Artificial intelligence in architecture education: reflections through structural equation modeling

Abstract

This study explores architecture students' attitudes, awareness, and use of artificial intelligence (AI) technologies within a multidimensional framework. As AI becomes integral to education, a comprehensive evaluation is vital in architecture, where creative and technical skills converge. A questionnaire based on RIBA's 2024 Artificial Intelligence Report was administered to architecture students, and data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The model demonstrated acceptable reliability and validity (Cronbach's alpha > 0.70, AVE > 0.50). Results showed that educational components significantly affected future perceptions (beta = 0.242, p < 0.01), and application effectiveness enhanced digital maturity (beta = 0.292, p < 0.01). Future perceptions also improved ethical awareness (beta = 0.308, p < 0.05). Although many students use AI tools, they lack systematic training, and positive perceptions do not necessarily translate into practice. Findings emphasize that AI-related learning is shaped not only by technical competence but also by digitalization, ethics, and professional transformation. The study recommends integrating AI into curricula, updating pedagogical strategies, and enhancing ethical awareness to support responsible and effective use. It contributes timely insights into how AI influences architectural education and students' readiness for future practice.