Predicting student success using in-program monitoring

Objective. To determine whether admissions data alone adequately predicts student success in the first-year doctor of pharmacy (PharmD) curriculum or whether academic monitoring and intervention has greater value toward successful completion of first-year coursework. Methods. A systematic evaluation of the literature assessing student success was performed to ascertain historical evidence of student success metrics. We then retrospectively analyzed internal admissions data and first-year outcomes for our pharmacy classes of 2016-2019 using available data. We conducted an interim evaluation of voluntary academic monitoring and mentoring with the hypothesis that admission data alone cannot predict student success in early foundational coursework, and intentional intervention might improve success. Results. Pre-pharmacy grade point average (GPA), science GPA, Pharmacy College Admission Test (PCAT) score, and prior degree status each retain some predictive value regarding success, and combinations of these factors may improve the ability to predict student success in early foundational coursework. There remains a significant, and perhaps insurmountable, gap in identifying quantitative metrics that forecast student success. Although admission data can stratify incoming students based on predicted academic ability, early monitoring and intervention provide an actionable means for enhancing student success in first-year coursework. Conclusion. Quantitative academic measures, such as PCAT scores and GPA, historically have demonstrated limited value in predicting student success. While these measures allow stratification of predicted academic performance among incoming students, monitoring of first-year, institution-specific data, such as midterm grades, can direct intentional intervention and remediation strategies that may provide more benefit to ensure students succeed.