Research Article
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Artificial Intelligence as a Pedagogical Tool for Architectural Design Education

Year 2024, Volume: 6 Issue: 2, 219 - 229, 20.12.2024
https://doi.org/10.46474/jds.1533480

Abstract

Artificial intelligence (AI) is increasingly influencing art and design, with tools like ChatGPT, DALL.E, and Midjourney transforming the way designers create visual content from written descriptions. Since its launch, AI-powered systems have sparked widespread interest and expanded production practices in design and artistic creativity. This transition has ushered in a new era of co-authorship, in which human designers and AI systems collaborate to reshape the boundaries of design. The introduction of language-based diffusion models has enabled a harmonic integration of language and visual elements, resulting in creative design paradigms. However, this incorporation of AI raises serious concerns about the cultural and social relevance of AI-generated designs, which may become estranged from human contexts if heavily dependent on algorithms. The representation of architectural knowledge is also evolving, as AI allows for a return to textual and mathematical tools, rather than traditional visual representation methods. This transition creates substantial challenges and possibilities for architectural education, particularly in design studios. The integration of AI into design curricula has the potential to reshape architectural education, necessitating that educators adapt to technology advances. This study investigates these developments, providing insights into the evolving landscape of design pedagogy in the age of AI and contributing to the continuing debate about the role of AI in design and architecture.

