2025 ASEE Annual Conference & Exposition

Work-in-Progress: Uncovering AI Adoption Trends Among University Engineering Students for Learning and Career Preparedness

Work-in-Progress: Uncovering AI Adoption Trends Among University Engineering Students for Learning and Career Preparedness-progress study explores self-reported data on AI use by university engineering students. The purpose of this study is to investigate how students are utilizing AI technologies and to understand their views on the role of AI in their future. The primary research question formulated was: How does the adoption of AI technologies for learning vary across demographic groups among university engineering students? Advances in technology and the emergence of AI tools have attracted attention from academia, research, and industry. The rapid growth of deep learning technologies has changed the landscape in the work environment, and universities may need to adapt to keep pace. Dynamic changes in the workplace have accelerated as these AI technologies are being leveraged to complete tasks at a high-speed rate. Research indicates that the workforce is increasingly demanding higher skill levels, including specialized AI skills. Formal education in AI basics could be crucial for future career readiness.
Over 150 engineering students reported their demographics, including age, race, gender, year in school, and if they identify as having any form of disability. Currently, the survey remains open. The final study will incorporate more responses, and additional data will come from semi-structured interviews. This research explores the ways in which undergraduate and graduate students at a major R1 land-grant university in the western United States interact with AI tools.
Students reported on using AI technologies, like ChatGPT, to aid in their learning. Preliminary findings suggest that freshman students are less likely to have used AI technologies than those later in their college careers. Encouragingly, students closest to entering the workforce are the ones with the most exposure to these technologies. Interestingly, students who identify as having any form of a disability or condition that impacts their learning (e.g., learning disability, neurodiversity, physical disability, etc.) initially reported lower usage of AI technologies compared to their classmates. The lower use by freshmen and increasing exposure to generative AI throughout students’ university experience is noteworthy.
Students were also asked for their views on the formal integration of AI technologies into the College of Engineering courses. It could be valuable for universities to explore adding formal training to help equip students for the workforce. We anticipate that this study will highlight how exposure to AI technologies may prove essential for engineering students in preparing for a rapidly evolving workplace, as AI has the potential to enhance real-world problem-solving skills and help students become more equipped for workplace demands.

Authors

Linda Davis Ahlstrom Utah State University [biography]

Linda Ahlstrom PhD student currently studying Engineering Education at Utah State University. Interested in the Univerity to Industry interface and the use of AI tools in engineering. MS Electrical Engineering Cal State Long Beach. Worked in industry: Biomedical, Software Development and Aerospace.
Dr. Oenardi Lawanto Utah State University [biography]

Dr. Oenardi Lawanto is a professor in the Department of Engineering Education at Utah State University, USA. He received his B.S.E.E. from Iowa State University, his M.S.E.E. from the University of Dayton, and his Ph.D. from the University of Illinois at Urbana-Champaign. Dr. Lawanto has a combination of expertise in engineering and education and has more than 30 and 14 years of experience teaching engineering and cognitive-related topics courses for his doctoral students, respectively. He also has extensive experience in working collaboratively with several universities in Asia, the World Bank Institute, and USAID to design and conduct workshops promoting active-learning and life-long learning that is sustainable and scalable. Dr. Lawanto’s research interests include cognition, learning, and instruction, and online learning.
Dr. Cassandra McCall http://orcid.org/https://0000-0002-0240-432X Utah State University [biography]

Dr. Cassandra McCall is an Assistant Professor in the Engineering Education Department at Utah State University (USU). Her research focuses on the intersections of disability, identity formation, and culture and uses anti-ableist approaches to enhance universal access for students with disabilities in STEM, particularly in engineering. At USU, she serves as the Co-Director of the Institute for Interdisciplinary Transition Services. In 2024, Dr. McCall received a National Science Foundation CAREER grant to identify systemic opportunities for increasing the participation of people with disabilities in engineering. Her award-winning publications have been recognized by leading engineering education research journals at both national and international levels. Dr. McCall has led several workshops promoting the inclusion of people with disabilities and other minoritized groups in STEM. She holds B.S. and M.S. degrees in civil engineering with a structural engineering emphasis.
Michaela Harper http://orcid.org/0009-0007-5985-8676 Utah State University [biography]

Michaela Harper is a doctoral student at Utah State University, pursuing a Ph.D. in Engineering Education. She holds a Bachelor's degree in Environmental Studies, focusing on STEM and non-traditional education approaches, and a Master's degree in Engineering Education, where she explored faculty perspectives on Generative Artificial Intelligence (GAI). Michaela's current research delves deeply into the effects of disruptive technologies on engineering education, driven by her passion for uncovering the foundational nature of phenomena and applying an exploratory and explanatory approach to her studies. Her work aims to illuminate how technological advancements reshape educational landscapes through student and faculty engagement.
Dr. Wade H Goodridge http://orcid.org/0000-0002-5811-7629 Utah State University [biography]

Wade Goodridge is a tenured Associate Professor in the Department of Engineering Education at Utah State University. His research lies in spatial thinking and ability, curriculum development, and professional development in K-16 engineering teaching.
Daniel Kane http://orcid.org/0000-0002-0220-9962 Utah State University [biography]

Daniel Kane is a third-year Ph.D. student in the department of engineering education at Utah State University. His research interests include spatial ability, accessibility for students with disabilities, artificial intelligence in education, and enhancing electric vehicle charging system infrastructure. Daniel has contributed significantly to the development of the Tactile Mental Cutting Test (TMCT) which is a significant advancement in assessing spatial ability for blind and low-vision populations. His research has helped inform teaching methods and develop strategies for improving STEM education accessibility. Currently, he is studying how AI tools are utilized by students across USU’s colleges to optimize their educational value. Daniel has also served as president of the ASEE student chapter at USU where he initiated outreach activities at local K-12 schools and promoted student engagement in research.

Note

The full paper will be available to logged in and registered conference attendees once the conference starts on June 22, 2025, and to all visitors after the conference ends on June 25, 2025