Showing 1 - 2 of 2 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

Trusting Your Test Results: Building and Revising Multiple-Choice Examinations

Posted: | D. Franzen, M. Cuddy, J. S. Ilgen

Journal of Graduate Medical Education: June 2018, Vol. 10, No. 3, pp. 337-338

 

To create examinations with scores that accurately support their intended interpretation and use in a particular setting, examination writers must clearly define what the test is intended to measure (the construct). Writers must also pay careful attention to how content is sampled, how questions are constructed, and how questions perform in their unique testing contexts.1–3 This Rip Out provides guidance for test developers to ensure that scores from MCQ examinations fit their intended purpose.

Category:Assessment-Oriented Research, General Measurement