Araştırma Makalesi
BibTex RIS Kaynak Göster

Integration of Artificial Intelligence into the Architectural Design Process: Architectural Studio Experience

Yıl 2025, Cilt: 8 Sayı: 6, 1874 - 1882, 15.11.2025
https://doi.org/10.34248/bsengineering.1761624

Öz

Integrating artificial intelligence (AI) technology into architectural design processes is becoming increasingly widespread, offering significant innovations. This study examines the effects of an AI-enabled design tool on architectural outputs through a student project produced in an architecture studio. The main theme of the architecture studio, Climate Change and Its Impacts: Architectural Analyses for Future Scenarios, focuses on the urgent problems posed by climate change and emphasizes the necessity of sustainable, adaptive design approaches. The project was evaluated using Leonardo AI, a meta-learning platform. This evaluation was carried out in two categories. In the first category, an image was generated concerning the existing student design; in the second category, the scenario was left entirely to the AI's perception without any reference. The findings show that AI optimizes design processes, improves decision-making processes through complex data analysis, and increases the speed of realization of building designs. However, it was found that AI cannot address post-design issues where human intelligence is strong. Therefore, a hybrid use of AI and human input was considered a more effective method, and it was concluded that combining the unique strengths of both parties would be beneficial. While the study highlights the potential of AI in architectural design processes, further research is needed to develop hybrid systems and strategies for integrating AI into the profession. It also provides essential insights into the changing role of AI in the architectural profession and its implications for future design practice.

Etik Beyan

Ethics committee approval was not required for this study because there was no study on animals or humans.

Teşekkür

The authors thank the Gazi University Academic Writing Application and Research Center for proofreading the article.

