This handbook provides an overview of major developments around diagnostic classification models (DCMs) with regard to modeling, estimation, model checking, scoring, and applications. It brings together not only the current state of the art, but also the theoretical background and models developed for diagnostic classification.
This informative graphic reports between‐individual information where a vertical line—with dashed lines on either side indicating an error band—spans three graphics allowing a student to easily see their score relative to four defined performance categories and, more notably, three relevant score distributions.
This article briefly reviews the aspects of validity that researchers should consider when using surveys. It then focuses on factor analysis, a statistical method that can be used to collect an important type of validity evidence.
The United States Medical Licensing Examination Step 2 Clinical Skills (CS) exam uses physician raters to evaluate patient notes written by examinees. In this Invited Commentary, the authors describe the ways in which the Step 2 CS exam could benefit from adopting a computer-assisted scoring approach that combines physician raters’ judgments with computer-generated scores based on natural language processing (NLP).
This paper provides results on a form of adaptive testing that is used frequently in intelligence testing. In these tests, items are presented in order of increasing difficulty. The presentation of items is adaptive in the sense that a session is discontinued once a test taker produces a certain number of incorrect responses in sequence, with subsequent (not observed) responses commonly scored as wrong.
Smoothing techniques are designed to improve the accuracy of equating functions. The main purpose of this study is to compare seven model selection strategies for choosing the smoothing parameter (C) for polynomial loglinear presmoothing and one procedure for model selection in cubic spline postsmoothing for mixed‐format pseudo tests under the random groups design.
This study investigates the impact of incorporating observer-reported workload into workplace-based assessment (WBA) scores on (1) psychometric characteristics of WBA scores and (2) measuring changes in performance over time using workload-unadjusted versus workload-adjusted scores.
In their 2018 article, (T&B) discuss how to deal with not reached items due to low working speed in ability tests (Tijmstra and Bolsinova, 2018). An important contribution of the paper is focusing on the question of how to define the targeted ability measure. This note aims to add further aspects to this discussion and to propose alternative approaches.
Research suggests that the three-option format is optimal for multiple choice questions (MCQs). This conclusion is supported by numerous studies showing that most distractors (i.e., incorrect answers) are selected by so few examinees that they are essentially nonfunctional. However, nearly all studies have defined a distractor as nonfunctional if it is selected by fewer than 5% of examinees.
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.