Predicting Student Success Using In-Program Monitoring.

Area of Science:

• Pharmacy Education
• Student Success Metrics
• Academic Intervention

Background:

• Traditional admissions metrics like GPA and PCAT scores have historically shown limited predictive power for student success in demanding pharmacy programs.
• Identifying reliable predictors of academic performance in the first year of pharmacy school remains a challenge.

Purpose of the Study:

• To evaluate the predictive value of admissions data versus academic monitoring for first-year Doctor of Pharmacy (PharmD) student success.
• To determine if early intervention strategies enhance student outcomes in foundational coursework.

Main Methods:

• Systematic literature review on student success metrics.
• Retrospective analysis of internal admissions data and first-year outcomes (2016-2019).
• Interim evaluation of voluntary academic monitoring and mentoring programs.

Main Results:

• Pre-pharmacy GPA, science GPA, PCAT scores, and prior degrees showed some predictive value, but a significant gap exists in forecasting student success.
• While admissions data can stratify students by predicted ability, early monitoring and intervention proved to be an actionable method for improving success.

Conclusions:

• Quantitative admissions measures (GPA, PCAT) have limited predictive value for pharmacy student success.
• Institution-specific, first-year data monitoring (e.g., midterm grades) is crucial for directing targeted interventions and remediation.
• Proactive academic support significantly benefits students in succeeding in the first year of pharmacy education.