Kaynakça

  • Abd El Fattah Ammar Z. 2023. Artificial intelligence and its role in accelerating decision-making processes in architectural design. Int J Archit Eng Urban Res, 6(2): 280-296. doi: 10.21608/ijaeur 2024.261190.1061
  • Albaghajati ZM, Bettaieb DM, Malek RB. 2023. Exploring text-to-image application in architectural design: insights and implications. Archit Struct Constr, 3(4): 475-497. https://doi.org/10.1007/s44150-023-00103-x
  • As I, Pal S, Basu P. 2018. Artificial intelligence in architecture: generating conceptual design via deep learning. Int J Archit Comput, 16(4): 306-327. https://doi.org/10.1177/1478077118800982
  • Bellaiche L, Shahi R, Turpin M, Ragnhildstveit A, Sprocket, Barr N, …, Seli P. 2023. Humans versus AI: whether and why we prefer human-created compared to AI-created artwork. Cogn Res Princ Implic, 8(1): 1-22. https://doi.org/10.1186/s41235-023-00499-6
  • Bengio Y. 2009. Learning deep architectures for AI. Found Trends Mach Learn, 2(1): 1-127. https://doi.org/10.1561/2200000006
  • Bölek B, Tutal O, Özbaşaran H. 2023. A systematic review on artificial intelligence applications in architecture. J Des Resil Archit Plan, 4(1): 91-104. https://doi.org/10.47818/drarch.2023.v4i1085
  • Brunetti GL. 2023. Evolutionary trends in the use of artificial intelligence in support of architectural design. Techne, 25, 55-60. https://doi.org/10.36253/techne-13739
  • Caratti-Zarytkiewicz R. 2023. Visual studies is a new opportunity for theoretical thinking in architectural lighting design. In: Proceedings of the 2023 IEEE Sustainable Smart Lighting World Conference & Expo (LS18), December 07-09, Mumbai, India, pp: 1-6. https://doi.org/10.1109/LS1858153.2023.10170083
  • Cudzik J, Radziszewski K. 2018. Artificial intelligence aided architectural design. In: Proceedings of the 36th eCAADe. September 19-21, Łódź, Poland, pp: 77-84. https://doi.org/10.52842/conf.ecaade.2018.1.077
  • Dilaveroğlu, B. 2024. The architecture of visual narrative: can text-to-image algorithms enhance the power of stylistic narrative for architecture. Int J Archit Comput, 22(3): 432-457. https://doi.org/10.1177/14780771241234449
  • European Parliament. 2020. What is artificial intelligence, and how is it used?. URL: https://www.europarl.europa.eu/topics/en/article/20200827STO85804/what-is-artificial-intelligence-and-how-is-it-used (accessed date: September 4, 2024).
  • Gero JS. 1994. Computational models of creative design processes. In: Dartnall T (ed). Artificial intelligence and creativity. Springer Netherlands, Dordrecht, pp: 269-281. https://doi.org/10.1007/978-94-017-0793-0_19
  • Hanafy N. 2023. Improving the environmental and design performance of building facades using “artificial intelligence”. J Eng Res, 7(3): 337-348. https://digitalcommons.aaru.edu.jo/erjeng/vol7/iss3/60
  • Hewitt C, Lieberman H. 1983. Design issues in parallel architectures for artificial intelligence. In: Proceedings of the IEEE Computer Society International Conference, September 01-30, Washington DC, USA, pp: 1-14.
  • Horvath A., Pouliou P. 2024. AI for conceptual architecture: reflections on designing with text-to-text, text-to-image, and image-to-image generators. Front Archit Res, 13(3): 593-612. https://doi.org/10.1016/j.foar.2024.02.006
  • Kolarevic B. 2003. Architecture in the digital age: design and manufacturing. Spon Press/Taylor & Francis Group, New York-London, pp: 1-16.
  • Krausková V, Pifko H. 2021. Use of artificial intelligence in the field of sustainable architecture: current knowledge. Archit Pap Fac Archit Des STU, 26(1): 20-29. https://doi.org/10.2478/alfa-2021-0004
  • Kriegler E, Edmonds J, Hallegatte S, Ebi KL, Kram T, Riahi K, Winkler H, van Vuuren DP. 2014. A new scenario framework for climate change research: the concept of shared climate policy assumptions. Clim Change, 122(3): 401-414. https://doi.org/10.1007/s10584-013-0971-5
  • Kwon DH. 2024. Analysis of prompt elements and use cases in image-generating AI: focusing on midjourney, stable diffusion, firefly. DALL EJ Digit Contents Soc, 25(2): 341-354.
  • Lee H, Calvin K, Dasgupta D, Krinner G, Mukherji A, Thorne P, Trisos C, Romero J, Aldunce P, Ruane AC. 2024. Climate change 2023 synthesis report summary for policymakers. URL: https://ntrs.nasa.gov/citations/20230009518 (accessed date: September 4, 2024).
  • Li H, Wu Q, Xing B, Wang W. 2023. Exploration of the intelligent-auxiliary design of architectural space using artificial intelligence model. PLoS One, 18(3): 1-17. https://doi.org/10.1371/journal.pone.0282158
  • Long R, Li Y. 2021. Research on energy-efficiency building design based on BIM and artificial intelligence. In: Proceedings of the 2nd Int Conf Energy Saving Environ Protection Civil Eng, June 18-20, Xining, China, pp: 1-6. https://doi.org/10.1088/1755-1315/825/1/012003
