2025 ASEE Annual Conference & Exposition

BPE: Year Three of Developing a New Dataset for Analyzing Engineering Curricula

Presented at NSF Grantees Poster Session II

This paper outlines the results obtained during Year 3 of a Broadening Participation in Engineering project through the National Science Foundation concerning structural barriers that can push diverse subgroups of students out of engineering. We specifically focus on curricular factors using an emerging framework based in network analysis that can quantify the “complexity” of engineering curricula. We have curated a dataset of 497 plans of study representing five engineering disciplines (Mechanical, Civil, Electrical, Chemical, and Industrial) across 13 institutions within the Multiple Institution Database for Investigating Engineering Longitudinal Development (MIDFIELD), which – among other demographic variables – contains course-taking records for all students. By aligning our plan of study dataset with MIDFIELD, we aim to enable the synthesis of the two data sources to parse out the educational trajectories of engineering students in the dataset.

In Year 3, we have focused on three primary activities: (1) mining course-taking trajectories for students in the MIDFIELD dataset to compare the uncovered patterns with the codified plans of studies, (2) distributing the dataset and functionality to analyze the plans of study through a comprehensive R package, and (3) conducting a scoping review to collect other possible metrics for researchers and practitioners to use in conjunction with the dataset or their own data.

Regarding the first activity, we have explored course-taking patterns in the five engineering disciplines under study at the 13 institutions within our dataset using association analysis. Through this process, we extracted common bundles of courses taken by students and overlayed those bundles within the plan of study networks. In this paper, we will provide sample visualizations to highlight how merging the two datasets can provide insights into the varied pathways in which students approach their degree program requirements.
Regarding the second and third activities, our R package is ready for public use and is currently being used by a set of early-adopting institutions. We will provide sample outputs to outline its essential functionality and include a list of metrics we have added to our package based on our scoping review of the literature describing other network-based measurements used to characterize the complexity of engineering programs. Our scoping review draws from a set of 159 papers that cited foundational papers on Curricular Analytics to capture how the framework has evolved since it was originally proposed in 2013.

Through this project, we contend our primary impact is drawing insights from already available data and providing the engineering education community with ready-to-use tools for analyzing their own curricula within a standard statistical programming platform used in the field. Moreover, by deconstructing the varied pathways students take to an engineering degree, we can better understand what curricular bottlenecks exist for students and find appropriate ways to increase the flexibility of our programs to enable a broader population of students to succeed.

Authors

Dr. David Reeping http://orcid.org/0000-0002-0803-7532 University of Cincinnati [biography]

Dr. David Reeping is an Assistant Professor in the Department of Engineering and Computing Education at the University of Cincinnati. He earned his Ph.D. in Engineering Education from Virginia Tech and was a National Science Foundation Graduate Research Fellow. He received his B.S. in Engineering Education with a Mathematics minor from Ohio Northern University. His main research interests include transfer student information asymmetries, threshold concepts, curricular complexity, and advancing quantitative and fully integrated mixed methods.
Dr. Matthew W. Ohland http://orcid.org/0000-0003-4052-1452 Purdue University at West Lafayette (PWL) (COE) [biography]

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 and represents ASEE on the Engineering Accreditation Commission. He was the 2002–2006 President of Tau Beta Pi and is a Fellow of the ASEE, IEEE, and AAAS. He was inducted into the ASEE Hall of Fame in 2023.
Dr. Kenneth Reid http://orcid.org/0000-0003-2337-7495 University of Indianapolis [biography]

Kenneth Reid is the Associate Dean and Director of Engineering at the R. B. Annis School of Engineering at the University of Indianapolis. He and his coauthors were awarded the Wickenden award (Journal of Engineering Education, 2014) and Best Paper award, Educational Research and Methods Division (ASEE, 2014). He was awarded an IEEE-USA Professional Achievement Award (2013) for designing the B.S. degree in Engineering Education. He is a co-PI on the “Engineering for Us All” (e4usa) project to develop a high school engineering course “for all”. He is active in engineering within K-12, (Technology Student Association Board of Directors) and has written multiple texts in Engineering, Mathematics and Digital Electronics. He earned a PhD in Engineering Education from Purdue University, is a Senior Member of IEEE, on the Board of Governors of the IEEE Education Society, and a Member of Tau Beta Pi.
Dr. Hossein EbrahimNejad Drexel University [biography]

Hossein EbrahimiNejad is a data scientist currently working with the office of Enrollment Analytics at Drexel University. He received his PhD in Engineering Education from Purdue University, where he gained a strong knowledge of higher education and strategic enrollment management. Hossein's skills in data management, data visualization, and predictive modeling allow him to empower stakeholders to make strategic decisions using advanced analytic information. With Drexel's commitment to promoting and supporting student success, Hossein's work with Enrollment Analytics allows the University to make data-driven strategic decisions regarding enrollment and financial projections that are as effective and efficient as possible.
NAHAL RASHEDI University of Cincinnati [biography]

PhD Student of Engineering Education
Yunmeng Han University of Cincinnati [biography]

Yunmeng Han is a PhD student in Engineering Education at the University of Cincinnati. She holds a Master’s degree in Computer Science from Northeastern University and serves as a reviewer for prominent engineering education conferences, including ASEE 2025. Yunmeng has been actively involved in NSF-funded research projects and is experienced in applying both quantitative and mixed-method research designs.

Note

The full paper will be available to logged in and registered conference attendees once the conference starts on June 22, 2025, and to all visitors after the conference ends on June 25, 2025

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