References

  • Abdullah, K. K., & Hassnpour, B. (2021). Digital design implications: a comparative study of architecture education curriculum and practices in leading architecture firms. International Journal of Technology and Design Education 31, 401-420.
  • Aish, R. (2013). First Build Your Tools. Inside Smartgeometry: Expanding the Architectural Possibilities of Computational Design, 36-49. https://doi.org/10.1002/9781118653074.ch2
  • Başarır, L. (2022). Modelling AI in Architectural Education. Gazi University Journal of Science, 35(4), 1260-1278.
  • Başarır, L., & Erol, K. (2021). Briefing AI: From Architectural Design Brief Texts to Architectural design Sketches The 9th ASCAAD International Conference,
  • Billie, P. (2002). From CAD to Communication: Connecting the Real and the Virtual. In Design E-ducation : Proceedings of the 20th eCAADe conference (pp. 156-159).
  • Burry, M. (2011). Scripting Cultures: Architectural Design and Programming. John Wiley& Sons Ltd.
  • Burry, M. (2014). From Descriptive Geometry to Smartgeometry: First Steps Towards Digital Architecture. In (pp. 154-165).
  • Carpo, M. (2003). Drawing with Numbers: Geometry and Numeracy in Early Modern Architectural Design. Journal of the Society of Architectural Historians, 62(4), 448-469. https://doi.org/10.2307/3592497
  • Carpo, M. (2012). The Digital Turn in Architecture 1992-2012 (C. Mario, Ed.). Wiley.
  • Castro Pena, M. L., Carballal, A., Rodríguez-Fernández, N., Santos, I., & Romero, J. (2021). Artificial intelligence applied to conceptual design. A review of its use in architecture. Automation in Construction, 124, 103550. https://doi.org/https://doi.org/10.1016/j.autcon.2021.103550
  • Crawford, J., Cowling, M., Ashton-Hay, S. A., Kelder, J.-A., & Middleton, R. (2023). Artificial Intelligence and Authorship Editor Policy: ChatGPT, Bard Bing AI, and beyond. Journal of university teaching and learning practice, 20(5). https://doi.org/10.53761/1.20.5.01
  • Dearden, A. (2006). Designing as a conversation with digital materials. Design Studies, 27, 399-421.
  • Dutton, T. A. (1991). The hidden curriculum and the design studio: toward a critical studio pedagogy. In T. A. Dutton (Ed.), Voices in Architectural Education: Cultural Politics and Pedagogy (pp. 165-194). Bergin & Garvey.
  • Ekici, B., Cubukcuoglu, C., Turrin, M., & Sariyildiz, I. S. (2019). Performative computational architecture using swarm and evolutionary optimisation: A review. Building and Environment, 147, 356-371. https://doi.org/https://doi.org/10.1016/j.buildenv.2018.10.023
  • Flechtner, R., & Stankowski, A. (2023). AI Is Not a Wildcard: Challenges for Integrating AI into the Design Curriculum. Proceedings of the 5th Annual Symposium on HCI Education,
  • Gal, R., Alaluf, Y., Atzmon, Y., Patashnik, O., Bermano, A. H., Chechik, G., & Cohen-Or, D. (2022). An image is worth one word: Personalizing text-to-image generation using textual inversion. arXiv preprint arXiv:2208.01618.
  • Gao, J., Shen, T., Wang, Z., Chen, W., Yin, K., Li, D., Litany, O., Gojcic, Z., & Fidler, S. (2022). Get3d: A generative model of high quality 3d textured shapes learned from images. Advances In Neural Information Processing Systems, 35, 31841-31854.
  • Gero, J. S. (2012). Artificial Intelligence in Design ’00. Springer Science & Business Media. https://books.google.com.tr/books?id=YfWpCAAAQBAJ
  • Goldschmidt, G. (2002). 'One-on-One': A Pedagogic Base for Design Instruction in the Studio. In D. Durling & J. Shackleton (Eds.), Proceedings of 'Common Ground', Design Research Society International Conferernce (pp. 430-434). Staffordshire University Press.
  • Hardman, P. D. (2022). The Transformative Potential of the Ongoing Digital Revolution for the Studio Model of Design Education. . In A. Afonso, L. Morgado, & L. Roque (Eds.), Impact of Digital Transformation in Teacher Training Models (pp. 160-177). IGI Global. https://doi.org/https://doi.org/10.4018/978-1-7998-9538-1.ch009
  • Hariri, N., Nader, R. B., & Hariri Haykal, S. (2020). Technological Change and Future Skill-Shortages in Engineering and Architecture Education: Lessons from Lebanon ICDEc 2020: Digital Economy. Emerging Technologies and Business Innovation,
  • Hewitt, M. (1985). Representational Forms and Modes of Conception; an Approach to the History of Architectural Drawing. Journal of Architectural Education, 39(2), 2-9. https://doi.org/10.1080/10464883.1985.10758387
  • Jaime, A., da Silva, T., & Tsigaris, P. P. (2023). Human‐ and AI‐based authorship: Principles and ethics. Learned Publishing. https://doi.org/doi: 10.1002/leap.1547
  • Karakaya, A. F., & Demirkan, H. (2015). Collaborative digital environments to enhance the creativity of designers. Computers in Human Behavior, 42, 176-186. https://doi.org/10.1016/j.chb.2014.03.029 (Digital Creativity: New Frontier for Research and Practice)
  • Kavakoglu, A. A., Almaç, B., Eser, B., & Alaçam, S. (2022). AI Driven Creativity in Early Design Education.
  • Kee, T., Kuys, B., & King, R. (2024). Generative Artificial Intelligence to Enhance Architecture Education to Develop Digital Literacy and Holistic Competency. Journal of Artificial Intelligence in Architecture, 3(1), 24-41.
  • Khean, N., Fabbri, A., & Haeusler, M. H. (2018). Learning machine learning as an architect, how to. Proceedings of the 36th eCAADe Conference,
  • Kolarevic, B. (2013). Parametric Evolution. Inside Smartgeometry: Expanding the Architectural Possibilities of Computational Design, 50-59. https://doi.org/10.1002/9781118653074.ch3
