RESEARCH LIBRARY
RESEARCH LIBRARY
View the latest publications from members of the NBME research team
Advancing Natural Language Processing in Educational Assessment
This book examines the use of natural language technology in educational testing, measurement, and assessment. Recent developments in natural language processing (NLP) have enabled large-scale educational applications, though scholars and professionals may lack a shared understanding of the strengths and limitations of NLP in assessment as well as the challenges that testing organizations face in implementation. This first-of-its-kind book provides evidence-based practices for the use of NLP-based approaches to automated text and speech scoring, language proficiency assessment, technology-assisted item generation, gamification, learner feedback, and beyond.
Medical Teacher: Volume 45 - Issue 6, Pages 565-573
This guide aims aim to describe practical considerations involved in reading and conducting studies in medical education using Artificial Intelligence (AI), define basic terminology and identify which medical education problems and data are ideally-suited for using AI.
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.
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.
Advances in Health Sciences Education: Volume 25, p 1057–1086 (2020)
This critical review explores: (1) published applications of data science and ML in HPE literature and (2) the potential role of data science and ML in shifting theoretical and epistemological perspectives in HPE research and practice.
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.
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.
Academic Medicine: Volume 95 - Issue 1 - p 111-121
This paper investigates the effect of a change in the United States Medical Licensing Examination Step 1 timing on Step 2 Clinical Knowledge (CK) scores, the effect of lag time on Step 2 CK performance, and the relationship of incoming Medical College Admission Test (MCAT) score to Step 2 CK performance pre and post change.
Academic Medicine: Volume 88 - Issue 11 - p 1670-1675
From 2007 through 2012, the NBME team reviewed literature in physician–patient communication, examined performance characteristics of the Step 2 CS exam, observed case development and quality assurance processes, interviewed SPs and their trainers, and reviewed video recordings of examinee–SP interactions. The authors describe perspectives gained by their team from the review process and outline the resulting enhancements to the Step 2 CS exam, some of which were rolled out in June 2012.