RESEARCH LIBRARY
RESEARCH LIBRARY
View the latest publications from members of the NBME research team
Applied Psychological Measurement: Volume 46, issue 2, page(s) 571-588
This study evaluates the degree to which position effects on two separate low-stakes tests administered to two different samples were moderated by different item (item length, number of response options, mental taxation, and graphic) and examinee (effort, change in effort, and gender) variables. Items exhibited significant negative linear position effects on both tests, with the magnitude of the position effects varying from item to item.
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.
Medical Teacher: Volume 40 - Issue 8 - p 838-841
Adaptive learning requires frequent and valid assessments for learners to track progress against their goals. This study determined if multiple-choice questions (MCQs) “crowdsourced” from medical learners could meet the standards of many large-scale testing programs.
Quality Assurance in Education, Vol. 26 No. 2, pp. 150-152
An introduction to a special issue of Quality Assurance in Education featuring papers based on presentations at a two-day international seminar on managing the quality of data collection in large-scale assessments.
Psychometrika 83, 847–857 (2018)
Utilizing algorithms to generate items in educational and psychological testing is an active area of research for obvious reasons: Test items are predominantly written by humans, in most cases by content experts who represent a limited and potentially costly resource. Using algorithms instead has the appeal to provide an unlimited resource for this crucial part of assessment development.