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Optimal Sequencing of Graduate Funding in a Chemical Engineering Department: Maximizing Completion and Persistence Rates

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Conference

2020 ASEE Virtual Annual Conference Content Access

Location

Virtual On line

Publication Date

June 22, 2020

Start Date

June 22, 2020

End Date

June 26, 2021

Conference Session

Graduate Education Expectations, Preparation, and Pathways

Tagged Division

Educational Research and Methods

Tagged Topic

Diversity

Page Count

15

DOI

10.18260/1-2--35014

Permanent URL

https://peer.asee.org/35014

Download Count

159

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Paper Authors

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Maya Denton University of Texas at Austin

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Maya Denton is a STEM Education doctoral student and Graduate Research Assistant in the Center for Engineering Education at the University of Texas at Austin. She received her B.S. in Chemical Engineering from Purdue University. Prior to attending UT-Austin, she worked as a chemical engineer for an industrial gas company.

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Nathan Hyungsok Choe Ohio State University Orcid 16x16 orcid.org/0000-0002-5662-0853

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Dr. Nathan (Hyungsok) Choe is a research assistant professor in department of engineering education at the Ohio State University.
He obtained his PhD in STEM education at UT Austin. His research focuses on the development of engineering identity in graduate school and underrepresented group. Dr. Choe holds master’s and bachelor’s degrees in electrical engineering from Illinois Tech. He also worked as an engineer at LG electronics mobile communication company.

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Maura J. Borrego University of Texas at Austin

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Maura Borrego is Director of the Center for Engineering Education and Professor of Mechanical Engineering and STEM Education at the University of Texas at Austin. Dr. Borrego is Senior Associaate Editor for Journal of Women and Minorities in Science and Engineering. She previously served as Deputy Editor for Journal of Engineering Education, a Program Director at the National Science Foundation, on the board of the American Society for Engineering Education, and as an associate dean and director of interdisciplinary graduate programs. Her research awards include U.S. Presidential Early Career Award for Scientists and Engineers (PECASE), a National Science Foundation CAREER award, and two outstanding publication awards from the American Educational Research Association for her journal articles. All of Dr. Borrego’s degrees are in Materials Science and Engineering. Her M.S. and Ph.D. are from Stanford University, and her B.S. is from University of Wisconsin-Madison.

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David B. Knight Virginia Polytechnic Institute and State University Orcid 16x16 orcid.org/0000-0003-4576-2490

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David B. Knight is an Associate Professor and Assistant Department Head of Graduate Programs in the Department of Engineering Education at Virginia Tech. He is also Director of Research of the Academy for Global Engineering at Virginia Tech, and is affiliate faculty with the Higher Education Program. His research tends to be at the macro-scale, focused on a systems-level perspective of how engineering education can become more effective, efficient, and inclusive, tends to be data-driven by leveraging large-scale institutional, state, or national data sets, and considers the intersection between policy and organizational contexts. He has B.S., M.S., and M.U.E.P. degrees from the University of Virginia and a Ph.D. in Higher Education from Pennsylvania State University.

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Abstract

Our research paper examines the sequence with which engineering doctoral students are funded through different mechanisms, such as research or teaching assistantships or fellowships, which impact their training, experiences, and time to degree. Prior research using the Survey of Earned Doctorates suggests that engineering students funded primarily by research assistantships complete their PhDs on average one semester earlier than students funded primarily by teaching assistantships. However, many doctoral students are funded by multiple sources in various sequences, and national datasets such as Survey of Earned Doctorates do not include semester-by-semester detail about funding nor include students who do not complete a PhD. Using a detailed institutional database, we investigated whether and how the timing and type of funding relates to persistence and completion among chemical engineering doctoral students at a large public research institution. Funding mechanisms were categorized as Teaching Assistantship (TA), Research Assistantship (RA), Fellowship, and No University Funding. This program requires all students to serve as a TA prior to degree completion, which raises an interesting policy question of the optimal timing with respect to student degree progress. Our research question is as follows: How, if at all, does being funded through a TA, RA, or fellowship in a given year predict the 3-, 4-, and 5-year persistence rates and 4-, 5-, and 6-year completion rates of chemical engineering doctoral students? The data include information on enrollment, degree completion and total dollar amount of funding by month in RA, TA and fellowship categories for all chemical engineering students since 1992. We report count and percentage data related to type of funding for all participants entering from 1992 to 2011. Then, we ran step-wise logistic regression models, which predicted persistence through Years 3, 4, and 5 and completion in Years 4, 5, and 6. Predictors for all logistic regression models included the type of funding in a specific year (e.g., Fellowship 2nd Year or RA 4th Year). Treating funding types as separate variables accounts for the possibility of multiple types of funding for a single participant, with “No University Funding” serving as the reference group in the models. Results from the logistic regression models empirically support conventional wisdom about graduate student funding. First, any type of funding is better than no university funding. Having a TA assignment early on or an RA during the middle of graduate school positively predicts student persistence. Second, students supported via RAs and fellowships have stronger persistence and graduation rates than TAs, with the highest, followed by fellowships. Third, completing a TA assignment in later years negatively predicts degree completion. Although the results are not unexpected, it is important to use empirical evidence to support policy decisions related to allocation of graduate student funding. This research will help graduate program leaders make policy decisions related to allocation of limited funding resources to improve retention and completion rates of all engineering PhD students.

Denton, M., & Choe, N. H., & Borrego, M. J., & Knight, D. B. (2020, June), Optimal Sequencing of Graduate Funding in a Chemical Engineering Department: Maximizing Completion and Persistence Rates Paper presented at 2020 ASEE Virtual Annual Conference Content Access, Virtual On line . 10.18260/1-2--35014

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