Showing 1 - 4 of 4 Research Library Publications
Posted: | Ian Micir, Kimberly Swygert, Jean D'Angelo

Journal of Applied Technology: Volume 23 - Special Issue 1 - Pages 30-40

 

The interpretations of test scores in secure, high-stakes environments are dependent on several assumptions, one of which is that examinee responses to items are independent and no enemy items are included on the same forms. This paper documents the development and implementation of a C#-based application that uses Natural Language Processing (NLP) and Machine Learning (ML) techniques to produce prioritized predictions of item enemy statuses within a large item bank.

Posted: | Daniel Jurich, Michelle Daniel, Karen E. Hauer, Christine Seibert, Latha Chandran, Arnyce R. Pock, Sara B. Fazio, Amy Fleming, Sally A. Santen

Teaching and Learning in Medicine: Volume 33 - Issue 4 - p 366-381

 

CSE scores for students from eight schools that moved Step 1 after core clerkships between 2012 and 2016 were analyzed in a pre-post format. Hierarchical linear modeling was used to quantify the effect of the curriculum on CSE performance. Additional analysis determined if clerkship order impacted clinical subject exam performance and whether the curriculum change resulted in more students scoring in the lowest percentiles before and after the curricular change.

Posted: | M. M. Hammoud, L. M.Foster, M. M.Cuddy, D. B. Swanson, P. M. Wallach

American Journal of Obstetrics and Gynecology, Volume 223, Issue 3, Pages 435.e1-435.e6

 

The purpose of this study was to examine medical student reporting of electronic health record use during the obstetrics and gynecology clerkship.

Posted: | P. M. Wallach L. M. Foster, M. M. Cuddy, M. M. Hammoud, K. Z. Holtzman, D. B. Swanson

J Gen Intern Med 34, 705–711 (2019)

 

This study examines medical student accounts of EHR use during their internal medicine (IM) clerkships and sub-internships during a 5-year time period prior to the new clinical documentation guidelines.