Cindy P. Veenstra recently earned her Ph.D. in Industrial and Operations Engineering at the University of Michigan. The research discussed in this paper was part of her Ph.D. Her research interests are in applying quality engineering methodology and systems thinking to engineering education, especially to the retention of freshman engineering students. She also holds a M.S. in Statistics and a M.S. in Industrial and Operations Engineering. She is a member of ASEE, INFORMS, SME and an ASQ Fellow.
Is Modeling of Freshman Engineering Success Different from Modeling of Non-Engineering Success?
Version of Record online: 2 JAN 2013
2008 American Society for Engineering Education
Journal of Engineering Education
Volume 97, Issue 4, pages 467–479, October 2008
How to Cite
Veenstra, C. P., Dey, E. L. and Herrin, G. D. (2008), Is Modeling of Freshman Engineering Success Different from Modeling of Non-Engineering Success?. Journal of Engineering Education, 97: 467–479. doi: 10.1002/j.2168-9830.2008.tb00993.x
- Issue online: 2 JAN 2013
- Version of Record online: 2 JAN 2013
- CIRP survey;
- freshman engineering success;
- pre-college characteristics
The engineering community has recognized the need for a higher retention rate in freshman engineering. If we are to increase the freshman retention rate, we need to better understand the characteristics of academic success for engineering students. One approach is to compare academic performance of engineering students to that of non-engineering students. This study explores the differences in predicting academic success (defined as the first year GPA) for freshman engineering students compared to three non-engineering student sectors (Pre-Med, STEM, and non-STEM disciplines) within a university. Academic success is predicted with pre-college variables from the UCLA/CIRP survey using factor analysis and regression analysis. Except for the factor related to the high school GPA and rank, the predictors for each student sector were discipline specific. Predictors unique to the engineering sector included the factors related to quantitative skills (ACT Math and Science test scores and placement test scores) and confidence in quantitative skills.