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Designing with AI: Integrating Image-Generative AI into Conceptual Design in a CAD Class

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Conference

2024 ASEE Annual Conference & Exposition

Location

Portland, Oregon

Publication Date

June 23, 2024

Start Date

June 23, 2024

End Date

July 12, 2024

Conference Session

Design in Engineering Education Division (DEED) - Best in DEED

Tagged Division

Design in Engineering Education Division (DEED)

Permanent URL

https://peer.asee.org/47146

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Paper Authors

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Wangda Zhu University of Florida

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Wangda Zhu is a Post-doc Associate in School of Teaching and Learning at University of Florida. He got his PhD in Human Behavior and Design from Cornell University, focusing on educational technology, and a Bachelor of Engineering from Zhejiang University, China. His research interests include AI in STEM education, learning communities, and learning analytics. His previous work has been published in British Journal of Educational Technology, Interactive Learning Environments, etc.

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Rui Guo University of Florida

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Dr. Rui Guo is an instructional assistant professor of the Department of Engineering Education in the UF Herbert Wertheim College of Engineering. Her research interests include data science & CS education, Fair Artificial Intelligence and Experiential learning.

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Yuanzhi Wang Cornell University

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Yuanzhi Wang is a Ph.D. student in Human Behavior and Design at Cornell University. His research interests revolve around proximity and innovation studies within higher education learning environments.

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Wanli Xing University of Florida

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Wanli Xing is the Informatics for Education Associate Professor of Educational Technology at University of Florida. His research interests are artificial intelligence, learning analytics, STEM education and online learning.

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Eddy Man Kim Cornell University

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Practitioner, researcher, educator, and technologist in architectural, media, web, brand, and experience design.

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Chenglu Li The University of Utah

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Chenglu Li is an Assistant Professor in Educational Technology and Instructional Design at the University of Utah. He is interested in extending and developing algorithmic and design strategies to promote fair, accountable, and transparent (FAccT) AI in STEM education.

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Abstract

Although image-generative AI has sparked heated discussion among engineers and designers, its role in CAD (computer aided design) education, particularly during the conceptual design phase, remains understudied. To address this, we examine the integration of image-generative AI into the early stages of design in a CAD class. Specifically, we developed an AI-integrated curriculum featuring an in-class workshop introducing the Midjourney tool for design, a take-home assignment for hands-on AI design practice, and a subsequent evaluation session for design critique. This curriculum was implemented with 20 students from a CAD class in a human centered design department at a research-intensive university. Employing a mixed-methods approach, we collected and analyzed data from surveys, interviews, and students’ interaction logs with Midjourney to gain insights into their behaviors and perceptions concerning the integration of generative AI in CAD. Through coding students’ logs and responses, we can identify several types of workflows on designing with AI and students' perceptions of AI integration in curriculums. The results offer valuable insights for the integration of generative AI in CAD education and suggest potential directions for future AI-assisted design tools and workflows.

Zhu, W., & Guo, R., & Wang, Y., & Xing, W., & Kim, E. M., & Li, C. (2024, June), Designing with AI: Integrating Image-Generative AI into Conceptual Design in a CAD Class Paper presented at 2024 ASEE Annual Conference & Exposition, Portland, Oregon. https://peer.asee.org/47146

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