Showing 1 - 2 of 2 Research Library Publications

Leveraging Natural Language Processing: Toward Computer-Assisted Scoring of Patient Notes in the USMLE Step 2 Clinical Skills Exam

Posted: | J. Salt, P. Harik, M. A. Barone

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).

Category:Assessment-Oriented Research, Scoring, Applications of Technology, Product-Oriented Research, USMLE

The Optimal Number of Options for Multiple-Choice Questions on High-Stakes Tests: Application of a Revised Index for Detecting Nonfunctional Distractors

Posted: | M.R. Raymond, C. Stevens, S.D. Bucak

Adv in Health Sci Educ 24, 141–150 (2019)

 

Research suggests that the three-option format is optimal for multiple choice questions (MCQs). This conclusion is supported by numerous studies showing that most distractors (i.e., incorrect answers) are selected by so few examinees that they are essentially nonfunctional. However, nearly all studies have defined a distractor as nonfunctional if it is selected by fewer than 5% of examinees.

Category:Assessment-Oriented Research, General Measurement