Dynamic scaffolding: exploring the role of artificial intelligence in urban design education
Abstract Purpose This study examines the role of Artificial Intelligence (AI) in urban design education, focusing on how AI supports various stages of the design process using scaffolding theory. Methods A multiple-case study approach was adopted, examining six AI-integrated urban design education p...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-07-01
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| Series: | Frontiers of Urban and Rural Planning |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s44243-025-00060-7 |
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| Summary: | Abstract Purpose This study examines the role of Artificial Intelligence (AI) in urban design education, focusing on how AI supports various stages of the design process using scaffolding theory. Methods A multiple-case study approach was adopted, examining six AI-integrated urban design education projects. Data were collected through semi-structured interviews with 6 key stakeholders, including students, educators, and urban design professionals. MAXQDA software was employed to analyse AI’s involvement across different phases of the scaffolding process, including diagnostic assessment, establishment of shared understanding, provision of targeted support, gradual withdrawal of assistance and promotion of independent performance. Results The findings reveal that AI effectively enhances student engagement (F1: Recruitment) and simplifies task execution (F2: Reduction in degrees of freedom). AI’s visual demonstration capabilities (F6: Demonstration) also support early-stage design learning. However, AI proves less effective in helping students set learning goals (F3: Direction maintenance) and make complex decisions. Its effectiveness varied depending on the context of the application. Conclusions The study proposes the “Dynamic Scaffolding Model of AI Involvement in Design Education,” providing educators with a flexible framework to adapt AI's role. While AI improves engagement and task efficiency, it falls short of supporting independent decision-making. Future research will explore broader applications of AI in urban design education and address its ethical implications. |
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| ISSN: | 2731-6661 |