  • Matter MG, Gado N. 2024. Artificial intelligence in architecture: integration into architectural design process. Eng Res J, 181 (March2024): 1-16. https://doi.org/10.21608/erj.2024.344313
  • McCarthy J, Minsky ML, Rochester N, Shannon CE. 1956. A proposal for the dartmouth summer research project on artificial intelligence. URL: https://home.dartmouth.edu/about/artificial-intelligence-ai-coined-dartmouth (accessed date: September 4, 2024).
  • Meng Q, Ge M, Zhang F. 2024. The integration of artificial intelligence in architectural visualization enhances augmented realism and interactivity. Acad J Sci Tech, 12(2): 7-12. https://doi.org/10.54097/yt4z3z55
  • Moussaoui M. 2025. Architectural practice process and artificial intelligence - an evolving practice. Open Eng, 15(1): 1-15. https://doi.org/10.1515/eng-2024-0098
  • Nakicenovic N, Lempert RJ, Janetos AC. 2014. A framework for the development of new socio-economic scenarios for climate change research: introductory essay. Clim Change, 122(3): 351-361. https://doi.org/10.1007/s10584-013-0982-2
  • Ningki ANK, Hikmah N, Harrama A, Alishah FN, Lukman MIRI. 2023. Penerapan AI dalam presentasi visualisasi desain arsitektur. Semin Nas Dies Natalis 62, 1: 335-340. https://doi.org/10.59562/semnasdies.v1i1.917
  • O’Neill BC, Kriegler E, Riahi K, Ebi KL, Hallegatte S, Carter TR, Mathur R, van Vuuren DP. 2014. A new scenario framework for climate change research: the concept of shared socioeconomic pathways. Clim Change, 122(3): 387-400. https://doi.org/10.1007/s10584-013-0905-2
  • Oxman R. 2014. Theories of the digital in architecture. Routledge, Taylor & Francis Group, London, pp: 72.
  • Sadek MR, Mohamed NAG. 2023. Artificial Intelligence as a pedagogical tool for architectural education: what does the empirical evidence tell us?. MSA Eng J, 2(2): 133-148. https://doi.org/10.21608/msaeng.2023.291867
  • Schumacher P. 2011. The autopoiesis of architecture: a new framework for architecture. John Wiley & Sons Limited, Chichester, UK, pp: 480.
  • Seli P, Ragnhildstveit A, Orwig W, Bellaiche L, Spooner S, Barr N. 2024. Beyond the brush: human versus AI creativity in the realm of generative art. Psychol Aesthet Creat Arts, pp:1-9. https://doi.org/10.31234/osf.io/vgzhj
  • SPM. 2019. Summary for policymakers-special report on climate change and land. URL: https://www.ipcc.ch/srccl/chapter/summary-for-policymakers/ (accessed date: January 17, 2025).
  • Steinfeld K. 2021. Significant others: machine learning as actor, material, and provocateur in art and design. In: The routledge companion to artificial intelligence in architecture. Routledge, New York, pp: 3-12.
  • Tafahomi R. 2022. Educational behavior of the students in the design studios during the pandemic time. Int J Soc Sci Educ Res, 8(4): 352-362. Article 4. https://doi.org/10.24289/ijsser.1164545
  • Takva Y, Takva C, Goksen F. 2023. A contemporary house proposal: structural analysis of wood and steel bungalows. ETASR, 13(3): 11032-11035. https://doi.org/10.48084/etasr.5896
  • Tanugraha S. 2023. Review using artificial intelligence-generating images: exploring material ideas from midjourney to improve vernacular designs. J Artif Intell Archit, 2(1): 48-57. https://doi.org/10.24002/jarina.v2i2.7537
  • Tuztaşi U, Koç P. 2019. “Design like him/her” method in the context of experimentality of design studies. Int Ref J Des Archit, 17: 104-137. https://doi.org/10.17365/TMD.2019.2.1
  • UNDP. 2023. The climate dictionary: an everyday guide to climate change | UNDP climate promise. URL: https://climatepromise.undp.org/news-and-stories/climate-dictionary-everyday-guide-climate-change (accessed date: February 23, 2025).
  • van Vuuren DP, Kriegler E, O’Neill BC, Ebi KL, Riahi K, Carter TR, Edmonds J, Hallegatte S, Kram T, Mathur R, Winkler H. 2014. A new scenario framework for climate change research: scenario matrix architecture. Clim Change, 122(3): 373-386. https://doi.org/10.1007/s10584-013-0906-1
  • Viliunas G, Grazuleviciute-Vileniske I. 2022. Shape-finding in biophilic architecture: application of AI-based tool. Archit Urban Plan, 18(1): 68-75. https://doi.org/10.2478/aup-2022-0007
  • Yaman Y, Tokuç A, Köktürk G. 2022. Towards carbon neutral settlements with algae. Int Ref J Des Archit, 25: 1-32. https://doi.org/10.17365/TMD.2022.TURKEY.25.01
  • Yıldırım E. 2023. Comparative analysis of leonardo AI, midjourney, and Dall-E: AI's perspective on future cities. Urbanizm, 28: 82-96. https://doi.org/10.58225/urbanizm.2023-28-82-96
  • Yılmaz N. 2023. Sensory experience in architectural design education: an experimental visual perception study with serial vision method. Soc Sci Dev J, 8(38): 229-239. https://doi.org/10.31567/ssd.939
  • Yoshimura Y, Cai BY, Wang Z, Ratti C. 2018. Deep learning architect: classification for architectural design through the eye of artificial intelligence. URL: https://arxiv.org/abs/1812.01714 (accessed date: February 23, 2025).

