2025 ASEE Annual Conference & Exposition

Impact of Structured AI Implementation on Student Confidence and Instructor Interactions in an Undergraduate Geotechnical Engineering Course

Presented at Civil Engineering in the Age of AI

This study investigated how structured AI implementation affects student-instructor interactions and student perceptions in an undergraduate geotechnical engineering course. The research compared an intervention group that was highly encouraged to use AI and received structured AI guidance with a control group with no formal AI integration or encouragement. Through pre- and post-course surveys, findings revealed that structured implementation helped maintain student confidence in using AI as a learning tool, while students without guidance showed decreased confidence. Statistical analysis of final grades showed no significant differences between groups, suggesting that while the implementation approach influenced student perceptions, it did not directly impact academic performance. Students across all sections expressed concerns about AI’s reliability for technical calculations and the balance between AI assistance and traditional learning methods. The results indicate that while implementation approach significantly influences both student confidence and classroom dynamics in technical courses, careful consideration must be given to how these changes translate to measurable learning outcomes.

Authors

Lt. Col. Vincent Italo Bongioanni United States Air Force Academy [biography]

Dr. Vincent Bongioanni is an innovator in integrating artificial intelligence into higher education. He formed the "AI in Higher Ed" research group under the United States Air Force Academy's Center for Excellence in Teaching and Learning. He leads a cross-disciplinary team investigating the transformative potential of generative AI (gAI) in academic settings. His work focuses on identifying both the challenges and opportunities presented by AI technologies in education.

Dr. Bongioanni's research aims to develop best practices for AI integration that enhance student learning experiences while addressing potential pitfalls. His team explores innovative ways to leverage AI to foster deeper engagement, critical thinking, and problem-solving skills among students. Additionally, they investigate methods to streamline instructional processes, potentially reducing faculty workload without compromising educational quality.

As a faculty member in the Department of Civil and Environmental Engineering, Dr. Bongioanni brings a unique perspective to AI integration in STEM fields. His work not only contributes to the academic discourse on AI in education but also has practical implications for preparing future military leaders for an increasingly AI-driven world.
Lt. Col. Jason D Christopher USAF Academy [biography]

Lt Col Jason Christopher is an assistant professor of mechanical engineering. His research interests include thermal fluid sciences and pedagogical innovation. He holds a Ph.D. in mechanical engineering from the University of Colorado, Boulder and an M.S. in mechanical engineering from Rice University. He is an engineer in the U.S. Air Force and has experience acquiring space launch range systems and directing operational tests of multi-billion-dollar systems.
Brianna D Hitt United States Air Force Academy

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

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