工作流程
转化式学习
计算机科学
建筑
生成设计
概念化
功能可见性
软件工程
工程类
人工智能
数据科学
人机交互
社会学
视觉艺术
艺术
公制(单位)
数据库
运营管理
教育学
作者
Yujie Cao,Mohammad Azhan Abdul Aziz,Wan Nur Rukiah Mohd Arshard
标识
DOI:10.1177/14780771241270257
摘要
This study explored integrating Stable Diffusion, a generative artificial intelligence (AI), into architectural design workflows, focusing on its impact on design process and students’ learning experiences. A comparative analysis revealed an optimized workflow incorporating Stable Diffusion, which enhanced design exploration, conceptualization and visualization in early design stages. Demonstrations showcased text/image-to-image capabilities generating architectural visuals. Employing a mixed-methods research design, which encompasses comparative analysis and a thorough questionnaire-based exploration, the research sheds light on the challenges and opportunities of integrating Stable Diffusion into architectural education and practice. While receptive, some concerns existed around AI automation risks. The paper contributes to a deeper understanding of the transformative potential of generative AI, particularly Stable Diffusion, in reshaping workflows and educational dimensions of architectural design. Findings advise integrating emerging AI like Stable Diffusion into architecture curricula to equip students for AI-driven industries, emphasizing judicious human-AI collaboration. Further research could continue optimizing hybrid human-AI design workflows.
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