  • Leach, N. (2018). Design in the age of artificial intelligence. Landscape Architecture Frontiers, 6(2), 8-20.
  • Leach, N. (2022). Architectural Hallucinations: What Can AI Tell Us About the Mind of an Architect? Architectural Design, 92(3), 66-71.
  • Ledewitz, S. (1985). Models of Design in Studio Teaching. Journal of Architectural Education (1984-), 38(2), 2. https://doi.org/10.2307/1424811
  • Lee, J. (2014). The Integrated Design Process from the Facilitator's Perspective. International Journal of Art & Design Education, 33(1), 141-156. https://doi.org/10.1111/j.1476-8070.2014.12000.x
  • Mark, E., Gross, M., & Goldschmidt, G. (2008). A Perspective on Computer Aided Design after Four Decades. eCAADe 26,
  • McCormack, J., Hutchings, P., Gifford, T., Yee-King, M., Llano, M. T., & D’inverno, M. (2020). Design considerations for real-time collaboration with creative artificial intelligence. Organised Sound, 25(1), 41-52.
  • Necipoğlu-Kafadar, G. (1986). Plans and Models in 15th- and 16th-Century Ottoman Architectural Practice. Journal of the Society of Architectural Historians, 45(3), 224-243. https://doi.org/10.2307/990160
  • Ogata, B., & Ogawa, M.-B. (2023). Augmented Cognition Instructional Design for Studio-Based Learning. In D. D. Schmorrow & C. M. Fidopiastis, Augmented Cognition Cham.
  • Oxman, R. (2006). Theory and design in the first digital age. Design Studies, 27(3), 229-265. https://doi.org/10.1016/j.destud.2005.11.002
  • Oxman, R. (2008). Digital architecture as a challenge for design pedagogy: theory, knowledge, models and medium. Design Studies, 29(2), 99-120. https://doi.org/10.1016/j.destud.2007.12.003
  • Oxman, R. (2017). Thinking difference: Theories and models of parametric design thinking. Design Studies, 52, 4-39. https://doi.org/10.1016/j.destud.2017.06.001 (Parametric Design Thinking)
  • Picon, A. (2011). Architecture and Mathematics: Between Hubris and Restraint. Architectural Design, 81(4), 28-35. https://doi.org/10.1002/ad.1265
  • Ploennigs, J., & Berger, M. (2023). Ai art in architecture. AI in Civil Engineering, 2(1), 8.
  • Radziszewski, K., & Cudzik, J. (2019). Parametric design in architectural education. World Transactions on Engineering and Technology Education, 17, 448-453.
  • Sadek, M. (2023). Artificial Intelligence as a pedagogical tool for architectural education: What does the empirical evidence tell us? MSA Engineering Journal, 2(2), 133-148. https://doi.org/10.21608/msaeng.2023.291867
  • Salman, H., Laing, R., & Conniff, A. (2008). The Changing Role of CAAD in the Architectural Design Studio. The Built and Human Environment Review, 1, 25-39.
  • Schmitt, G. (1997). Design Medium — Design Object. In R. Junge (Ed.), CAAD futures 1997 (pp. 3-13). Springer Netherlands. http://link.springer.com/10.1007/978-94-011-5576-2_1
  • Schön, D. (1983). The reflective practitioner. How Professionals Think in Action.
  • Schön, D. A. (1985). The Design Studio. An Exploration of its Traditions and Potentials. RIBA Publications Limited.
  • Schumacher, P. (2011). Parametricism and the Autopoiesis of Architecture. Log 21, 62-71. https://www.patrikschumacher.com/Texts/Parametricism%20and%20the%20Autopoiesis%20of%20Architecture.html
  • Smith, A., Schroeder, H., Epstein, Z., Cook, M., Colton, S., & Lippman, A. (2023). Trash to Treasure: Using text-to-image models to inform the design of physical artefacts 37th AAAI Conference on Artificial Intelligence,
  • Şapcı, B., & Pektaş, Ş. T. (2021). Integrating user experience knowledge into early architectural design processes through machine learning. JCoDe: Journal of Computational Design, 2(1), 67-94.
  • Tianran, T., Pengfei, L., & Qiheng, T. (2022). New Strategies and Practices of Design Education Under the Background of Artificial Intelligence Technology: Online Animation Design Studio. Frontiers in Psychology. https://doi.org/doi: 10.3389/fpsyg.2022.767295
  • Tucker-Raymond, E., Cassidy, M., & Puttick, G. (2021). Science teachers can teach computational thinking through distributed expertise. Computers & Education, 173, 104284. https://doi.org/10.1016/j.compedu.2021.104284
  • Uluoğlu, B. (1996). Representation of design knowledge in studio critiques. Proceedings of Descriptive Models of Design, 1-5.
  • Uncu, E. Ö., & Çağdaş, G. (2022). The Pedagogical Alignment of Computational Thinking to Architecture Education for the 21st Century Learners. JCoDe: Journal of Computational Design, 3(2), 159-172. https://doi.org/10.53710/jcode.1146
  • Yıldırım, E. (2023a, September 28-29, 2023). A Crisis in Education: Navigating the Technological Abbys in Architectural Design Studio 2. International Çankaya Scientific Studies Congress, Ankara.
  • Yıldırım, E. (2023b). Mimarlıkta Yapay Zeka. In A. Özen & D. Muhammet (Eds.), Dijital dönüşüm ve Değişen Uygulamalar (pp. 561-578). Efe Akademi.
  • Yurman, P., & Reddy, A. V. (2022). Drawing Conversations Mediated by AI Creativity and Cognition,
  • Zhang, C., Wang, W., Pangaro, P., Martelaro, N., & Byrne, D. (2023). Generative Image AI Using Design Sketches as input: Opportunities and Challenges Proceedings of the 15th Conference on Creativity and Cognition, <conf-loc>, <city>Virtual Event</city>, <country>USA</country>, </conf-loc>. https://doi.org/10.1145/3591196.3596820
Year 2024, Volume: 6 Issue: 2, 219 - 229, 20.12.2024
https://doi.org/10.46474/jds.1533480