Integration of Artificial Intelligence into the Architectural Design Process: Architectural Studio Experience

Yıl 2025, Cilt: 8 Sayı: 6, 1874 - 1882, 15.11.2025
https://doi.org/10.34248/bsengineering.1761624

Öz

Integrating artificial intelligence (AI) technology into architectural design processes is becoming increasingly widespread, offering significant innovations. This study examines the effects of an AI-enabled design tool on architectural outputs through a student project produced in an architecture studio. The main theme of the architecture studio, Climate Change and Its Impacts: Architectural Analyses for Future Scenarios, focuses on the urgent problems posed by climate change and emphasizes the necessity of sustainable, adaptive design approaches. The project was evaluated using Leonardo AI, a meta-learning platform. This evaluation was carried out in two categories. In the first category, an image was generated concerning the existing student design; in the second category, the scenario was left entirely to the AI's perception without any reference. The findings show that AI optimizes design processes, improves decision-making processes through complex data analysis, and increases the speed of realization of building designs. However, it was found that AI cannot address post-design issues where human intelligence is strong. Therefore, a hybrid use of AI and human input was considered a more effective method, and it was concluded that combining the unique strengths of both parties would be beneficial. While the study highlights the potential of AI in architectural design processes, further research is needed to develop hybrid systems and strategies for integrating AI into the profession. It also provides essential insights into the changing role of AI in the architectural profession and its implications for future design practice.

Etik Beyan

Ethics committee approval was not required for this study because there was no study on animals or humans.

Teşekkür

The authors thank the Gazi University Academic Writing Application and Research Center for proofreading the article.

