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Perceptions of Engineering College Instructors and Their Students Towards Generative Artificial Intelligence (GenAI) Tools: A Preliminary Qualitative Analysis

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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

Educational Research and Methods Division (ERM) Technical Session 22

Tagged Division

Educational Research and Methods Division (ERM)

Permanent URL

https://peer.asee.org/47840

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Paper Authors

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Dhruv Gambhir Nanyang Technological University

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Dhruv is a senior undergraduate student majoring in Computer Science at Nanyang Technological University (NTU) in Singapore. Actively engaged in Dr. Yeter’s Research Team, he specializes in projects at the intersection of engineering education and artificial intelligence (AI). With a unique perspective as an engineering student focused on AI, Dhruv is dedicated to enhancing engineering education in the age of artificial intelligence.

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Yifan Xie University College London

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Yifan Xie has recently obtained his second master’s degree at the Institute of Education (IOE) at University College London (UCL), and he obtained his first master’s degree at the Faculty of Natural, Mathematical & Engineering Sciences at King’s College London (KCL). His major emphasis has been exploring the influence of transferable abilities, such as active learning and problem-based learning, on engineering education and learning experiences. With a background in both engineering and education, Yifan is actively involved in Dr. Yeter’s Research Team, focusing on projects related to the facilitation of education through the practical use of technology.

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Ibrahim H. Yeter Nanyang Technological University Orcid 16x16 orcid.org/0000-0002-0175-2306

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Ibrahim H. Yeter, Ph.D., is an Assistant Professor at the National Institute of Education (NIE) at Nanyang Technological University (NTU) in Singapore. He is an affiliated faculty member of the NTU Centre for Research and Development in Learning (CRADLE) and the NTU Institute for Science and Technology for Humanity (NISTH). He serves as the Director of the World MOON Project and holds editorial roles as Associate Editor of the IEEE Transactions on Education and Editorial Board Member for the Journal of Research and Practice in Technology Enhanced Learning. He is also the upcoming Program Chair-Elect of the PCEE Division at ASEE. His current research interests include STEM+C education, specifically artificial intelligence literacy, computational thinking, and engineering.

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Junaid Qadir Qatar University

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Junaid Qadir is a Professor of Computer Engineering at Qatar University, Doha, Qatar, where he leads the IHSAN Research Lab. His research interests include computer systems, networking, machine learning applications, and ICT for development (ICT4D). With over 150 peer-reviewed publications in leading journals such as IEEE Communication Magazine and IEEE Transactions on Mobile Computing, he has received prestigious teaching awards and research grants from organizations like Facebook Research and Qatar National Research Fund. Junaid Qadir is also an ACM Distinguished Speaker and a senior member of IEEE and ACM.

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Andy Khong Nanyang Technological University

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Andy Khong is currently a Deputy Associate Provost and an Associate Professor in the School of Electrical and Electronic Engineering at Nanyang Technological University, Singapore. He holds a joint appointment with Lee Kong Chian School of Medicine at the same university. Prior to that, he obtained his Ph.D. from the Department of Electrical and Electronic Engineering, Imperial College London. Andy currently serves as an Associate Editor for the IEEE Transactions on Audio, Speech, and Language Processing and the Journal of Multidimensional Systems and Signal Processing (Springer). His main research interests include learning analytics, acoustic signal processing, and recommendation systems.

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Abstract

GenAI tools, such as ChatGPT, have gained significant traction in engineering colleges and are revolutionizing how students approach each assignment and project. However, integrating them into the education system introduces challenges to the core assessment criteria and the traditional grading system that has been used in these institutions for decades. To achieve a better understanding of the significant influence and disturbance caused by GenAI, this study employed semi-structured interviews to collect qualitative data from a group of six students and two instructors, chosen via stratified sampling, from a research-intensive engineering college in Southeast Asia to explore their perspectives regarding GenAI. Initially, we discussed the positive and negative effects of GenAI on engineering education. Subsequently, we explored the correlation between ChatGPT and the current assessment pattern. It turned out that the widespread adoption of GenAI tools has made it necessary to reevaluate current assessment methods at educational institutions. The conventional grading scheme also found itself increasingly incompetent against the capabilities of ChatGPT, posing a potential threat to the equilibrium of academic integrity. The adaptive strategies employed by institutions in response to GenAI are also discussed in this paper, and we have explored whether instructors restrict students’ access using sophisticated detection systems or simply advocate ethical and responsible use of GenAI. The potential consequences of these policies on students’ learning were also explored with an emphasis on whether students feel unfairly disadvantaged when detection systems fail or if they perceive the need to rely on GenAI tools to maintain academic competitiveness.

Gambhir, D., & Xie, Y., & Yeter, I. H., & Qadir, J., & Khong, A. (2024, June), Perceptions of Engineering College Instructors and Their Students Towards Generative Artificial Intelligence (GenAI) Tools: A Preliminary Qualitative Analysis Paper presented at 2024 ASEE Annual Conference & Exposition, Portland, Oregon. https://peer.asee.org/47840

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