Pedagogy 2025

Abstract

Architecture education traditionally maintains rigid boundaries between design thinking and quantitative analysis, leaving students unprepared for contemporary urban practice requiring data literacy. This study documents a pedagogical intervention using AI as learning partner to bridge disciplinary boundaries in an 8-week intensive online course. Fifteen architecture students with zero programming experience participated in “Mapping is Power,” employing collaborative AI-assisted programming methodology. Students executed provided code examples, then recreated equivalent analyses through directed AI interaction, progressing from basic Python operations to sophisticated urban research using real MLS stadium datasets. The pedagogical framework positioned AI as interactive tutor rather than content generator, enabling scaffolded skill development while maintaining analytical rigor. Canvas analytics documented robust engagement (32-103 hours average activity, 87% completion rate). Portfolio analysis revealed remarkable transformation: students produced work ranging from basic stadium business analysis to sophisticated 15-minute city integration studies, walkability correlation research, and accessibility assessments credible in consulting contexts. Final projects demonstrated genuine analytical independence, developing both technical competency and design thinking sophistication suitable for professional application. This approach offers a replicable model for integrating AI tools as learning partners across design disciplines, addressing contemporary demands for data literacy while preserving spatial reasoning that distinguishes architectural education. The methodology demonstrates potential for scaling across programs seeking to bridge humanities and STEM educational divides.