Examining the Importance of Noncognitive and Affective (NCA) Factors for Engineering Student Success
- Conference
- Location
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Virtual On line
- Publication Date
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June 22, 2020
- Start Date
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June 22, 2020
- End Date
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June 26, 2021
- Conference Session
- Tagged Topics
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Diversity and NSF Grantees Poster Session
- Page Count
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12
- DOI
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10.18260/1-2--34618
- Permanent URL
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https://peer.asee.org/34618
- Download Count
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497
Paper Authors
Lily Krest Purdue University at West Lafayette
Lily Krest is a second-year Engineering Education PhD student at Purdue University. Prior to graduate school, she completed a Bachelor's Degree in Mechanical Engineering at the University of Virginia. Lily’s research interests focus around engineering student success, and making educational environments more inclusive for LGBTQIA+ and neurodiverse students in engineering.
Justin Charles Major
Purdue University at West Lafayette (COE)
orcid.org/0000-0002-3111-8509
Justin C. Major is a fourth-year Ph.D Candidate and National Science Foundation Graduate Research Fellow in the Purdue University Engineering Education Program. As an undergraduate student at the University of Nevada, Reno (UNR), Justin completed Bachelor's degrees in both Mechanical Engineering and Secondary Mathematics Education with an informal emphasis in engineering education. Through his involvement in the UNR PRiDE Research Lab and engagement with the UNR and Northern Nevada STEM Education communities, he studied student motivation, active learning, and diversity; developed K-12 engineering education curriculum; and advocated for socioeconomically just access to STEM education. As a Ph.D. Candidate with the STRiDE Research Lab at Purdue University, Justin's dissertation research focuses on the study of Intersectionality Theory and the intersectionality of socioeconomic inequality in engineering education, use of critical quantitative methodology and narrative inquiry to understand the complex stories of engineering students from traditionally minoritized backgrounds, and the pursuit of a socioeconomically just engineering education.
Matthew Scheidt
Purdue University at West Lafayette (COE)
orcid.org/0000-0001-6779-1992
Matthew Scheidt is a Ph.D. candidate in Engineering Education at Purdue University. He graduated from Purdue University with a B.S. in Mechanical Engineering, The Ohio State University with a M.S. in Mechanical Engineering with a focus in Ultrasonic Additive Manufacturing. Matt is currently part of Dr. Allison Godwin’s STRIDE (Shaping Transformative Research on Identity and Diversity in Engineering) research group at Purdue. Matt’s research interests include engineering student success, both quantitatively and qualitatively. He is also interested in military veterans' success in engineering
Julianna Ge
Purdue University at West Lafayette (COE)
orcid.org/0000-0002-0084-951X
Julianna Ge is a Ph.D. student in the School of Engineering Education at Purdue University. At Purdue, she created and currently teaches a novel course for undergraduate engineering students to explore the intersections of wellbeing, leadership, diversity and inclusion. As an NSF Graduate Research Fellow, her research interests intersect the fields of engineering education, positive psychology, and human development to understand diversity, inclusion, and success for undergraduate engineering students. Prior to Purdue, she received dual bachelor’s degrees in Industrial Engineering and Human Development and Family Studies from the University of Illinois at Urbana-Champaign. Her prior work experiences include product management, consulting, tutoring, marketing, and information technology.
Brian P. Self California Polytechnic State University, San Luis Obispo
Brian Self obtained his B.S. and M.S. degrees in Engineering Mechanics from Virginia Tech, and his Ph.D. in Bioengineering from the University of Utah. He worked in the Air Force Research Laboratories before teaching at the U.S. Air Force Academy for seven years. Brian has taught in the Mechanical Engineering Department at Cal Poly, San Luis Obispo since 2006. During the 2011-2012 academic year he participated in a professor exchange, teaching at the Munich University of Applied Sciences. His engineering education interests include collaborating on the Dynamics Concept Inventory, developing model-eliciting activities in mechanical engineering courses, inquiry-based learning in mechanics, and design projects to help promote adapted physical activities. Other professional interests include aviation physiology and biomechanics.
John Chen P.E. California Polytechnic State University, San Luis Obispo
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 student success.
