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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA)
Santos, D., Verniz, D.  & Domingos, L. (2026). AI in architectural education: A global survey of course curricula and trends. In Alvaro Rocha, Francisco García Peñalvo, Carlos J. Costa, Ramiro Gonçalves (Ed.), Proceedings of 20th Iberian Conference on Information Systems and Technologies (CISTI 2025) (pp. 3?14). Springer Nature. https://doi.org/10.1007/978-3-032-10929-3_1
Exportar Referência (IEEE)
D. M. Santos et al.,  "AI in architectural education: A global survey of course curricula and trends", in Proc. of 20th Iberian Conf. on Information Systems and Technologies (CISTI 2025), Alvaro Rocha, Francisco García Peñalvo, Carlos J. Costa, Ramiro Gonçalves, Ed., Lisboa, Springer Nature, 2026, vol. 1716 LNNS, pp. 3-14
Exportar BibTeX
@inproceedings{santos2026_1793116896028,
	author = "Santos, D. and Verniz, D.  and Domingos, L.",
	title = "AI in architectural education: A global survey of course curricula and trends",
	booktitle = "Proceedings of 20th Iberian Conference on Information Systems and Technologies (CISTI 2025)",
	year = "2026",
	editor = "Alvaro Rocha, Francisco García Peñalvo, Carlos J. Costa, Ramiro Gonçalves",
	volume = "1716 LNNS",
	number = "",
	series = "",
	doi = "10.1007/978-3-032-10929-3_1",
	pages = "3-14",
	publisher = "Springer Nature",
	address = "Lisboa",
	organization = "",
	url = "https://link.springer.com/book/10.1007/978-3-032-10929-3"
}
Exportar RIS
TY  - CPAPER
TI  - AI in architectural education: A global survey of course curricula and trends
T2  - Proceedings of 20th Iberian Conference on Information Systems and Technologies (CISTI 2025)
VL  - 1716 LNNS
AU  - Santos, D.
AU  - Verniz, D. 
AU  - Domingos, L.
PY  - 2026
SP  - 3-14
SN  - 2367-3370
DO  - 10.1007/978-3-032-10929-3_1
CY  - Lisboa
UR  - https://link.springer.com/book/10.1007/978-3-032-10929-3
AB  - The integration of artificial intelligence (AI) into architectural education is reshaping how future architects are trained, as technologies like generative design, AI-enhanced BIM, and data-driven urbanism become central to the profession. This study examines the incorporation of AI-related topics in architectural curricula at the world’s top 100 universities, ranked by the Academic Ranking of World Universities (ARWU). Through analyzing course descriptions, syllabi, and program details, the research identifies the presence of AI in architectural programs, categorizes the types of AI topics taught, and compares regional trends in AI integration. Findings reveal that leading institutions in North America and Europe are at the forefront of AI adoption, emphasizing computational design, smart cities, and sustainable solutions, while other regions face challenges like resource limitations and technological disparities. Despite the growing emphasis on AI, barriers such as curricular constraints, faculty training gaps, and unequal access to resources hinder its widespread adoption. To address these challenges, the study recommends prioritizing interdisciplinary collaboration, investing in faculty development, and promoting project-based learning that integrates AI into real-world design scenarios. Additionally, global partnerships and open-access resources are essential to reduce disparities and ensure equitable access to AI-driven educational tools. This research provides a comprehensive understanding of how AI is being integrated into architectural education globally, offering insights for educators, policymakers, and practitioners seeking to bridge the gap between academic training and industry demands. By embracing these strategies, architectural education can better prepare students to leverage AI in creating innovative, sustainable, and human-centered built environments.
ER  -