Title

Joining the conversation: Predictors of success on the United States Medical Licensing Examinations (USMLE)

Document Type

Article

Publication Date

2011

Abstract

The purpose of this study was to evaluate whether models based on pre-­admission testing, including performance on the Medical College Admission Test (MCAT), performance on required courses in the medical school curriculum, or a combination of both could accurately predict performance of medical students on the United States Medical Licensing Examination (USMLE) Steps 1 and 2. Models were produced using stepwise linear regression and feed forward neural networks. Notable accuracy in predicting Step 1 and Step 2 scores were achieved from models integrating pre-admission variables with medical school coursework grades. Of interest, the coursework grades contributed far greater to these models than the pre-admission variables except the MCAT.

Comments

The copy of record is available from the publisher at http://www.nclca.org/tlar_back_issues/spring11vol16num1.pdf#page=13. Copyright © 2011 Learning Assistance Review. Reprinted with permission. All rights reserved.