Do GPAs, Entrance Exams, or Course Grades Predict Outcomes in First Semester Nursing Students?

Abstract

Background: Previous studies employed varying methods, predictors, and endpoints to determine how to best predict student success.

Purpose: This study examined current admission criteria in predicting nursing students' success during two first semester courses.

Methods: Grade point averages and Health Education Systems Incorporated entrance exam scores were extracted from student files while pre-nursing pathophysiology grades from electronic gradebooks were used as independent variables. A principal component analysis confirmed three components: Academic performance, logical/mathematical intelligence, and verbal/linguistic intelligence. Multiple regressions were performed using first semester nursing course grades as dependent variables.

Results: A multiple regression using Pharmacology course grades as the dependent variable (R² = 0.268, p ≤0.001) was more predictive than a regression using Concepts course grades as the dependent variable (R² = 0.177, p ≤0.001). Bivariate analyses revealed that each independent variable significantly predicted Concepts course grades and all except math and reading scores predicted Pharmacology course grades.

Conclusions: Pathophysiology was a better predictor of both dependent variables. A high degree of shared variance necessitated bivariate analyses to elucidate the importance of each independent variable. Pharmacology course grades proved better predictors of success by the independent variables than Concepts course grades.

Keywords: Admission criteria; Bivariate regression; Multiple regression; Nursing education; Nursing student success; Predictors; Principal component analysis; Selection methods.