared to the conventional group, with strong gains among lower-performing students. The results suggest that structured stage-specific AI integration can enhance students' performance particularly during key stages such as form generation and façade design.
The study proposes a recommended framework connecting design stages with GenAI outputs, offering practical guidance for educators on when and how AI tools can be integrated into architectural design studios.
In this AI paradigm shift, this study provides context-specific empirical evidence on stage-oriented GenAI integration in architectural education, employing a multi-layered methodological structure within a developing-country context.
