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Predictors of First-year Retention Among Undergraduate Engineering Students Who Earn a C in their First-semester Math Course

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2020 ASEE Virtual Annual Conference Content Access


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Publication Date

June 22, 2020

Start Date

June 22, 2020

End Date

June 26, 2021

Conference Session

The Best of First-year Programs Division

Tagged Division

First-Year Programs

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Paper Authors


Campbell R. Bego University of Louisville Orcid 16x16

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An instructor and postdoctoral researcher in engineering education, Campbell R. Bego, PhD, PE, is interested in improving STEM student learning and gaining understanding of STEM-specific learning mechanisms through controlled implementations of evidence-based practices in the classroom. Dr. Bego has an undergraduate Mechanical Engineering degree from Columbia University, a Professional Engineering license in the state of NY, and a doctorate in Cognitive Science.

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Jason Immekus University of Louisville

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Dr. Immekus is associate professor in the Department of Educational Leadership, Evaluation, and Organizational Development.

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Jeffrey Lloyd Hieb University of Louisville

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Jeffrey L. Hieb is an Associate Professor in the Department of Engineering Fundamentals at the University of Louisville. He graduated from Furman University in 1992 with degrees in Computer Science and Philosophy. After 10 years working in industry, he returned to school, completing his Ph.D. in Computer Science Engineering at the University of Louisville’s Speed School of Engineering in 2008. Since completing his degree, he has been teaching engineering mathematics courses and continuing his dissertation research in cyber security for industrial control systems. In his teaching, Dr. Hieb focuses on innovative and effective use of tablets, digital ink, and other technology and is currently investigating the use of the flipped classroom model and collaborative learning. His research in cyber security for industrial control systems is focused on high assurance field devices using microkernel architectures.

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This study examines non-cognitive predictors of first-year engineering retention for students who received a C in their first semester mathematics course. Scores across eight non-cognitive measures served as model predictors, obtained at the onset of the freshmen year, including: value interest in engineering, perceived effort, opportunity, and psychological costs, perceived belonging uncertainty, contingencies of self-worth: academic competence, test anxiety, and self-efficacy. Results based on least absolute shrinkage and selection operator regression reported that value interest and test anxiety were the best predictors of C-student retention. The results from this study inform research on the decision-making of students that have potential for graduation but are at risk of leaving engineering. Our results indicate that a strategic intervention in increasing interest in engineering may lead to strong gains in engineering retention at this university, and potentially others as well.

Bego, C. R., & Immekus, J., & Hieb, J. L. (2020, June), Predictors of First-year Retention Among Undergraduate Engineering Students Who Earn a C in their First-semester Math Course Paper presented at 2020 ASEE Virtual Annual Conference Content Access, Virtual On line . 10.18260/1-2--35076

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