Abstract
The field of artificial intelligence (AI) in architectural design (AIEd) has experienced significant growth, and there is great potential for the application of Generative AI (GAI) in architectural design education. However, addressing challenges associated with AI is important. These include overhyped speculation, hidden inherent drawbacks such as fairness and ethics, and a trend of lacking human interaction when AI is involved. To tackle these issues, this paper introduces a triangulated research framework encompassing three key perspectives: vision, technology, and user acceptance. This framework aligns with Human-computer Interaction (HCI) principles, AI technology development, and past experiences in AIEd. By adopting this multi-perspective analysis approach, the paper aims to comprehensively understand the phenomena surrounding AI in architectural design. Furthermore, the research presented in this paper goes beyond theoretical discussions and illustrates how the research findings are applied in practice. It showcases the design of an ongoing architectural design course that incorporates the insights gained from the research. Three key observations from the ongoing designed modules indicate the need to shift the focus towards integrating multi-modal AIs and existing parametric tools. Secondly, it is essential to emphasise AIs as design partners rather than making assumptions about AIs’ specific uses at different stages. Lastly, providing user-friendly tools and theoretical foundations motivates students to explore beyond the design process, expanding their research and design boundaries.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.