Teaching with Artificial Intelligence in Architecture: Embedding Technical Skills and Ethical Reflection in a Core Design Studio

This case study examines the integration of artificial intelligence (AI) into undergraduate architectural education through a 2024–25 core studio teaching experiment at Zhejiang University. A dual-module framework was implemented, comprising a 20 h AI skills training module and in-class ethics discussions, without altering the existing studio structure. The AI skills module introduced deep learning models, LLMs, AIGC image models, LoRA fine-tuning, and ComfyUI, supported by a dedicated technical instructor. Student feedback indicated phase-dependent and tool-sensitive engagement, and students expressed a preference for embedded ethical discussion within the design studio rather than separate formal instruction. The experiment demonstrated that modular AI education is both scalable and practical, highlighting the importance of phase-sensitive guidance, balanced technical and ethical framing, and institutional support such as cloud platforms and research-based AI tools. The integration enhanced students’ digital adaptability and strategic thinking while prompting reflection on issues such as authorship, algorithmic bias, and accountability in human–AI collaboration. These findings offer a replicable model for AI-integrated design pedagogy that balances technical training with critical awareness.

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Publication Details

Journal
Buildings
Published
2025-08-27
DOI
https://doi.org/10.3390/buildings15173069
Citations
3
Primary Topic
BIM and Construction Integration
Type
article
Field-Weighted Citation Impact
3.02
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article

Teaching with Artificial Intelligence in Architecture: Embedding Technical Skills and Ethical Reflection in a Core Design Studio

Jiaqi Wang, Xiang Chen, Yi Lan, Yu Shi et al.
3 citations
Buildings
BIM and Construction Integration
3.02
article

Teaching with Artificial Intelligence in Architecture: Embedding Technical Skills and Ethical Reflection in a Core Design Studio

Jiaqi Wang, Xiang Chen, Yi Lan, Yu Shi, Shuying Liu
article en
3 citations

Abstract

This case study examines the integration of artificial intelligence (AI) into undergraduate architectural education through a 2024–25 core studio teaching experiment at Zhejiang University. A dual-module framework was implemented, comprising a 20 h AI skills training module and in-class ethics discussions, without altering the existing studio structure. The AI skills module introduced deep learning models, LLMs, AIGC image models, LoRA fine-tuning, and ComfyUI, supported by a dedicated technical instructor. Student feedback indicated phase-dependent and tool-sensitive engagement, and students expressed a preference for embedded ethical discussion within the design studio rather than separate formal instruction. The experiment demonstrated that modular AI education is both scalable and practical, highlighting the importance of phase-sensitive guidance, balanced technical and ethical framing, and institutional support such as cloud platforms and research-based AI tools. The integration enhanced students’ digital adaptability and strategic thinking while prompting reflection on issues such as authorship, algorithmic bias, and accountability in human–AI collaboration. These findings offer a replicable model for AI-integrated design pedagogy that balances technical training with critical awareness.

BuildingsVol. 15(17)
Wuhan University of Technology (CN), Zhejiang Province Institute of Architectural Design and Research (CN), Zhejiang University (CN)
Openalex Percentile: Top 9%
BIM and Construction Integration
3.02
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Teaching with Artificial Intelligence in Architecture: Embedding Technical Skills and Ethical Reflection in a Core Design Studio — Jiaqi Wang, Xiang Chen, et al. · Buildings (2025) | TGRS Research Map | TGRS