Showing 1 - 4 of 4 Research Library Publications
Posted: | Katie L. Arnhart, Monica M. Cuddy, David Johnson, Michael A. Barone, Aaron Young

Academic Medicine: Volume 97 - Issue 4 - Pages 476-477

 

Response to to emphasize that although findings support a relationship between multiple USMLE attempts and increased likelihood of receiving disciplinary actions, the findings in isolation are not sufficient for proposing new policy on how many attempts should be allowed.

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: | Katie L. Arnhart, Monica M. Cuddy, David Johnson, Michael A. Barone, Aaron Young

Academic Medicine: Volume 96 - Issue 9 - Pages 1319-1323

 

This study examined the relationship between USMLE attempts and the likelihood of receiving disciplinary actions from state medical boards.

Posted: | Monica M. Cuddy, Aaron Young, Andrew Gelman, David B. Swanson, David A. Johnson, Gerard F. Dillon, Brian E. Clauser

The authors examined the extent to which USMLE scores relate to the odds of receiving a disciplinary action from a U.S. state medical board.