Modeling Freshman Engineering Success.

The objective of this research was to model freshman engineering success, using education theory and statistical modeling techniques. Freshman academic success and retention were modeled from pre-college characteristics. The UCLA/CIRP survey was used in this to survey students’ pre-college attitudes and experiences. An empirical analysis was conducted at the University of Michigan to validate the model using factor and regression analysis. Three research objectives were explored: • Define a proposed model based on the significant pre-college predictors of engineering student academic success and retention from the literature and determine if the empirical data support the proposed model. • Define and explore the effectiveness of selected intervention strategies for student academic success and retention. • Evaluate if the predictors of student success and retention are different for engineering students than for non-engineering students. Three student sectors other than engineering were considered: pre-med students; students pursuing an intended major in science, math or a technical field; and students with an intended major in the social sciences, humanities or business field. The significance of this research is that it proposed and validated a model for engineering student success. Prediction equations for both academic success and retention were developed. The modeling of freshman student success of the Engineering discipline was compared to the Pre-Med, STEM and Non-STEM disciplines. The only factor that was a common predictor for academic success for all four disciplines was the factor that included the high school GPA and class rank. All other significant predictors were discipline specific. This finding supports that the modeling of freshman engineering student success is different from the modeling of general college freshman success. Significant predictors unique to freshman engineering academic success (GPA) included the factors related to quantitative skills preparation (ACT Math and Science test scores and the math and chemistry placement tests) and confidence in quantitative skills (self-rating of math and computer abilities). Significant predictors for freshman engineering retention were high school rank and concern about financing a college education.PhDIndustrial & Operations EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/58391/4/cpveenst_1.pd