
RESEARCH LIBRARY
RESEARCH LIBRARY
View the latest publications from members of the NBME research team
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.
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: November 2018 - Volume 93 - Issue 11S - p S14-S20
An important goal of medical education is to teach students to use an electronic health record (EHR) safely and effectively. The purpose of this study is to examine medical student accounts of EHR use during their core inpatient clinical clerkships using a national sample. Paper health records (PHRs) are similarly examined.
Journal of Educational Measurement: Volume 55, Issue 4, Pages 582-594
This article proposes and evaluates a new method that implements computerized adaptive testing (CAT) without any restriction on item review. In particular, it evaluates the new method in terms of the accuracy on ability estimates and the robustness against test‐manipulation strategies. This study shows that the newly proposed method is promising in a win‐win situation: examinees have full freedom to review and change answers, and the impacts of test‐manipulation strategies are undermined.
Medical Teacher: Volume 40 - Issue 8 - p 838-841
Adaptive learning requires frequent and valid assessments for learners to track progress against their goals. This study determined if multiple-choice questions (MCQs) “crowdsourced” from medical learners could meet the standards of many large-scale testing programs.
Quality Assurance in Education, Vol. 26 No. 2, pp. 150-152
An introduction to a special issue of Quality Assurance in Education featuring papers based on presentations at a two-day international seminar on managing the quality of data collection in large-scale assessments.
Psychometrika 83, 847–857 (2018)
Utilizing algorithms to generate items in educational and psychological testing is an active area of research for obvious reasons: Test items are predominantly written by humans, in most cases by content experts who represent a limited and potentially costly resource. Using algorithms instead has the appeal to provide an unlimited resource for this crucial part of assessment development.