Faculty Perspectives on Undergraduate Use of Generative Artificial Intelligence (GAI) Assistance: A Work-in-Progress
- Conference
- Location
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Portland, Oregon
- Publication Date
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June 23, 2024
- Start Date
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June 23, 2024
- End Date
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July 12, 2024
- Conference Session
- Tagged Division
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Faculty Development Division (FDD)
- Permanent URL
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https://peer.asee.org/47459
Paper Authors
Michaela Harper Utah State University
Michaela Harper is a graduate student at Utah State University specializing in engineering education with a background in Environmental Studies, focusing on STEM and non-traditional education. Her interest predominantly lies in understanding the underlying nature of things, bringing an exploratory and explanatory approach to her research, including the impacts of disruptive technology on engineering, a field popularly deemed as “tech-savvy.”
Cassandra McCall
Utah State University
orcid.org/0000-0002-0240-432X
Cassandra McCall, Ph.D., is an Assistant Professor in the Engineering Education Department and Co-Director of the Institute for Interdisciplinary Transition Services at Utah State University. Her research centers the intersection identity formation, engineering culture, and disability studies. Her work has received several awards including best paper awards from the Journal of Engineering Education and the Australasian Journal of Engineering Education. She holds a Ph.D. in Engineering Education from Virginia Tech as well as M.S. and B.S. degrees in civil engineering from the South Dakota School of Mines and Technology.
Abstract
This work-in-progress paper explores faculty perspectives regarding student use of Generative Artificial Intelligence (GAI) assistance tools, such as ChatGPT, to complete engineering coursework. A common debate in engineering and computer science exists about how faculty should address GAI tools (i.e., prevent their usage in order to maintain academic integrity, teach students the new technologies, or establish regulatory guidelines in higher education). While GAI continues to disrupt traditional educational paradigms, its full impacts on teaching and learning are currently unknown. Such work is especially useful for fields such as engineering and computer science, whose work lies at the forefront of technological advancement and whose students more readily adopt new technologies into course tasks.
This paper discusses the preliminary findings of an intrinsic qualitative case study that answers the research question: How do engineering faculty perceive student use of GAI assistance in undergraduate course completion? Data were collected using semi-structured interviews with engineering and computer science faculty, including civil, mechanical, electrical, and biological engineering and computer science. As a result, this paper lays the groundwork for more extensive research in this domain and contributes to the broader discourse on the role of emerging technologies in shaping the future of engineering education.
Harper, M., & McCall, C. (2024, June), Faculty Perspectives on Undergraduate Use of Generative Artificial Intelligence (GAI) Assistance: A Work-in-Progress Paper presented at 2024 ASEE Annual Conference & Exposition, Portland, Oregon. https://peer.asee.org/47459
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