2026 ASEE Annual Conference & Exposition

Cultivating Resilience and Collaboration in a Foundational Computing Course

Presented at Engineering Ethics Division (ETHICS) Poster Session

This article presents an evidence-based intervention integrating character formation into Computing for Engineers, a required first-year course at Duke University. Traditionally centered on programming and computational thinking, the course is now intentionally designed to cultivate resilience and collaboration through partnership with the Pratt School of Engineering’s ethics initiative, Character Forward. Drawing on Crossan and colleagues’ Leader Character Framework and strategies from Lamb and colleagues, students develop virtue literacy through lecture, case examples, and reflections that connect character to engineering practice. Reflection prompts and team charters encourage students to recognize resilience in debugging and iteration, and to define norms for effective teamwork and feedback. A mixed-methods assessment using pre-/post-course surveys measured changes in students’ understanding and self-reported growth. While our closed-ended measures revealed little growth, our open-ended measures found that over 80% of student respondents reflected positively on how the interventions impacted their resilience and collaboration. Ultimately, embedding virtue-focused pedagogy in this foundational computing course models how engineering education can unite technical proficiency with the habits of character essential for responsible and effective professional practice.

Authors

Dr. Rich Eva http://orcid.org/0000-0002-1661-060X Duke University [biography]

Rich Eva, Ph.D., is the inaugural director of Character Forward, an ethics initiative in Duke University’s Pratt School of Engineering, and a research fellow with the Kenan Institute for Ethics. A philosopher by training, his research and teaching focus on ethics, political philosophy, and pedagogy.
Dr. Alexandra Cooper Ph.D. Duke University [biography]

Alexandra Cooper, Ph.D., is the associate director for assessment at the Kenan Institute for Ethics at Duke Duke University, associate director of the Duke Initiative on Survey Methodology, and a member of the Duke University Institutional Review Board. She is trained in survey and qualitative research methods and uses these tools to support a wide variety of assessment and research projects.
Dr. Genevieve M Lipp Duke University [biography]

Genevieve Lipp is an Assistant Professor of the Practice in the departments of Electrical and Computer Engineering and Mechanical Engineering and Materials Science. She received a B.S.E. in mechanical engineering from Duke University in 2010 and a Ph.D. in 2014 with a focus on nonlinear dynamical systems.
Dr. Kip D. Coonley Duke University [biography]

Kip D. Coonley received the Ph.D. degree in Electrical and Computer Engineering from Duke University, Durham, NC in 2023, the M.S. degree in Electrical Engineering from Dartmouth College, Hanover, NH, in 1999 and the B.S. degree in Physics from Bates College, Lewiston, ME, in 1997. Following graduation from Dartmouth, he developed electronically controlled dimmers for fluorescent and incandescent lamps at Lutron Electronics, Coopersburg, PA. From 2001 to 2005, he was a Research Engineer at RTI International, where he designed high-efficiency thermoelectrics using epitaxially grown superlattice thin-film structures. Since 2005, he has been the Undergraduate Laboratory Manager in the Department of Electrical and Computer Engineering at Duke University, Durham, NC earning the doctoral degree in 2023. His research interests include undergraduate engineering education, energy harvesting, RFID, power electronics, plasma physics, and thin films.
Dr. Javier Pastorino http://orcid.org/https://0000-0002-2641-9833 Duke University [biography]

Dr. Javier Pastorino is an Assistant Professor in Electrical and Computer Engineering at Duke University. His work bridges academia and industry, drawing on more than twenty years of experience across roles in software engineering. He holds a Ph.D. in Computer Science with a focus on artificial intelligence, and his research centers on data management, machine learning for scientific applications, and privacy-aware machine learning from a software engineering perspective. In addition to his research contributions, he is actively engaged in enhancing engineering education through the development of scalable, technology-driven learning systems.

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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