Kaynakça

  • Abd El Fattah Ammar Z. 2023. Artificial intelligence and its role in accelerating decision-making processes in architectural design. Int J Archit Eng Urban Res, 6(2): 280-296. doi: 10.21608/ijaeur 2024.261190.1061
  • Albaghajati ZM, Bettaieb DM, Malek RB. 2023. Exploring text-to-image application in architectural design: insights and implications. Archit Struct Constr, 3(4): 475-497. https://doi.org/10.1007/s44150-023-00103-x
  • As I, Pal S, Basu P. 2018. Artificial intelligence in architecture: generating conceptual design via deep learning. Int J Archit Comput, 16(4): 306-327. https://doi.org/10.1177/1478077118800982
  • Bellaiche L, Shahi R, Turpin M, Ragnhildstveit A, Sprocket, Barr N, …, Seli P. 2023. Humans versus AI: whether and why we prefer human-created compared to AI-created artwork. Cogn Res Princ Implic, 8(1): 1-22. https://doi.org/10.1186/s41235-023-00499-6
  • Bengio Y. 2009. Learning deep architectures for AI. Found Trends Mach Learn, 2(1): 1-127. https://doi.org/10.1561/2200000006
  • Bölek B, Tutal O, Özbaşaran H. 2023. A systematic review on artificial intelligence applications in architecture. J Des Resil Archit Plan, 4(1): 91-104. https://doi.org/10.47818/drarch.2023.v4i1085
  • Brunetti GL. 2023. Evolutionary trends in the use of artificial intelligence in support of architectural design. Techne, 25, 55-60. https://doi.org/10.36253/techne-13739
  • Caratti-Zarytkiewicz R. 2023. Visual studies is a new opportunity for theoretical thinking in architectural lighting design. In: Proceedings of the 2023 IEEE Sustainable Smart Lighting World Conference & Expo (LS18), December 07-09, Mumbai, India, pp: 1-6. https://doi.org/10.1109/LS1858153.2023.10170083
  • Cudzik J, Radziszewski K. 2018. Artificial intelligence aided architectural design. In: Proceedings of the 36th eCAADe. September 19-21, Łódź, Poland, pp: 77-84. https://doi.org/10.52842/conf.ecaade.2018.1.077
  • Dilaveroğlu, B. 2024. The architecture of visual narrative: can text-to-image algorithms enhance the power of stylistic narrative for architecture. Int J Archit Comput, 22(3): 432-457. https://doi.org/10.1177/14780771241234449
  • European Parliament. 2020. What is artificial intelligence, and how is it used?. URL: https://www.europarl.europa.eu/topics/en/article/20200827STO85804/what-is-artificial-intelligence-and-how-is-it-used (accessed date: September 4, 2024).
  • Gero JS. 1994. Computational models of creative design processes. In: Dartnall T (ed). Artificial intelligence and creativity. Springer Netherlands, Dordrecht, pp: 269-281. https://doi.org/10.1007/978-94-017-0793-0_19
  • Hanafy N. 2023. Improving the environmental and design performance of building facades using “artificial intelligence”. J Eng Res, 7(3): 337-348. https://digitalcommons.aaru.edu.jo/erjeng/vol7/iss3/60
  • Hewitt C, Lieberman H. 1983. Design issues in parallel architectures for artificial intelligence. In: Proceedings of the IEEE Computer Society International Conference, September 01-30, Washington DC, USA, pp: 1-14.
  • Horvath A., Pouliou P. 2024. AI for conceptual architecture: reflections on designing with text-to-text, text-to-image, and image-to-image generators. Front Archit Res, 13(3): 593-612. https://doi.org/10.1016/j.foar.2024.02.006
  • Kolarevic B. 2003. Architecture in the digital age: design and manufacturing. Spon Press/Taylor & Francis Group, New York-London, pp: 1-16.
  • Krausková V, Pifko H. 2021. Use of artificial intelligence in the field of sustainable architecture: current knowledge. Archit Pap Fac Archit Des STU, 26(1): 20-29. https://doi.org/10.2478/alfa-2021-0004
  • Kriegler E, Edmonds J, Hallegatte S, Ebi KL, Kram T, Riahi K, Winkler H, van Vuuren DP. 2014. A new scenario framework for climate change research: the concept of shared climate policy assumptions. Clim Change, 122(3): 401-414. https://doi.org/10.1007/s10584-013-0971-5
  • Kwon DH. 2024. Analysis of prompt elements and use cases in image-generating AI: focusing on midjourney, stable diffusion, firefly. DALL EJ Digit Contents Soc, 25(2): 341-354.
  • Lee H, Calvin K, Dasgupta D, Krinner G, Mukherji A, Thorne P, Trisos C, Romero J, Aldunce P, Ruane AC. 2024. Climate change 2023 synthesis report summary for policymakers. URL: https://ntrs.nasa.gov/citations/20230009518 (accessed date: September 4, 2024).
  • Li H, Wu Q, Xing B, Wang W. 2023. Exploration of the intelligent-auxiliary design of architectural space using artificial intelligence model. PLoS One, 18(3): 1-17. https://doi.org/10.1371/journal.pone.0282158
  • Long R, Li Y. 2021. Research on energy-efficiency building design based on BIM and artificial intelligence. In: Proceedings of the 2nd Int Conf Energy Saving Environ Protection Civil Eng, June 18-20, Xining, China, pp: 1-6. https://doi.org/10.1088/1755-1315/825/1/012003
  • Matter MG, Gado N. 2024. Artificial intelligence in architecture: integration into architectural design process. Eng Res J, 181 (March2024): 1-16. https://doi.org/10.21608/erj.2024.344313
