Pedagogy 2025

Abstract

As architectural education evolves in response to shifting technological, societal, and ecological imperatives, integrating AI into pedagogy is essential. In line with the outward turn of academia and the push toward applied, student-centered learning, this work introduces EmoGenAi, a web-based application developed to make emerging AI tools accessible to students and educators alike. Developed to support both design pedagogy and research, EmoGenAi merges data-informed methodologies with creative exploration, enabling more engaged, analytical, and feedback-responsive design processes that take into account human perspectives and experience. It comprises three distinct modules: PredictiveAi, which allows students to build and test predictive models, particularly focused on performance-based design; EmotionAi, which leverages large language models for custom context-sensitive emotion analysis of human feedback to enable insightful interpretations of user experiences in response to built environments; and ArchGenAi, a generative AI engine that translates textual prompts into architectural visualizations across historical, theoretical, and technical domains and at scale, allowing for rapid iteration and speculative exploration of spatial ideas. Together, these tools foster a multi-dimensional design literacy—combining empirical evidence, emotional intelligence, and visual imagination. The platform supports flipped classrooms, peer-to-peer experimentation, and interdisciplinary research, bridging the studio and seminar environment with real-world concerns and community feedback. By democratizing access to AI modeling and visualization, EmoGenAi also cultivates critical AI literacy in future architects, empowering them to interrogate, not just deploy, emerging technologies. This presentation will showcase how the tool can be embedded into architecture curricula, from design studios to research seminars, and discuss its potential for cross-disciplinary application.