Abstract

References

  • Abdullah, K. K., & Hassnpour, B. (2021). Digital design implications: a comparative study of architecture education curriculum and practices in leading architecture firms. International Journal of Technology and Design Education 31, 401-420.
  • Aish, R. (2013). First Build Your Tools. Inside Smartgeometry: Expanding the Architectural Possibilities of Computational Design, 36-49. https://doi.org/10.1002/9781118653074.ch2
  • Başarır, L. (2022). Modelling AI in Architectural Education. Gazi University Journal of Science, 35(4), 1260-1278.
  • Başarır, L., & Erol, K. (2021). Briefing AI: From Architectural Design Brief Texts to Architectural design Sketches The 9th ASCAAD International Conference,
  • Billie, P. (2002). From CAD to Communication: Connecting the Real and the Virtual. In Design E-ducation : Proceedings of the 20th eCAADe conference (pp. 156-159).
  • Burry, M. (2011). Scripting Cultures: Architectural Design and Programming. John Wiley& Sons Ltd.
  • Burry, M. (2014). From Descriptive Geometry to Smartgeometry: First Steps Towards Digital Architecture. In (pp. 154-165).
  • Carpo, M. (2003). Drawing with Numbers: Geometry and Numeracy in Early Modern Architectural Design. Journal of the Society of Architectural Historians, 62(4), 448-469. https://doi.org/10.2307/3592497
  • Carpo, M. (2012). The Digital Turn in Architecture 1992-2012 (C. Mario, Ed.). Wiley.
  • Castro Pena, M. L., Carballal, A., Rodríguez-Fernández, N., Santos, I., & Romero, J. (2021). Artificial intelligence applied to conceptual design. A review of its use in architecture. Automation in Construction, 124, 103550. https://doi.org/https://doi.org/10.1016/j.autcon.2021.103550
  • Crawford, J., Cowling, M., Ashton-Hay, S. A., Kelder, J.-A., & Middleton, R. (2023). Artificial Intelligence and Authorship Editor Policy: ChatGPT, Bard Bing AI, and beyond. Journal of university teaching and learning practice, 20(5). https://doi.org/10.53761/1.20.5.01
  • Dearden, A. (2006). Designing as a conversation with digital materials. Design Studies, 27, 399-421.
  • Dutton, T. A. (1991). The hidden curriculum and the design studio: toward a critical studio pedagogy. In T. A. Dutton (Ed.), Voices in Architectural Education: Cultural Politics and Pedagogy (pp. 165-194). Bergin & Garvey.
  • Ekici, B., Cubukcuoglu, C., Turrin, M., & Sariyildiz, I. S. (2019). Performative computational architecture using swarm and evolutionary optimisation: A review. Building and Environment, 147, 356-371. https://doi.org/https://doi.org/10.1016/j.buildenv.2018.10.023
  • Flechtner, R., & Stankowski, A. (2023). AI Is Not a Wildcard: Challenges for Integrating AI into the Design Curriculum. Proceedings of the 5th Annual Symposium on HCI Education,
  • Gal, R., Alaluf, Y., Atzmon, Y., Patashnik, O., Bermano, A. H., Chechik, G., & Cohen-Or, D. (2022). An image is worth one word: Personalizing text-to-image generation using textual inversion. arXiv preprint arXiv:2208.01618.
  • Gao, J., Shen, T., Wang, Z., Chen, W., Yin, K., Li, D., Litany, O., Gojcic, Z., & Fidler, S. (2022). Get3d: A generative model of high quality 3d textured shapes learned from images. Advances In Neural Information Processing Systems, 35, 31841-31854.
  • Gero, J. S. (2012). Artificial Intelligence in Design ’00. Springer Science & Business Media. https://books.google.com.tr/books?id=YfWpCAAAQBAJ
  • Goldschmidt, G. (2002). 'One-on-One': A Pedagogic Base for Design Instruction in the Studio. In D. Durling & J. Shackleton (Eds.), Proceedings of 'Common Ground', Design Research Society International Conferernce (pp. 430-434). Staffordshire University Press.
  • Hardman, P. D. (2022). The Transformative Potential of the Ongoing Digital Revolution for the Studio Model of Design Education. . In A. Afonso, L. Morgado, & L. Roque (Eds.), Impact of Digital Transformation in Teacher Training Models (pp. 160-177). IGI Global. https://doi.org/https://doi.org/10.4018/978-1-7998-9538-1.ch009