James M. Widmann California Polytechnic State University, San Luis Obispo
Jim Widmann is a professor and chair of the Mechanical Engineering Department at California Polytechnic State University, San Luis Obispo. He received his Ph.D. from Stanford University and has served as a Fulbright Scholar at Kathmandu University in Nepal. At Cal Poly, he teaches the College of Engineering's interdisciplinary, industry sponsored, senior project class as well as course in mechanics and design. He also conducts research in the areas of creative design, machine design, fluid power control, and engineering education.
Allison Godwin
Purdue University at West Lafayette (COE)
orcid.org/0000-0002-0741-3356
Allison Godwin, Ph.D. is an Assistant Professor of Engineering Education at Purdue University. Her research focuses what factors influence diverse students to choose engineering and stay in engineering through their careers and how different experiences within the practice and culture of engineering foster or hinder belongingness 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 2016 American Society of Engineering Education Educational Research and Methods Division Best Paper Award and the 2018 Benjamin J. Dasher Best Paper Award for the IEEE Frontiers in Education Conference. She has also been recognized for the synergy of research and teaching as an invited participant of the 2016 National Academy of Engineering Frontiers of Engineering Education Symposium and the Purdue University 2018 recipient of School of Engineering Education Award for Excellence in Undergraduate Teaching and the 2018 College of Engineering Exceptional Early Career Teaching Award.
Edward J. Berger
Purdue University at West Lafayette (COE)
orcid.org/0000-0003-0337-7607
Edward Berger is an Associate 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 of specific technology interventions in mechanics classes. He was one of the co-leaders in 2013-2014 of the ASEE Virtual Community of Practice (VCP) for mechanics educators across the country. His current research focuses on student problem-solving processes and use of worked examples, change models and evidence-based teaching practices in engineering curricula, and the role of non-cognitive and affective factors in student academic outcomes and overall success.
Abstract
Undergraduate engineering student success, or potential for success, is traditionally determined by student performance on summative assessments such as exams, standardized tests, or by GPA. Recent literature shows that these traditional metrics may not be adequate measures of student success as even the “best” students (using the above measures) may not succeed in engineering. Rather, the literature suggests that non-cognitive and affective (NCA) factors also play an important role. In our larger grant project, we explore how students’ NCA factors might better predict their success. We also explore whether certain NCA factors are malleable and if initiatives can be developed to support the success of engineering students. The overall project is guided by the following research questions:
RQ1. What are the NCA profiles of engineering and computing students, and to what extent do profiles vary by institution, academic program, demographics, or over time? RQ2. In what ways are NCA factors predictors of academic performance, and how do they mediate a student’s response to academic or personal obstacles they may face? RQ3. To what extent can NCA-based interventions improve academic performance and the perceived quality of the undergraduate experience, and how do students at different institutions experience those interventions?
For the larger project, we have data on 28 different NCA factors from engineering students (n = 2339) at 21 institutions across the United States. We have also obtained institutional records such as those from our Dean of Students and Financial Aid offices for students at the three collaborating institutions on this project.
In the past year, we have used these data to predict various student outcomes and trends in educational pathways. We report on these different efforts in this paper. As a single example, through a scoping literature review and a concurrent Delphi study, we examine how engineering student success has been discussed in the engineering education literature, and compare it to how it is interpreted by academic professionals in engineering. Our goal is to redefine what success means more broadly than academic outcomes. To answer RQ1, we have conducted a cluster analysis of students’ NCA factors and connected those profiles to academic outcomes as well as negative outcomes such as substance abuse and academic dishonesty in college. These results can help us identify sets of NCA factors on which students may need additional support. In support of RQ2, we are using different modeling techniques to determine whether different outcomes such as GPA or retention in different classes or subjects can be predicted by NCA factors.
With the initial understanding of how and why NCA factors are important for engineering student success, we are beginning our future work to answer RQ3. In the coming year, we plan to develop pilot interventions based on malleable NCA factors to determine whether or not pedagogical practices can help students become more successful.
Krest, L., & Major, J. C., & Scheidt, M., & Ge, J., & Self, B. P., & Chen, J., & Widmann, J. M., & Godwin, A., & Berger, E. J. (2020, June), Examining the Importance of Noncognitive and Affective (NCA) Factors for Engineering Student Success Paper presented at 2020 ASEE Virtual Annual Conference Content Access, Virtual On line . 10.18260/1-2--34618
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