2026 ASEE Annual Conference & Exposition

Closing the Teamwork and Ethics Gap through Structured Interventions in Civil Engineering Education

Presented at Putting our Students in the Driver's Seat: Engineering in the 21st Century Fastlane

Persistent gaps in teamwork (ABET Student Outcome 5) and ethical responsibility (ABET Student Outcome 4) continue to challenge civil engineering programs, even within established outcomes-based assessment systems. At the study institution, longitudinal assessment data revealed fluctuating attainment in teamwork and a decline in ethics performance below the program’s 75 percent benchmark during the 2022 academic year. These trends prompted structured instructional refinements within existing coursework aimed at strengthening professional competency development.
Guided by two research questions focused on longitudinal attainment patterns, this study employs a longitudinal descriptive design using aggregated, program-level rubric-based assessment data collected across multiple academic terms from Fall 2021 through Fall 2024. Instructional refinements included calibrated teamwork rubrics, redesigned team structures with reduced group sizes, and embedded ethics case discussions within technical design assignments. Outcome attainment was defined as the combined percentage of students achieving Satisfactory or Exemplary performance levels relative to the program benchmark.
Results document reductions in unsatisfactory ratings and increased concentration of student performance in satisfactory and exemplary categories across successive assessment cycles, particularly for Student Outcome 5. Ethics attainment trends show recovery and stabilization following an initial decline, with later assessment terms meeting or exceeding the program benchmark. Although variability across terms remains, the longitudinal patterns indicate directional movement toward higher attainment categories within the program’s continuous improvement framework.
This study illustrates how longitudinal analysis of ABET-aligned assessment data can inform structured instructional refinement within civil engineering curricula. The findings provide a program-level model for integrating teamwork and ethics development into technical coursework while maintaining alignment with accreditation expectations.

Authors

Julius Ogaga Etuke http://orcid.org/0000-0002-2710-2803 Morgan State University [biography]

Julius Ogaga Etuke is a seasoned civil engineer and Ph.D. Candidate in Civil Engineering at Morgan State University, where his research focuses on sustainable and resilient infrastructure engineering. With over 15 years of consulting and project leadership experience, primarily in Nigeria's infrastructure landscape, he brings a robust, practical perspective to academic inquiry. His doctoral research is at the cutting edge of transportation resilience, integrating virtual and augmented reality (VR/AR), climate adaptation modeling, and data-driven solutions to improve disaster preparedness and risk mitigation in complex transportation systems. As a COREN-registered engineer and member of the Nigerian Society of Engineers, his work emphasizes impactful research and consultancy that bridges structural design principles with urgent sustainability and resilience challenges.
Obiageli Gertrude Adaku Nwachukwu Morgan State University [biography]

Obiageli Nwachukwu is a Graduate Research Assistant at the Centre for Equitable Artificial Intelligence and Machine Learning Systems, Morgan State University, where she specializes in data‑driven modeling, machine learning, and applied bioinformatics. Her research spans predictive analytics, digital health adoption, and the development of equitable AI frameworks for underserved communities. She has contributed to NTIA‑funded projects focused on broadband access, telehealth readiness, and community‑centered digital equity initiatives. With a background in pharmacy and advanced training in computer science (bioinformatics), she integrates domain expertise in health systems with computational methods to build predictive models that support informed decision‑making in public health and technology adoption. Her broader interests include clinical trial outcome prediction, translational data science, and AI‑enabled solutions for improving health access and outcomes.
Dr. Oludare Adegbola Owolabi P.E. Morgan State University [biography]

Dr. Oludare Owolabi, a professional engineer in Maryland, joined the Morgan State University faculty in 2010. He is the director of the Sustainable Infrastructure Development, Smart Innovation and Resilient Engineering Research Lab, Department of Civil Engineering at Morgan State University.
Taiwo O Ogunlade Morgan State University [biography]

Taiwo O. Ogunlade is a Structural and Bridge Engineer at Century Engineering, a Kleinfelder Company, in Hunt Valley, Maryland, specializing in the design, inspection, and rehabilitation of highway bridge structures across Maryland, Delaware, and Pennsylvania. He holds a Master of Engineering (MEng) in Civil Engineering from Morgan State University Maryland and is currently pursuing a doctoral degree at the same institution, with research focused on infrastructure performance, sustainable materials, and applications of machine learning in Bridge Inspections.

With over eight years of engineering experience including four years in residential and highway infrastructure construction in Nigeria and four years in bridge design in the United States, Ogunlade brings a strong integration of field construction knowledge and structural engineering expertise. At Kleinfelder, he has contributed to significant regional bridge projects involving structural analysis, QA/QC oversight, and CADD-based design. Alongside his practice, he is actively engaged in doctoral research, including journal writing and reflecting his commitment to advancing civil and structural engineering through both professional practice and scholarly contribution.

Note

The full paper will be available to logged in and registered conference attendees once the conference starts on June 21, 2026, and to all visitors after the conference ends on June 24, 2026

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