Presentation Schedule
Enhancing Engineering and Technology Education Through AI-Enhanced Instructional Methods (98680)
Session Chair: Ompe Aime Mudimu
Sunday, 4 January 2026 13:05
Session: Session 3 (Parallel)
Room: Hawaii Convention Center: Room 301B
Presentation Type: Oral Presentation
Artificial Intelligence (AI) tools are rapidly transforming engineering and technology education, offering personalized learning, simulation-based visualization, and real-time feedback. This study explores the integration of AI-powered platforms into the delivery of a senior-level course in the CM and CE programs at a U.S. public university. The research investigates the effectiveness of incorporating ChatGPT and AI-driven design assistants to improve conceptual understanding, assignment engagement, and technical writing. The methodology employed a mixed-format instructional model, where traditional lectures were supplemented with structured AI activities. Students utilized AI to interpret civil drawings, refine construction cost estimates, and simulate construction sequencing. A quantitative analysis compared student performance metrics and rubric-aligned assessments across two semesters: one with AI integration and one without. Qualitative data from anonymous student surveys and reflective journals were coded to assess perceived utility and learning confidence. Results indicated a 22% improvement in technical report quality and a 31% increase in student engagement scores. Notably, 78% of participants reported that AI tools significantly enhanced their comprehension of complex project delivery systems, particularly in visualizing multi-phase construction processes, clarifying technical terminology, and understanding coordination between design, technology, and site logistics. This level of reported benefit suggests a strong alignment between AI-supported inquiry and the cognitive demands of applied engineering coursework. This case study demonstrates that thoughtfully integrated AI tools can enhance learning outcomes and student confidence in engineering education. The findings support further adoption of AI-enhanced instruction across STEM curricula and offer scalable insights for educators designing human-AI collaborative learning environments.
Authors:
Mohamed Askar, Southern Utah University, United States
Jared Baker, Southern Utah University, United States
About the Presenter(s)
Dr. Askar is currently a Professor of Engineering, Associate Chair, and Construction Management Program Director in the Department of Engineering & Technology at Southern Utah University.
Additional website of interest
https://www.suu.edu/et/contact.html
See this presentation on the full schedule – Sunday Schedule








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