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.
Medical Teacher: Volume 40 - Issue 11 - p 1143-1150
This study explores a novel milestone-based workplace assessment system that was implemented in 15 pediatrics residency programs. The system provided: web-based multisource feedback and structured clinical observation instruments that could be completed on any computer or mobile device; and monthly feedback reports that included competency-level scores and recommendations for improvement.
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.
Academic Medicine: April 2018 - Volume 93 - Issue 4 - p 636-641
Increasing criticism of maintenance of certification (MOC) examinations has prompted certifying boards to explore alternative assessment formats. The purpose of this study was to examine the effect of allowing test takers to access reference material while completing their MOC Part III standardized examination.
Measurement: Interdisciplinary Research and Perspectives, 16:1, 59-70
This article critically reviews how diagnostic models have been conceptualized and how they compare to other approaches used in educational measurement. In particular, certain assumptions that have been taken for granted and used as defining characteristics of diagnostic models are reviewed and it is questioned whether these assumptions are the reason why these models have not had the success in operational analyses and large-scale applications, contrary to what many have hoped.
Educational Measurement: Issues and Practice, 37: 40-45
This simulation study demonstrates that the strength of item dependencies and the location of an examination systems’ cut‐points both influence the accuracy (i.e., the sensitivity and specificity) of examinee classifications. Practical implications of these results are discussed in terms of false positive and false negative classifications of test takers.
Qual Life Res 27, 1711–1720 (2018)
The US Food and Drug Administration (FDA), as part of its regulatory mission, is charged with determining whether a clinical outcome assessment (COA) is “fit for purpose” when used in clinical trials to support drug approval and product labeling. This paper provides a review (and some commentary) on the current state of affairs in COA development/evaluation/use with a focus on one aspect: How do you know you are measuring the right thing? In the psychometric literature, this concept is referred to broadly as validity and has itself evolved over many years of research and application.