RESEARCH LIBRARY

Patient Education and Counseling: Volume 109, Supplement, April 2023, Page 2

Physicians' responses to patient communication were assessed by both clinically matched and unmatched analogue patients (APs). Significant correlations between their ratings indicated consistency in evaluating physician communication skills. Thematic analysis identified twenty-one common themes in both clinically matched and unmatched AP responses, suggesting similar assessments of important behaviors. These findings imply that clinically unmatched APs can effectively substitute for clinically matched ones in evaluating physician communication and offering feedback when the latter are unavailable.

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.