  • Hariri, N., Nader, R. B., & Hariri Haykal, S. (2020). Technological Change and Future Skill-Shortages in Engineering and Architecture Education: Lessons from Lebanon ICDEc 2020: Digital Economy. Emerging Technologies and Business Innovation,
  • Hewitt, M. (1985). Representational Forms and Modes of Conception; an Approach to the History of Architectural Drawing. Journal of Architectural Education, 39(2), 2-9. https://doi.org/10.1080/10464883.1985.10758387
  • Jaime, A., da Silva, T., & Tsigaris, P. P. (2023). Human‐ and AI‐based authorship: Principles and ethics. Learned Publishing. https://doi.org/doi: 10.1002/leap.1547
  • Karakaya, A. F., & Demirkan, H. (2015). Collaborative digital environments to enhance the creativity of designers. Computers in Human Behavior, 42, 176-186. https://doi.org/10.1016/j.chb.2014.03.029 (Digital Creativity: New Frontier for Research and Practice)
  • Kavakoglu, A. A., Almaç, B., Eser, B., & Alaçam, S. (2022). AI Driven Creativity in Early Design Education.
  • Kee, T., Kuys, B., & King, R. (2024). Generative Artificial Intelligence to Enhance Architecture Education to Develop Digital Literacy and Holistic Competency. Journal of Artificial Intelligence in Architecture, 3(1), 24-41.
  • Khean, N., Fabbri, A., & Haeusler, M. H. (2018). Learning machine learning as an architect, how to. Proceedings of the 36th eCAADe Conference,
  • Kolarevic, B. (2013). Parametric Evolution. Inside Smartgeometry: Expanding the Architectural Possibilities of Computational Design, 50-59. https://doi.org/10.1002/9781118653074.ch3
  • Leach, N. (2018). Design in the age of artificial intelligence. Landscape Architecture Frontiers, 6(2), 8-20.
  • Leach, N. (2022). Architectural Hallucinations: What Can AI Tell Us About the Mind of an Architect? Architectural Design, 92(3), 66-71.
  • Ledewitz, S. (1985). Models of Design in Studio Teaching. Journal of Architectural Education (1984-), 38(2), 2. https://doi.org/10.2307/1424811
  • Lee, J. (2014). The Integrated Design Process from the Facilitator's Perspective. International Journal of Art & Design Education, 33(1), 141-156. https://doi.org/10.1111/j.1476-8070.2014.12000.x
  • Mark, E., Gross, M., & Goldschmidt, G. (2008). A Perspective on Computer Aided Design after Four Decades. eCAADe 26,
  • McCormack, J., Hutchings, P., Gifford, T., Yee-King, M., Llano, M. T., & D’inverno, M. (2020). Design considerations for real-time collaboration with creative artificial intelligence. Organised Sound, 25(1), 41-52.
  • Necipoğlu-Kafadar, G. (1986). Plans and Models in 15th- and 16th-Century Ottoman Architectural Practice. Journal of the Society of Architectural Historians, 45(3), 224-243. https://doi.org/10.2307/990160
  • Ogata, B., & Ogawa, M.-B. (2023). Augmented Cognition Instructional Design for Studio-Based Learning. In D. D. Schmorrow & C. M. Fidopiastis, Augmented Cognition Cham.
  • Oxman, R. (2006). Theory and design in the first digital age. Design Studies, 27(3), 229-265. https://doi.org/10.1016/j.destud.2005.11.002
  • Oxman, R. (2008). Digital architecture as a challenge for design pedagogy: theory, knowledge, models and medium. Design Studies, 29(2), 99-120. https://doi.org/10.1016/j.destud.2007.12.003
  • Oxman, R. (2017). Thinking difference: Theories and models of parametric design thinking. Design Studies, 52, 4-39. https://doi.org/10.1016/j.destud.2017.06.001 (Parametric Design Thinking)
  • Picon, A. (2011). Architecture and Mathematics: Between Hubris and Restraint. Architectural Design, 81(4), 28-35. https://doi.org/10.1002/ad.1265
  • Ploennigs, J., & Berger, M. (2023). Ai art in architecture. AI in Civil Engineering, 2(1), 8.
