Springer International Publishing; 2019
This handbook provides an overview of major developments around diagnostic classification models (DCMs) with regard to modeling, estimation, model checking, scoring, and applications. It brings together not only the current state of the art, but also the theoretical background and models developed for diagnostic classification.
Academic Medicine: July 2019 - Volume 94 - Issue 7 - p 926-927
A response to concerns regarding potential bias in the implementation of machine learning (ML) to scoring of the United States Medical Licensing Examination Step 2 Clinical Skills (CS) patient notes (PN).
On the Cover. Educational Measurement: Issues and Practice, 38: 5-5
This informative graphic reports between‐individual information where a vertical line—with dashed lines on either side indicating an error band—spans three graphics allowing a student to easily see their score relative to four defined performance categories and, more notably, three relevant score distributions.
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.
Academic Medicine: March 2019 - Volume 94 - Issue 3 - p 371-377
Schools undergoing curricular reform are reconsidering the optimal timing of Step 1. This study provides a psychometric investigation of the impact on United States Medical Licensing Examination Step 1 scores of changing the timing of Step 1 from after completion of the basic science curricula to after core clerkships.
CBE—Life Sciences Education Vol. 18, No. 1
This article briefly reviews the aspects of validity that researchers should consider when using surveys. It then focuses on factor analysis, a statistical method that can be used to collect an important type of validity evidence.
Academic Medicine: March 2019 - Volume 94 - Issue 3 - p 314-316
The United States Medical Licensing Examination Step 2 Clinical Skills (CS) exam uses physician raters to evaluate patient notes written by examinees. In this Invited Commentary, the authors describe the ways in which the Step 2 CS exam could benefit from adopting a computer-assisted scoring approach that combines physician raters’ judgments with computer-generated scores based on natural language processing (NLP).
Psychometrika 84, 147–163 (2019)
This paper provides results on a form of adaptive testing that is used frequently in intelligence testing. In these tests, items are presented in order of increasing difficulty. The presentation of items is adaptive in the sense that a session is discontinued once a test taker produces a certain number of incorrect responses in sequence, with subsequent (not observed) responses commonly scored as wrong.
Investigación en Educación Médica, Vol. 8, Núm. 29, 2019