  • McCarthy J, Minsky ML, Rochester N, Shannon CE. 1956. A proposal for the dartmouth summer research project on artificial intelligence. URL: https://home.dartmouth.edu/about/artificial-intelligence-ai-coined-dartmouth (accessed date: September 4, 2024).
  • Meng Q, Ge M, Zhang F. 2024. The integration of artificial intelligence in architectural visualization enhances augmented realism and interactivity. Acad J Sci Tech, 12(2): 7-12. https://doi.org/10.54097/yt4z3z55
  • Moussaoui M. 2025. Architectural practice process and artificial intelligence - an evolving practice. Open Eng, 15(1): 1-15. https://doi.org/10.1515/eng-2024-0098
  • Nakicenovic N, Lempert RJ, Janetos AC. 2014. A framework for the development of new socio-economic scenarios for climate change research: introductory essay. Clim Change, 122(3): 351-361. https://doi.org/10.1007/s10584-013-0982-2
  • Ningki ANK, Hikmah N, Harrama A, Alishah FN, Lukman MIRI. 2023. Penerapan AI dalam presentasi visualisasi desain arsitektur. Semin Nas Dies Natalis 62, 1: 335-340. https://doi.org/10.59562/semnasdies.v1i1.917
  • O’Neill BC, Kriegler E, Riahi K, Ebi KL, Hallegatte S, Carter TR, Mathur R, van Vuuren DP. 2014. A new scenario framework for climate change research: the concept of shared socioeconomic pathways. Clim Change, 122(3): 387-400. https://doi.org/10.1007/s10584-013-0905-2
  • Oxman R. 2014. Theories of the digital in architecture. Routledge, Taylor & Francis Group, London, pp: 72.
  • Sadek MR, Mohamed NAG. 2023. Artificial Intelligence as a pedagogical tool for architectural education: what does the empirical evidence tell us?. MSA Eng J, 2(2): 133-148. https://doi.org/10.21608/msaeng.2023.291867
  • Schumacher P. 2011. The autopoiesis of architecture: a new framework for architecture. John Wiley & Sons Limited, Chichester, UK, pp: 480.
  • Seli P, Ragnhildstveit A, Orwig W, Bellaiche L, Spooner S, Barr N. 2024. Beyond the brush: human versus AI creativity in the realm of generative art. Psychol Aesthet Creat Arts, pp:1-9. https://doi.org/10.31234/osf.io/vgzhj
  • SPM. 2019. Summary for policymakers-special report on climate change and land. URL: https://www.ipcc.ch/srccl/chapter/summary-for-policymakers/ (accessed date: January 17, 2025).
  • Steinfeld K. 2021. Significant others: machine learning as actor, material, and provocateur in art and design. In: The routledge companion to artificial intelligence in architecture. Routledge, New York, pp: 3-12.
  • Tafahomi R. 2022. Educational behavior of the students in the design studios during the pandemic time. Int J Soc Sci Educ Res, 8(4): 352-362. Article 4. https://doi.org/10.24289/ijsser.1164545
  • Takva Y, Takva C, Goksen F. 2023. A contemporary house proposal: structural analysis of wood and steel bungalows. ETASR, 13(3): 11032-11035. https://doi.org/10.48084/etasr.5896
  • Tanugraha S. 2023. Review using artificial intelligence-generating images: exploring material ideas from midjourney to improve vernacular designs. J Artif Intell Archit, 2(1): 48-57. https://doi.org/10.24002/jarina.v2i2.7537
  • Tuztaşi U, Koç P. 2019. “Design like him/her” method in the context of experimentality of design studies. Int Ref J Des Archit, 17: 104-137. https://doi.org/10.17365/TMD.2019.2.1
  • UNDP. 2023. The climate dictionary: an everyday guide to climate change | UNDP climate promise. URL: https://climatepromise.undp.org/news-and-stories/climate-dictionary-everyday-guide-climate-change (accessed date: February 23, 2025).
  • van Vuuren DP, Kriegler E, O’Neill BC, Ebi KL, Riahi K, Carter TR, Edmonds J, Hallegatte S, Kram T, Mathur R, Winkler H. 2014. A new scenario framework for climate change research: scenario matrix architecture. Clim Change, 122(3): 373-386. https://doi.org/10.1007/s10584-013-0906-1
  • Viliunas G, Grazuleviciute-Vileniske I. 2022. Shape-finding in biophilic architecture: application of AI-based tool. Archit Urban Plan, 18(1): 68-75. https://doi.org/10.2478/aup-2022-0007
  • Yaman Y, Tokuç A, Köktürk G. 2022. Towards carbon neutral settlements with algae. Int Ref J Des Archit, 25: 1-32. https://doi.org/10.17365/TMD.2022.TURKEY.25.01
  • Yıldırım E. 2023. Comparative analysis of leonardo AI, midjourney, and Dall-E: AI's perspective on future cities. Urbanizm, 28: 82-96. https://doi.org/10.58225/urbanizm.2023-28-82-96
  • Yılmaz N. 2023. Sensory experience in architectural design education: an experimental visual perception study with serial vision method. Soc Sci Dev J, 8(38): 229-239. https://doi.org/10.31567/ssd.939
  • Yoshimura Y, Cai BY, Wang Z, Ratti C. 2018. Deep learning architect: classification for architectural design through the eye of artificial intelligence. URL: https://arxiv.org/abs/1812.01714 (accessed date: February 23, 2025).
Toplam 46 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Görsel İletişimde Bilgisayar Destekli Tasarım, Görsel Tasarım, Görsel İletişim Tasarımı (Diğer)
Bölüm Research Articles
Yazarlar

