Showing 1 - 3 of 3 Research Library Publications

Examining ChatGPT Performance on USMLE Sample Items and Implications for Assessment

Posted: | Victoria Yaneva, Peter Baldwin, Daniel P. Jurich, Kimberly Swygert, Brian E. Clauser

Academic Medicine: Volume 99 - Issue 2 - p 192-197

 

This report investigates the potential of artificial intelligence (AI) agents, exemplified by ChatGPT, to perform on the United States Medical Licensing Examination (USMLE), following reports of its successful performance on sample items. 

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

Using Eye-Tracking Data as Part of the Validity Argument for Multiple-Choice Questions

Posted: | Victoria Yaneva, Brian E. Clauser, Amy Morales, Miguel Paniagua

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.

Category:Assessment-Oriented Research, Applications of Technology

The Choice of Response Probability in Bookmark Standard Setting: An Experimental Study

Posted: | P. Baldwin, M.J. Margolis, B.E. Clauser, J. Mee, M. Winward

Educational Measurement: Issues and Practice, 39: 37-44

 

This article presents the results of an experiment in which content experts were randomly assigned to one of two response probability conditions: .67 and .80. If the standard-setting judgments collected with the bookmark procedure are internally consistent, both conditions should produce highly similar cut scores.

Category:Assessment-Oriented Research, General Measurement