Course and Standardized Exam Statistics in Mechanical Engineering
- Conference
- Location
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Salt Lake City, Utah
- Publication Date
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June 23, 2018
- Start Date
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June 23, 2018
- End Date
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July 27, 2018
- Conference Session
- Tagged Division
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Mechanical Engineering
- Tagged Topic
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Diversity
- Page Count
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16
- DOI
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10.18260/1-2--30228
- Permanent URL
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https://peer.asee.org/30228
- Download Count
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432
Paper Authors
Jessica Lofton University of Evansville
Dr. Lofton is an Assistant Professor of Mechanical Engineering at the University of Evansville. She is the Director for the OPTIONS in Engineering summer camps for middle school and high school girls.
Jared T. Fulcher University of Evansville
Dr. Fulcher is an assistant professor of mechanical engineering at the University of Evansville. He is faculty adviser of the student chapter of the Society of Automotive Engineers (SAE) and faculty adviser to the UE SAE Baja Design Team. He is also the faculty adviser of Tau Delta Kappa, the University of Evansville Engineering Honor Society. He earned a B.S. in Mechanical Engineering at the University of Kentucky Extended Campus in Paducah, KY. He received both a M.S. and a PhD. in Mechanical Engineering from the University of Kentucky in Lexington, KY.
Dick Blandford University of Evansville
Dick Blandford is the department chair of the Electrical Engineering and Computer Science Department at the University of Evansville.
Abstract
This paper investigates the link between course and national exam performance with success in an undergraduate mechanical engineering program. Success in the program is measured by cumulative GPA at graduation and GPA in ME courses. The data include SAT/ACT scores, high school GPA, and grades for math, science, and engineering courses taken in the first two years of the undergraduate mechanical engineering program. The data are analyzed seeking a correlation with success in the major using two methods. The first method examines relationships with individual data items and success in the major. Results suggest that alternatives to standardized exam scores can act as predictors for success in mechanical engineering. The second method uses an optimal weighting sequence to establish linear combinations of various data items for prediction of success in the major. The results may be useful to evaluate and establish entrance requirements for high school students applying to the program and for upper level admission requirements implemented to restrict access to junior and senior level courses. The data are limited to a small sample of mechanical engineering students that have completed a BSME program at a private institution in the Midwest.
Lofton, J., & Fulcher, J. T., & Blandford, D. (2018, June), Course and Standardized Exam Statistics in Mechanical Engineering Paper presented at 2018 ASEE Annual Conference & Exposition , Salt Lake City, Utah. 10.18260/1-2--30228
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