Predicting Medical School Enrollment Behavior: Comparing an Enrollment Management Model to Expert Human Judgment.

Purpose: Medical school admissions committees are tasked with fulfilling the values of their institutions through careful recruitment. Making accurate predictions regarding enrollment behavior of admitted students is critical to intentionally formulating class composition and impacts long-term physician representation. The predictive accuracy and potential advantages of employing an enrollment predictive model in medical school admissions compared with expert human judgment have not been tested.

Enrollment Management in Medical School Admissions: A Novel Evidence-Based Approach at One Institution.

Purpose: In higher education, enrollment management has been developed to accurately predict the likelihood of enrollment of admitted students. This allows evidence to dictate numbers of interviews scheduled, offers of admission, and financial aid package distribution. The applicability of enrollment management techniques for use in medical education was tested through creation of a predictive enrollment model at the University of Michigan Medical School (U-M).

Predictive efficacy of Chiropractic College Assessment Test scores in basic science chiropractic education.

Objective: To evaluate the ability of Chiropractic College Assessment Test (CCAT) to explain academic success within a chiropractic basic science curriculum.

Methods: The CCAT examination was administered to 202 subjects from 1 chiropractic college on the first day of classes. Zero-order Pearson correlations were used to examine for associations between the prechiropractic grade point average (GPA), CCAT scores, and basic science GPA.