  • Radziszewski, K., & Cudzik, J. (2019). Parametric design in architectural education. World Transactions on Engineering and Technology Education, 17, 448-453.
  • Sadek, M. (2023). Artificial Intelligence as a pedagogical tool for architectural education: What does the empirical evidence tell us? MSA Engineering Journal, 2(2), 133-148. https://doi.org/10.21608/msaeng.2023.291867
  • Salman, H., Laing, R., & Conniff, A. (2008). The Changing Role of CAAD in the Architectural Design Studio. The Built and Human Environment Review, 1, 25-39.
  • Schmitt, G. (1997). Design Medium — Design Object. In R. Junge (Ed.), CAAD futures 1997 (pp. 3-13). Springer Netherlands. http://link.springer.com/10.1007/978-94-011-5576-2_1
  • Schön, D. (1983). The reflective practitioner. How Professionals Think in Action.
  • Schön, D. A. (1985). The Design Studio. An Exploration of its Traditions and Potentials. RIBA Publications Limited.
  • Schumacher, P. (2011). Parametricism and the Autopoiesis of Architecture. Log 21, 62-71. https://www.patrikschumacher.com/Texts/Parametricism%20and%20the%20Autopoiesis%20of%20Architecture.html
  • Smith, A., Schroeder, H., Epstein, Z., Cook, M., Colton, S., & Lippman, A. (2023). Trash to Treasure: Using text-to-image models to inform the design of physical artefacts 37th AAAI Conference on Artificial Intelligence,
  • Şapcı, B., & Pektaş, Ş. T. (2021). Integrating user experience knowledge into early architectural design processes through machine learning. JCoDe: Journal of Computational Design, 2(1), 67-94.
  • Tianran, T., Pengfei, L., & Qiheng, T. (2022). New Strategies and Practices of Design Education Under the Background of Artificial Intelligence Technology: Online Animation Design Studio. Frontiers in Psychology. https://doi.org/doi: 10.3389/fpsyg.2022.767295
  • Tucker-Raymond, E., Cassidy, M., & Puttick, G. (2021). Science teachers can teach computational thinking through distributed expertise. Computers & Education, 173, 104284. https://doi.org/10.1016/j.compedu.2021.104284
  • Uluoğlu, B. (1996). Representation of design knowledge in studio critiques. Proceedings of Descriptive Models of Design, 1-5.
  • Uncu, E. Ö., & Çağdaş, G. (2022). The Pedagogical Alignment of Computational Thinking to Architecture Education for the 21st Century Learners. JCoDe: Journal of Computational Design, 3(2), 159-172. https://doi.org/10.53710/jcode.1146
  • Yıldırım, E. (2023a, September 28-29, 2023). A Crisis in Education: Navigating the Technological Abbys in Architectural Design Studio 2. International Çankaya Scientific Studies Congress, Ankara.
  • Yıldırım, E. (2023b). Mimarlıkta Yapay Zeka. In A. Özen & D. Muhammet (Eds.), Dijital dönüşüm ve Değişen Uygulamalar (pp. 561-578). Efe Akademi.
  • Yurman, P., & Reddy, A. V. (2022). Drawing Conversations Mediated by AI Creativity and Cognition,
  • Zhang, C., Wang, W., Pangaro, P., Martelaro, N., & Byrne, D. (2023). Generative Image AI Using Design Sketches as input: Opportunities and Challenges Proceedings of the 15th Conference on Creativity and Cognition, <conf-loc>, <city>Virtual Event</city>, <country>USA</country>, </conf-loc>. https://doi.org/10.1145/3591196.3596820
There are 58 citations in total.

Details

Primary Language English
Subjects Architecture (Other), Information Technology in Design, Design (Other)
Journal Section Research Articles
Authors

Cansu Günaydın 0000-0002-8615-0952

Altuğ Kasalı 0000-0001-5931-0490

Fehmi Doğan 0000-0003-4754-1907

Early Pub Date December 13, 2024
Publication Date December 20, 2024
Submission Date August 16, 2024
Acceptance Date September 13, 2024
Published in Issue Year 2024 Volume: 6 Issue: 2

Cite

APA Günaydın, C., Kasalı, A., & Doğan, F. (2024). Artificial Intelligence as a Pedagogical Tool for Architectural Design Education. Journal of Design Studio, 6(2), 219-229. https://doi.org/10.46474/jds.1533480

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