Portland, Oregon
June 23, 2024
June 23, 2024
June 26, 2024
Multidisciplinary Engineering Division (MULTI) Technical Session 10
Multidisciplinary Engineering Division (MULTI)
9
10.18260/1-2--46474
https://peer.asee.org/46474
235
Dr. Lawrence Whitman is Dean of the Donaghey College of Science, Technology, Engineering, and Mathematics.
Dr. Whitman earned his Bachelor's degree in Mechanical Engineering Design Technology from Oklahoma State University where he also earned his Master
Kristin Dutcher Mann is professor of history and social studies education coordinator at the University of Arkansas at Little Rock. A specialist in the colonial history of the U.S.-Mexico Borderlands, she has authored a book and articles about music, dance, and material culture. She often works with K-12 and college faculty to incorporate reading, writing, and primary source document analysis into instruction. Her latest research is part of an interdisciplinary project to examine student perceptions of the use of large language models such as ChatGPT and Microsoft CoPilot in academic work.
Dr. Kanekar is a Professor and Graduate Program Coordinator for Health Education and Health Promotion at the University of Arkansas at Little Rock. His 17 years of teaching experience involves more than 30 different courses (undergraduate and graduate) in the areas of public health, health education and health promotion. Recipient of numerous teaching awards at the international, national and local levels, his pedagogical techniques involve online –distance learning, hybrid, and face-to-face courses.
He has published more than 80 publications (refereed and non-refereed) and his research areas of interest focus on adolescent health, measurement in health education, global health, online and hybrid pedagogy, and health behavior interventions. He currently serves as a Certified in Public Health ambassador for the National Board of Public Health Examiners and on the Arkansas Public Health Education Board
Dr. Pidugu is a Professor and Director (Interim) of School of Engineering and Engineering Technology at University of Arkansas at Little Rock. He obtained Ph.D. in Mechanical Engineering at Old Dominion University in 2001.
This study investigates college students' use of and attitude toward large language models (LLMs). The primary research questions are, “What are students’ perceptions of the ethical use of large language models in college coursework and other settings?” and “How does teaching about large-language models impact student understanding of the applications of machine-learning, plagiarism, and ethics in specific content areas?”
Our mixed-methods study involves pre- and post-module surveys with questions assessing students' attitudes and perceptions about the ethics of large language model use in college and professional settings. The learning module includes an introductory video, interactive slide presentation, and discussion questions. We collected additional data through a related assignment. Participants were students from introductory engineering courses, along with those in computer science, science, and humanities courses, in the fall 2023 semester.
Our study considers the impact of LLMs in engineering education, addressing opportunities for enhancing students' understanding of machine learning and ethical considerations in college and the workplace. The results will offer insights to educators, allowing for more effective integration of LLMs in engineering curricula.
Whitman, L. E., & Mann, K. D., & Kanekar, A. S., & Baker, A. L., & Pidugu, S. B. (2024, June), A Pilot Study of the Use and Attitudes Toward Large Language Models Across Academic Disciplines Paper presented at 2024 ASEE Annual Conference & Exposition, Portland, Oregon. 10.18260/1-2--46474
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