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Using High School and District Economic Variables to Predict Engineering Persistence

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Conference

2012 ASEE Annual Conference & Exposition

Location

San Antonio, Texas

Publication Date

June 10, 2012

Start Date

June 10, 2012

End Date

June 13, 2012

ISSN

2153-5965

Conference Session

Before and After: Matriculants and Alumni

Tagged Division

Educational Research and Methods

Page Count

10

Page Numbers

25.1427.1 - 25.1427.10

Permanent URL

https://peer.asee.org/22184

Download Count

71

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Paper Authors

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Marisa K. Orr Purdue University Orcid 16x16 orcid.org/0000-0001-5944-5846

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Marisa K. Orr is a Postdoctoral Researcher in the School of Engineering Education at Purdue University, where she is part of the core MIDFIELD team. MIDFIELD is the Multiple-Institution Database for Investing Engineering Longitudinal Development that includes academic transcript data from eleven public universities from 1988-2009. The focus of Orr’s research is on developing new metrics and models to enhance our understanding of students, institutions, and policies. Orr earned her Ph.D., M.S., and B.S. in mechanical engineering from Clemson University, as well as a certificate in engineering and science education.

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Nichole M. Ramirez Purdue University

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Nichole M. Ramirez is a graduate student in the School of Engineering Education at Purdue University. She received her B.S. in aerospace engineering from the University of Alabama in 2010 and will complete her M.S. in aviation and aerospace management in May 2012. She is a recipient of the Purdue Doctoral Fellowship and currently serves as Committee Chair of the Engineering Education Graduate Student Association. In addition to socioeconomic research, she is also interested in studying ways to integrate aerospace engineering and aviation technology education.

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Matthew W. Ohland Purdue University, West Lafayette Orcid 16x16 orcid.org/0000-0003-4052-1452

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Matthew W. Ohland is Associate Professor 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, team assignment, peer evaluation, and active and collaborative teaching methods has been supported by more than $11.6 million from the National Science Foundation and the Sloan Foundation and his team received the William Elgin Wickenden Award for the Best Paper in the Journal of Engineering Education in 2008 and multiple conference Best Paper awards. Ohland is Past Chair of ASEE’s Educational Research and Methods division and an At-large member the Administrative Committee of the IEEE Education Society. He was the 2002-2006 President of Tau Beta Pi.

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Valerie Lundy-Wagner New York University

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Valerie Lundy-Wagner is is currently an Assistant Professor and Faculty Fellow in higher and post-secondary education at the Steinhardt School for Culture, Education, and Human Development at New York University. Her research focuses on how institutions can better support degree completion, with a special interest in demography (i.e., ethnicity/race, gender, and social class), engineering/STEM, and minority-serving institutions. She earned her doctorate in higher education at the University of Pennsylvania, master's at education at Stanford University, and B.S. in civil and environmental engineering at UCLA.

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Abstract

Engineering Enrollment, Persistence, and Academic Achievement as a Function of District and Peer Economic StatusThere is a growing socioeconomic status (SES) gap in higher education with increasing tuitionrates and decreasing aid, creating greater barriers for low SES students to overcome poverty.Prior research has shown that Peer Economic Status (PES), a socioeconomic indicator based on aschool’s free lunch participation, is predictive of enrollment in engineering, first-year GPA, andengineering degree completion. In that study, PES was calculated as an average over the entiretime period (1987-2004). To further explore the utility of this variable two new time-variantforms will be used, computed at the school-level and the district-level. Academic variables aredrawn from the Multiple Institution Database for Investigation of Engineering LongitudinalDevelopment (MIDFIELD) database and high school codes are used to link data from theNational Center for Education Statistics (NCES).The time-variant PES is calculated from the four years each student is expected to have been inhigh school. Additionally, a new algorithm for the treatment of missing values is utilized. Thedistrict economic status (DES) is computed in a similar fashion. A series of logistic and linearregression models is used to determine the impact of school- and district-level economic statusvariables on engineering enrollment, persistence to the 3rd semester, degree completion, and firstyear GPA. It is hypothesized that the time-variant PES will be a stronger indicator of studentoutcomes than the previous variable and that DES will have a similar relationship with theoutcome variables.The significance of this work is that it connects postsecondary outcomes to high school anddistrict characteristics. Findings can inform academic policy, as well as the recruiting andadvising of students from all socioeconomic strata by identifying potential roadblocks faced bystudents from low economic status schools and districts.

Orr, M. K., & Ramirez, N. M., & Ohland, M. W., & Lundy-Wagner, V. (2012, June), Using High School and District Economic Variables to Predict Engineering Persistence Paper presented at 2012 ASEE Annual Conference & Exposition, San Antonio, Texas. https://peer.asee.org/22184

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