Fulya Gökşen Takva 0000-0002-9754-0956

Burcu Buram Çolak Demirel 0000-0001-7932-6422

İdil Ayçam 0000-0001-7170-5436

Erken Görünüm Tarihi 12 Kasım 2025
Yayımlanma Tarihi 15 Kasım 2025
Gönderilme Tarihi 9 Ağustos 2025
Kabul Tarihi 3 Ekim 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 8 Sayı: 6

Kaynak Göster

APA Gökşen Takva, F., Çolak Demirel, B. B., & Ayçam, İ. (2025). Integration of Artificial Intelligence into the Architectural Design Process: Architectural Studio Experience. Black Sea Journal of Engineering and Science, 8(6), 1874-1882. https://doi.org/10.34248/bsengineering.1761624
AMA Gökşen Takva F, Çolak Demirel BB, Ayçam İ. Integration of Artificial Intelligence into the Architectural Design Process: Architectural Studio Experience. BSJ Eng. Sci. Kasım 2025;8(6):1874-1882. doi:10.34248/bsengineering.1761624
Chicago Gökşen Takva, Fulya, Burcu Buram Çolak Demirel, ve İdil Ayçam. “Integration of Artificial Intelligence into the Architectural Design Process: Architectural Studio Experience”. Black Sea Journal of Engineering and Science 8, sy. 6 (Kasım 2025): 1874-82. https://doi.org/10.34248/bsengineering.1761624.
EndNote Gökşen Takva F, Çolak Demirel BB, Ayçam İ (01 Kasım 2025) Integration of Artificial Intelligence into the Architectural Design Process: Architectural Studio Experience. Black Sea Journal of Engineering and Science 8 6 1874–1882.
IEEE F. Gökşen Takva, B. B. Çolak Demirel, ve İ. Ayçam, “Integration of Artificial Intelligence into the Architectural Design Process: Architectural Studio Experience”, BSJ Eng. Sci., c. 8, sy. 6, ss. 1874–1882, 2025, doi: 10.34248/bsengineering.1761624.
ISNAD Gökşen Takva, Fulya vd. “Integration of Artificial Intelligence into the Architectural Design Process: Architectural Studio Experience”. Black Sea Journal of Engineering and Science 8/6 (Kasım2025), 1874-1882. https://doi.org/10.34248/bsengineering.1761624.
JAMA Gökşen Takva F, Çolak Demirel BB, Ayçam İ. Integration of Artificial Intelligence into the Architectural Design Process: Architectural Studio Experience. BSJ Eng. Sci. 2025;8:1874–1882.
MLA Gökşen Takva, Fulya vd. “Integration of Artificial Intelligence into the Architectural Design Process: Architectural Studio Experience”. Black Sea Journal of Engineering and Science, c. 8, sy. 6, 2025, ss. 1874-82, doi:10.34248/bsengineering.1761624.
Vancouver Gökşen Takva F, Çolak Demirel BB, Ayçam İ. Integration of Artificial Intelligence into the Architectural Design Process: Architectural Studio Experience. BSJ Eng. Sci. 2025;8(6):1874-82.

                           24890