Predicting Achievement and Improving Equity in Engineering Using Contextualized High School Performance

PERIOD:

Aug 15, 2020

TO

Jul 31, 2022
Funding Agency
National Science Foundation

Michael Bastedo leads this project to improve the number of well-qualified women, low-income students, and students of color who pursue and obtain postsecondary engineering degrees.

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In previous NSF-funded research, the investigator concluded that the use of contextualized high school performance in engineering admissions has the potential to increase the number of women, low-income students, and students of color in engineering. Yet surprisingly little is known about how contextualized high school performance relates to student success in engineering. The research that exists, however, suggests that doing well in high school compared to your peers has predictive validity above and beyond the student’s raw credentials.

This project solves significant data, design, and methodological challenges to investigate this question, and the investigator will create a unique dataset drawn from state unit-record data and data from institutional inventories of ABET-accredited engineering programs within that state. Doctoral students Emma Bausch and Bo-Kyung Byun will contribute to the project, as well as Ford School researcher Mark Umbricht.

Primary Investigator(s)

Director, Center for the Study of Higher and Postsecondary Education; Professor

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