2026 ASEE Annual Conference & Exposition

Engineering Success: Identifying Key Predictors of GPA Trajectories Through Latent Class Trajectory Modeling

Presented at Persistence, Completion, and their Factors

This paper (empirical research, research brief) investigates the psychological, academic, and demographic predictors of longitudinal grade point average (GPA) trajectories among undergraduate engineering students. Although GPA remains a central indicator of academic achievement, most studies rely on variable-centered approaches that focus on average performance at a single time point, obscuring within-group heterogeneity and changes over time (Richardson et al., 2012; Godwin et al., 2021). To address these limitations, this study employed latent class trajectory modeling (LCTM) and hierarchical multinomial regression to examine three years of GPA data from 883 engineering undergraduates across two U.S. universities, integrating 30 non-cognitive and affective (NCA) predictors drawn from the [redacted] survey (redacted for review). LCTM is a machine learning-based statistical method that identifies latent classes within a population based on patterns in variables. The method can be used to identify unique groups that can be studied further in other ways.

LCTM identified six distinct GPA trajectories: Consistently High Performers, Steadily Improving, Sharply Improving, Starting to Struggle, Consistently Struggling, and Consistently Vulnerable. Most students (79%) maintained high or improving GPAs, while approximately 13% exhibited concerning academic trajectories, often falling below the 2.0 threshold for academic probation. Hierarchical multinomial regression revealed that race/ethnicity, standardized test scores, personality traits (e.g., neuroticism, openness), mindset, stress, social support, and belonging significantly predicted trajectory membership. In particular, Black, Indigenous, and Hispanic/Latino students were disproportionately represented in the lowest-performing groups, highlighting the enduring impact of systemic inequities in engineering education.

This study extends prior trajectory analyses by modeling the constellation of factors that predict academic persistence and success in engineering education. These findings highlight that engineering students’ academic trajectories are shaped by a complex interaction of psychological and sociocultural factors rather than cognitive preparation alone. By linking longitudinal performance data with a wide range of individual and contextual predictors, this work provides a more nuanced view of how and why students’ academic paths diverge over time.

Authors

Dr. Heather Perkins http://orcid.org/0000-0002-8757-0545 Purdue University Northwest [biography]

Heather Perkins holds a Ph.D. in Psychology from North Carolina State University and a B.S. in Psychology from the University of Cincinnati. Before joining Purdue University Northwest as an Assistant Professor in 2025, she served as a Visiting Assistant Professor at Indiana University Bloomington and a Postdoctoral Researcher in the School of Engineering Education at Purdue University West Lafayette. Heather's work examines how identity shapes motivation, confidence, and academic trajectories, particularly in graduate and underrepresented student populations.
Dr. Justin Charles Major http://orcid.org/0000-0002-3111-8509 Rowan University [biography]

Dr. Justin C. Major (they/them) is an Assistant Professor of Experiential Engineering Education at Rowan University where they leads ASPIRE Lab (Advancing Student Pathways through Inequality Research in Engineering). Justin’s research focuses on low-income students, engineering belonging and marginalization mechanisms, adverse childhood experiences, and feminist approaches to EER, and connects these topics to broader understandings of student success in engineering. Justin completed their Ph.D. in Engineering Education (’22) and M.S. in Aeronautics and Astronautics (’21) at Purdue University, and two B.S. in Mechanical Engineering and Secondary Mathematics Education at the University of Nevada, Reno (’17). Atop their education, Justin is a previous NSF Graduate Research Fellow and has won over a dozen awards for research, service, and activism related to marginalized communities, including the 2020 ASEE ERM Division Best Diversity Paper for their work on test anxiety. As a previous homeless and food-insecure student, Justin is eager to challenge and change engineering engineering education to be a pathway for socioeconomic mobility and broader systemic improvement rather than an additional barrier.
Dr. John Chen P.E. California Polytechnic State University, San Luis Obispo [biography]

John Chen is a professor of mechanical engineering. His interests in engineering education include conceptual learning, conceptual change, student autonomy and motivation, lifelong learning skills and behaviors, and non-cognitive factors that lead to stu
Dr. Edward J. Berger http://orcid.org/0000-0003-0337-7607 Virginia Polytechnic Institute and State University [biography]

Edward Berger is a Professor of Engineering Education and Mechanical Engineering at Purdue University, joining Purdue in August 2014. He has been teaching mechanics for over 20 years, and has worked extensively on the integration and assessment.
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.

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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