Showing 1 - 5 of 5 Research Library Publications
Posted: | Jonathan D. Rubright, Thai Q. Ong, Michael G. Jodoin, David A. Johnson, Michael A. Barone

Academic Medicine: Volume 97 - Issue 8 - Pages 1219-1225

 

Since 2012, the United States Medical Licensing Examination (USMLE) has maintained a policy of ≤ 6 attempts on any examination component. The purpose of this study was to empirically examine the appropriateness of existing USMLE retake policy.

Posted: | F.S. McDonald, D. Jurich, L.M. Duhigg, M. Paniagua, D. Chick, M. Wells, A. Williams, P. Alguire

Academic Medicine: September 2020 - Volume 95 - Issue 9 - p 1388-1395

 

This article aims to assess the correlations between United States Medical Licensing Examination (USMLE) performance, American College of Physicians Internal Medicine In-Training Examination (IM-ITE) performance, American Board of Internal Medicine Internal Medicine Certification Exam (IM-CE) performance, and other medical knowledge and demographic variables.

Posted: | L. E. Peterson, J. R. Boulet, B. E. Clauser

Academic Medicine: Volume 95 - Issue 9 - p 1396-1403

 

The objective of this study was to evaluate the associations of all required standardized examinations in medical education with ABFM certification examination scores and eventual ABFM certification.

Posted: | M. J. Margolis, M. von Davier, B. E. Clauser

Integrating Timing Considerations to Improve Testing Practices

 

This chapter addresses timing considerations in the context of other types of performance assessments and reports on a previously unpublished experiment examining timing with respect to performance on computer-based case simulations that are used in physician licensure.

Posted: | M. J. Margolis, B. E. Clauser

Handbook of Automated Scoring

 

In this chapter we describe the historical background that led to development of the simulations and the subsequent refinement of the construct that occurred as the interface was being developed. We then describe the evolution of the automated scoring procedures from linear regression modeling to rule-based procedures.