Showing 1 - 5 of 5 Research Library Publications
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. 

Posted: | Peter Baldwin

Educational Measurement: Issues and Practice

 

This article aims to answer the question: when the assumption that examinees may apply themselves fully yet still respond incorrectly is violated, what are the consequences of using the modified model proposed by Lewis and his colleagues? 

Posted: | B. E. Clauser, M. Kane, J. C. Clauser

Journal of Educational Measurement: Volume 57, Issue 2, Pages 216-229

 

This article presents two generalizability-theory–based analyses of the proportion of the item variance that contributes to error in the cut score. For one approach, variance components are estimated on the probability (or proportion-correct) scale of the Angoff judgments, and for the other, the judgments are transferred to the theta scale of an item response theory model before estimating the variance components.

Posted: | B.C. Leventhal, I. Grabovsky

Educational Measurement: Issues and Practice, 39: 30-36

 

This article proposes the conscious weight method and subconscious weight method to bring more objectivity to the standard setting process. To do this, these methods quantify the relative harm of the negative consequences of false positive and false negative misclassification.

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.