Dataset for: Quantifying Built Environment Aesthetics: A Generative AI Approach to Decoupling Architectural Style and Form

This dataset contains anonymized response data from a pairwise forced-choice experiment investigating aesthetic judgments in the built environment. Participants (N = 106) were spatial design students from a university in Taiwan. The experiment used AI-generated architectural façade stimuli to evaluate preference hierarchies and decision dynamics across different architectural styles. Each participant completed a series of comparative judgment trials where they selected preferred architectural images while reaction time was recorded. To protect participant privacy and adhere to ethical guidelines, all identifying information including student names, student IDs, and institutional identifiers has been removed. Participants are represented only by anonymized participant codes. The dataset supports the findings reported in the manuscript: "Quantifying Built Environment Aesthetics: A Generative AI Approach to Decoupling Architectural Style and Form."