RESEARCH LIBRARY
RESEARCH LIBRARY
View the latest publications from members of the NBME research team
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.
Journal of Educational Measurement: Volume 58, Issue 4, Pages 515-537
In this paper, the NBME team reports the results an eye-tracking study designed to evaluate how the presence of the options in multiple-choice questions impacts the way medical students responded to questions designed to evaluate clinical reasoning. Examples of the types of data that can be extracted are presented. We then discuss the implications of these results for evaluating the validity of inferences made based on the type of items used in this study.
Medical Science Educator: Volume 31, p 607–613 (2021)
This study extended previous research on the NBME Clinical Science Mastery Series self-assessments to investigate the utility of recently released self-assessments for students completing Family Medicine clerkships and Emergency Medicine sub-internships and preparing for summative assessments.
ACM SIGACCESS Accessibility and Computing
In this article, we first summarise STA (Scanpath Trend Analysis) with its application in autism detection, and then discuss future directions for this research.
Evaluation & the Health Professions: Volume: 43 issue: 3, page(s): 149-158
This study examines the innovative and practical application of DCM framework to health professions educational assessments using retrospective large-scale assessment data from the basic and clinical sciences: National Board of Medical Examiners Subject Examinations in pathology (n = 2,006) and medicine (n = 2,351).
Educational Measurement: Issues and Practice
This short, invited manuscript focuses on the implications for certification and licensure assessment organizations as a result of the wide‐spread disruptions caused by the COVID-19 pandemic.
IEEE Transactions on Neural Systems and Rehabilitation Engineering
The purpose of this study is to test whether visual processing differences between adults with and without high-functioning autism captured through eye tracking can be used to detect autism.
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).
Investigación en Educación Médica, Vol. 8, Núm. 29, 2019
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.