A Methodological Proposal AI Based for Learning in Architecture, Evaluating Its Acceptance and Perceived Usefulness

AI-based tools are being introduced at an accelerating pace in educational settings, influencing how students learn and reshaping their habits. This study examines their application in architectural design teaching. Within an architectural design course, AI tools were integrated into three stages of the design process: language models to support conceptual definition, volumetric modeling to explore geometric relationships, and spatial resolution to organize and test functional layouts. To evaluate integration, digital surveys with ordinal questions were administered at each stage to assess students’ perceptions of usefulness. Results demonstrate that AI positively supports acceptance in design education by streamlining processes, generating ideas, and facilitating decision-making. Nonetheless, findings also show that while students were already familiar with AI prior to the course, effective and discipline-specific use required structured guidance and prior course knowledge, particularly when engaging with specialized tools. This indicates that teaching support remains crucial for ensuring rigorous application. The study concludes with a replicable methodology for integrating AI into architectural learning, with implications for pedagogy and professional practice.