As artificial intelligence (AI) gradually becomes an integral part of higher education, its integration with creative disciplines such as architectural design studios, raises pedagogical, ethical and epistemological questions. This study presents a semester long empirical investigation concerning AI adoption among 37 architecture students in a third-year speculative design studio. Rather than mandating its use, the course positioned generative systems as optional epistemic actors in order to monitor the students’ approaches in embracing or resisting a relationship with generative systems. The evaluation system was constructed via a weekly interaction matrix that cross-referenced AI integration scores (0-3 scale, constant) with performance metrics (0-2/10 scale, variable) per assignment. This kind of systematic tracking gave us a baseline to perform longitudinal typology analysis, as a diagnostic survey to map students’ attitudes in relation to AI adoption. Five behavioural archetypes emerged throughout the academic term: Digital Emergers, Strategic Adopters, Cautious Integrators, Disengaged, and Resistant; revealing varied temporal patterns of integration. The research highlights the non-linear evolution of digital abilities shaped by contextual alignment, cognitive load and dialogical scaffolding. It also recognizes infrastructural disparities and the ethical uncertainties of AI co-authorship as significant obstacles to fair and substantive integration. The findings support a paradigm change from instructing digital tools as mere software, to guiding students in adaptive reasoning, ethical judgment, and the strategic engagement with AI as collaborators. This research offers a replicable methodology for documenting the temporal progression of digital competence development and establishes a comprehensive framework for educators aiming to incorporate AI into design-based learning environments with critical insight and pedagogical awareness.

The Cognitive-Digital Turn in Higher-Education: A Longitudinal Analysis of AI Engagement in an Architectural Design Studio

Fulvio Papadhopulli
Primo
;
2025

Abstract

As artificial intelligence (AI) gradually becomes an integral part of higher education, its integration with creative disciplines such as architectural design studios, raises pedagogical, ethical and epistemological questions. This study presents a semester long empirical investigation concerning AI adoption among 37 architecture students in a third-year speculative design studio. Rather than mandating its use, the course positioned generative systems as optional epistemic actors in order to monitor the students’ approaches in embracing or resisting a relationship with generative systems. The evaluation system was constructed via a weekly interaction matrix that cross-referenced AI integration scores (0-3 scale, constant) with performance metrics (0-2/10 scale, variable) per assignment. This kind of systematic tracking gave us a baseline to perform longitudinal typology analysis, as a diagnostic survey to map students’ attitudes in relation to AI adoption. Five behavioural archetypes emerged throughout the academic term: Digital Emergers, Strategic Adopters, Cautious Integrators, Disengaged, and Resistant; revealing varied temporal patterns of integration. The research highlights the non-linear evolution of digital abilities shaped by contextual alignment, cognitive load and dialogical scaffolding. It also recognizes infrastructural disparities and the ethical uncertainties of AI co-authorship as significant obstacles to fair and substantive integration. The findings support a paradigm change from instructing digital tools as mere software, to guiding students in adaptive reasoning, ethical judgment, and the strategic engagement with AI as collaborators. This research offers a replicable methodology for documenting the temporal progression of digital competence development and establishes a comprehensive framework for educators aiming to incorporate AI into design-based learning environments with critical insight and pedagogical awareness.
2025
AI Integration in Design Education, Digital Competence Trajectories, Architectural Pedagogy, Interaction Matrix, Temporal Behavioural Typologies
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/2629696
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