A Primer on Working with Longitudinal Student Unit Records
- Conference
- Location
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Baltimore , Maryland
- Publication Date
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June 25, 2023
- Start Date
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June 25, 2023
- End Date
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June 28, 2023
- Conference Session
- Tagged Division
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New Engineering Educators Division (NEE)
- DOI
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10.18260/1-2--44629
- Permanent URL
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https://strategy.asee.org/44629
Paper Authors
Russell Andrew Long Purdue University
Russell Long, M.Ed. was the Director of Project Assessment at the Purdue University School of Engineering Education (retired) and is Managing Director of The Multiple-Institution Database for Investigating Engineering Longitudinal Development (MIDFIELD).
Richard A. Layton Layton Data Display
Richard A. Layton is Professor Emeritus of Mechanical Engineering at Rose-Hulman Institute of Technology. He received a B.S. from California State University, Northridge, and an M.S. and Ph.D. from the University of Washington. With Matthew Ohland, Layton is a co-founding developer of the CATME Smarter Teamwork system and the midfieldr R package for working with student unit records. He is a co-author of the Engineering Communications Manual, Oxford Univ. Press, 2017. He currently consults as a data visualization specialist using R.
Marisa K. Orr
Clemson University
orcid.org/0000-0001-5944-5846
Marisa K. Orr is an Associate Professor in Engineering and Science Education with a joint appointment in the Department of Mechanical Engineering at Clemson University.
Susan M. Lord
University of San Diego
orcid.org/0000-0002-2675-5626
Susan Lord is Professor and Chair of Integrated Engineering at the University of San Diego. She received a BS from Cornell University in Materials Science and Electrical Engineering (EE) and MS and PhD in EE from Stanford University. Her research focuses on the study and promotion of equity in engineering including student pathways and inclusive teaching. She has won best paper awards from the Journal of Engineering Education, IEEE Transactions on Education, and Education Sciences. Dr. Lord is a Fellow of the IEEE and ASEE and received the 2018 IEEE Undergraduate Teaching Award. She is a coauthor of The Borderlands of Education: Latinas in Engineering. She is a co-Director of the National Effective Teaching Institute (NETI).
Matthew W. Ohland
Purdue University
orcid.org/0000-0003-4052-1452
Matthew W. Ohland is the Dale and Suzi Gallagher Professor and Associate Head of Engineering Education at Purdue University. He has degrees from Swarthmore College, Rensselaer Polytechnic Institute, and the University of Florida. His research on the longitudinal study of engineering students and forming and managing teams has been supported by the National Science Foundation and the Sloan Foundation and his team received for the best paper published in the Journal of Engineering Education in 2008, 2011, and 2019 and from the IEEE Transactions on Education in 2011 and 2015. Dr. Ohland is an ABET Program Evaluator for ASEE. He was the 2002–2006 President of Tau Beta Pi and is a Fellow of the ASEE, IEEE, and AAAS.
Abstract
Longitudinal, student-level data are a rich resource for characterizing how students navigate the terrain of higher education. Learning to work effectively with such data, however, can be a challenge. In this paper, we share some of our experiences over years of conducting research with the Multiple Institution Database for Investigating Engineering Longitudinal Development (MIDFIELD). MIDFIELD contains individual student-level records for all undergraduate students at 19 US institutions with over 1.7 million unique students. This paper focuses on our lessons learned about processing longitudinal data to prepare it for analysis. We describe and define the steps that we take to process the data including filtering for data sufficiency, degree-seeking, and program (major), then classifying by completion status and demographics. We use the examples of calculation of graduation rate and stickiness to show the details of how the processed data is used in analysis. We hope this paper will help introduce the landscape of longitudinal research to a wider audience and provide tips for working with this valuable resource.
Long, R. A., & Layton, R. A., & Orr, M. K., & Lord, S. M., & Ohland, M. W. (2023, June), A Primer on Working with Longitudinal Student Unit Records Paper presented at 2023 ASEE Annual Conference & Exposition, Baltimore , Maryland. 10.18260/1-2--44629
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