2026 ASEE Annual Conference & Exposition

Meaningful Failure: Transforming Academic Structures and Incentives through Personalization in Engineering Education

Presented at NSF Grantees Poster Session II

The project aims to develop personalized learning tools to support engineering students in engaging with "meaningful failure"–an approach that encourages students to embrace uncertainty, learn from setbacks, and ultimately achieve success through productive failure (Kapur, 2008; Sinha & Kapur, 2021). This research adopts a multi-pronged approach, including three strands: (1) in-vitro laboratory experiments to study cognitive, emotional, and physiological responses to failure; (2) in-situ observational studies across various engineering learning environments; and (3) socio-cultural studies to understand the conceptualization and interpretation of failure by students, instructors, and administrators. Three research questions were defined for each strand: (1) What are the useful real-time failure profile signals that would yield actionable personalization in engineering education contexts?; (2) How do students' differential responses to failure present opportunities for personalization of support in engineering education contexts?; (3) What changes to pedagogy, assessment, policy, and instructor professional development might be necessary to facilitate a culture of learning from and through failure in engineering education? Through a single IRB process, five engineering institutions are (1) exploring how the cognitive and affective states that students experience is reflected in recorded biosignals that can be decoded in real-time to understand how individual students respond differently to failure across different learning and social contexts; (2) documenting, capturing, and analyzing real-time interactions of students and instructors in the classroom, including moments of individual-level and group-level failures and successes during the experience of regular activities in several engineering courses; and (3) determining the best ways to translate the insights gained into directions for future development of systems that educators and administrators can use to address the key issues in promoting meaning failure and long-term success for engineering students. The initial outcomes were: (1) a standardized protocol for multi-modal physiological data collection, which enabled the collection of 18 participants' physiological data; (2) a survey instrument focusing on key psychosocial constructs, which enabled the data collection of 126 participants; a workflow to perform latent profile analyses (LPA); a qualitative data collection through 11 interviews; a biometric and audiovisual data collection through observation of seven students; (3) eight interviews of associate deans or engineering department chairs. The significant results of the first-year project were: (1) a protocol was established to analyze multimodal biosignals for individual students and determine accuracy and mental load on a trial-by-trial basis during a demanding cognitive task, relying on different signal patterns for different students; (2) four classes of failure response related to engagement and identity were defined, students’ definitions of failure seem to be very personalized and sensitive to how meaningful others may view it; (3) at small institutions failure is viewed very negatively and mostly in the mode of academic failure (e.g., failing a course, dropping out, etc.). These same concerns were not observed at larger research-intensive institutions. Other achievements of the whole group were the definition of research protocols across multiple sites to support fidelity of data collection in each research strand, publication of one conference paper, and the dissemination of the project idea and initial findings through two invited talks. This research is funded by NSF Grants Nos. 2432011, 2432012, 2432013, 2432014, and 2432015.

Authors

Runu Proma Das University of Georgia
Yeongji Lee http://orcid.org/0000-0002-8090-5242 Dartmouth College
Tathyana Moratti http://orcid.org/https://0000-0001-6359-8001 The University of Georgia [biography]

PhD student
Spencer Johnathan Sabatino http://orcid.org/0000-0002-1462-7475 Cornell University [biography]

Spencer Sabatino is a PhD candidate at the Robert Frederick Smith School of Chemical and Biomolecular Engineering at Cornell University. Spencer's research interests include studying engineering students' beliefs and their effects on broader student outcomes. He earned his Bachelor of Science degree in Chemical Engineering and his Master of Science in Chemical and Biomedical Engineering from Miami University in 2022.
David Zabner http://orcid.org/0009-0000-9920-2208 Tufts University [biography]

David Zabner is a PhD student at Tufts university where he focuses on computer science and engineering education
Mathew Baby University of Georgia
Katherine Becking Cornell University
Dr. Herman Ronald Clements III http://orcid.org/0009-0002-9165-7173 University of Nebraska - Lincoln
Michael Brown University of Michigan
Prof. Allison Godwin http://orcid.org/0000-0002-0741-3356 Cornell University [biography]

Allison Godwin, Ph.D. is the Dr. G. Stephen Irwin '67, '68 Professor in Engineering Education Research in the Robert Frederick Smith School of Chemical and Biomolecular Engineering at Cornell University. She is also the Associate Director of the Cornell NanoScale Science and Technology Facility and a McCormick Teaching Excellence Institute Research Fellow. Her research focuses on how identity, among other affective factors, influences diverse groups of students to choose engineering and persist in engineering. She also studies how different experiences within the practice and culture of engineering foster or hinder belonging, motivation, and identity development. Dr. Godwin graduated from Clemson University with a B.S. in Chemical Engineering and Ph.D. in Engineering and Science Education. Her research earned her a National Science Foundation CAREER Award focused on characterizing latent diversity, which includes diverse attitudes, mindsets, and approaches to learning to understand engineering students’ identity development. She has won several awards for her research including the 2021 Chemical Engineering Education William H. Corcoran Award, 2022 American Educational Research Association Education in the Professions (Division I) 2021-2022 Outstanding Research Publication Award, and the 2023 AIChE Excellence in Engineering Education Research Award.
Trevion S Henderson http://orcid.org/0000-0003-4319-1700 Tufts University [biography]

Trevion Henderson is Assistant Professor of Mechanical Engineering at Tufts University. He earned his Ph.D. in Higher Education at the University of Michigan.
Dr. Beshoy Morkos http://orcid.org/0000-0002-6656-3610 University of Georgia [biography]

Beshoy Morkos is a professor in the College of Engineering at the University of Georgia where he directs MODEL (Manufacturing Optimization, Design, and Engineering Education Lab) Group. His research group currently explores the areas of system design, manufacturing, and their respective education. His system design research focuses on developing computational representation and reasoning support for managing complex system design through the use of Model Based approaches. The goal of Dr. Morkos’ manufacturing research is to fundamentally reframe our understanding and utilization of product and process representations and computational reasoning capabilities to support the development of models which help engineers and project planners intelligently make informed decisions. On the engineering education front, Dr. Morkos’ research explores means to improve persistence and diversity in engineering education by leveraging students’ design experiences.
Dr. Vitaliy Popov http://orcid.org/0000-0003-2348-5285 University of Michigan [biography]

Vitaliy Popov is an Assistant Professor of Learning Health Sciences at the University of Michigan Medical School. His research focuses on understanding, designing, and evaluating learning technologies and environments that foster collaborative problem solving, spatial reasoning, engineering design thinking and agency. He is currently serving as a co-principal investigator on three projects funded by the National Science Foundation ranging from studying visuospatial skills development through origami to applying multimodal learning analytics in teamwork and understanding the mechanisms of an A-ha! moment. Dr. Popov completed his Ph.D. on computer-supported collaborative learning at Wageningen University & Research Center, in the Netherlands. His background allows him to utilize evidence in education science, simulation-based training and learning analytics to understand how people become expert health professionals, how they can better work in teams and how we can support these processes to foster health care delivery and health outcomes.
David J. M. Kraemer http://orcid.org/0000-0001-9829-2029 Dartmouth College

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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