ACE up your Sleeve: An Analysis of Student Generative AI Usage in an Engineering Statics Course

Jacklyn Wyszynski; David Adam DeFrancisis; David Pabst; Lee Allen Dosse; Matthew M. Barry

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Conference: 2025 ASEE Annual Conference & Exposition
Location: Montreal, Quebec, Canada
Publication Date: June 22, 2025
Start Date: June 22, 2025
End Date: August 15, 2025
Conference Session: Mechanics Division (MECHS) Technical Session 1A
Tagged Division: Mechanics Division (MECHS)
Page Count: 19
DOI: 10.18260/1-2--55423
Permanent URL: https://peer.asee.org/55423
Download Count: 11

Lee A. Dosse is a PhD student working with the Engineering Education Research Center at the University of Pittsburgh.

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Matthew M. Barry University of Pittsburgh

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Dr. Barry is a Visiting Associate Professor in the Mechanical Engineering and Materials Science department at the University of Pittsburgh. His research interests include space power propulsion systems and Engineering Education.

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Abstract

Rapid technological advancements, including the emergence of computer-aided design and simulation, have had a significant impact on the engineering industry. This, in turn, extends to engineering education, demonstrating a similar influential effect. The latest development to have such reverberations is the launch of a generative artificial intelligence (AI) chatbot known as ChatGPT. ChatGPT utilizes a large language model (LLM) that trains the platform to understand and generate human-like responses. This LLM comprises numerous neural networks trained using the vast amount of information available online, including research papers. As this new technology is widely accessible to students, the questions that arise regarding its role in education are almost always related to academic integrity. ChatGPT can answer questions, compose and revise papers (like this one), and complete collegiate course evaluations. Though ChatGPT can be misused, like many tools, when used as intended, it can assist students in their educational efforts. That is, instead of asking AI to answer homework prompts, one can inquire for clarification to further their knowledge about nuanced engineering phenomena.

This paper attempts to understand students' perspectives and engagement with generative AI in a university-level introductory engineering course. Self-reported student data were collected through a survey and six focus group interviews, which were then thematically coded to elucidate any common trends. Unsurprisingly, students admitted to copying and pasting assignment questions into AI but soon discovered that the answers were, more often than not, unreliable. This feedback forced them to use it more productively. Interestingly, many students viewed AI as an around-the-clock tutor that was conveniently always available, asking it to clarify complex topics or provide definitions or equations needed for assignments. A substantial number of responses indicated that students found AI helpful when preparing for exams, as it helped formulate study guides by synthesizing student-inputted equation sheets or created practice problems that mimicked exam questions.

Citation
Format

Wyszynski, J., & DeFrancisis, D. A., & Pabst, D., & Dosse, L. A., & Barry, M. M. (2025, June), ACE up your Sleeve: An Analysis of Student Generative AI Usage in an Engineering Statics Course Paper presented at 2025 ASEE Annual Conference & Exposition , Montreal, Quebec, Canada . 10.18260/1-2--55423

TY - CPAPER
AB - Rapid technological advancements, including the emergence of computer-aided design and simulation, have had a significant impact on the engineering industry. This, in turn, extends to engineering education, demonstrating a similar influential effect. The latest development to have such reverberations is the launch of a generative artificial intelligence (AI) chatbot known as ChatGPT. ChatGPT utilizes a large language model (LLM) that trains the platform to understand and generate human-like responses. This LLM comprises numerous neural networks trained using the vast amount of information available online, including research papers. As this new technology is widely accessible to students, the questions that arise regarding its role in education are almost always related to academic integrity. ChatGPT can answer questions, compose and revise papers (like this one), and complete collegiate course evaluations. Though ChatGPT can be misused, like many tools, when used as intended, it can assist students in their educational efforts. That is, instead of asking AI to answer homework prompts, one can inquire for clarification to further their knowledge about nuanced engineering phenomena.

This paper attempts to understand students&#39; perspectives and engagement with generative AI in a university-level introductory engineering course. Self-reported student data were collected through a survey and six focus group interviews, which were then thematically coded to elucidate any common trends. Unsurprisingly, students admitted to copying and pasting assignment questions into AI but soon discovered that the answers were, more often than not, unreliable. This feedback forced them to use it more productively. Interestingly, many students viewed AI as an around-the-clock tutor that was conveniently always available, asking it to clarify complex topics or provide definitions or equations needed for assignments. A substantial number of responses indicated that students found AI helpful when preparing for exams, as it helped formulate study guides by synthesizing student-inputted equation sheets or created practice problems that mimicked exam questions.
AU - Jacklyn Wyszynski
AU - David Adam DeFrancisis
AU - David Pabst
AU - Lee Allen Dosse
AU - Matthew M. Barry
CY - Montreal, Quebec, Canada
DA - 2025/06/22
PB - ASEE Conferences
TI - ACE up your Sleeve: An Analysis of Student Generative AI Usage in an Engineering Statics Course
UR - https://peer.asee.org/55423
DO - 10.18260/1-2--55423
ER -