In low-stakes assessment settings, students' performance is not only influenced by students' ability level but also their test-taking engagement. In computerized adaptive tests (CATs), disengaged responses (e.g., rapid guesses) that fail to reflect students' true ability levels may lead to the selection of less informative items and thereby…

The use of computerized adaptive testing algorithms for ranking items (e.g., college preferences, career choices) involves two major challenges: unacceptably high computation times (selecting from a large item pool with many dimensions) and biased results (enhanced preferences or intensified examinee responses because of repeated statements across…

Many scholars compared various item discrimination indices in real or simulated data. Item discrimination indices, such as item-total correlation, item-rest correlation, and IRT item discrimination parameter, provide information about individual differences among all participants. However, there are tests that aim to select a very limited number…

As technology use continues to rapidly increase, so too does consumer use of web-based resources. While important, accessibility is often overemphasized by users when consuming and evaluating web resources. This prioritization may have particularly negative consequences for the selection of supports or interventions in educational settings. This…

For item selection in cognitive diagnostic computerized adaptive testing (CD-CAT), ideally, a single item selection index should be created to simultaneously regulate precision, exposure status, and attribute balancing. For this purpose, in this study, we first proposed an attribute-balanced item selection criterion, namely, the standardized…

General education programs often offer students a choice among various courses to fulfill a specific requirement. However, the extent to which these courses equally enable students to achieve the intended learning outcomes can vary, potentially giving some students an unintended advantage. This article evaluates whether students are inadvertently…

Medical school selection is currently in the paradoxical situation in which selection tools may predict study outcomes, but which constructs are actually doing the predicting is unknown (the 'black box of selection'). Therefore, our research focused on those constructs, answering the question: do the internal structures of the tests in an…

More than three decades after their introduction, diagnostic classification models (DCM) do not seem to have been implemented in educational systems for the purposes they were devised. Most DCM research is either methodological for model development and refinement or retrofitting to existing nondiagnostic tests and, in the latter case, basically…

Diagnostic classification models (DCMs) can provide multidimensional diagnostic feedback about students' mastery levels of knowledge components or attributes. One advantage of using DCMs is the ability to accurately and reliably classify students into mastery levels with a relatively small number of items per attribute. Combining DCMs with…

The number of teacher candidates is increasing as a result of the excessive quotas given to departments that train teacher candidates and the right to teach different branches with pedagogical formation certificates. Therefore it becomes compulsory to hold selection exams in teacher appointments. The exams carried out during this selection process…

This study linked ninth-grade student background data and school-reported high school transcript data from the national High School Longitudinal Study of 2009 (HSLS:09) to student item responses on the 2013 National Assessment of Educational Progress (NAEP) mathematics assessment to examine the relationships between high school coursework and…

The development of cognitive diagnostic-computerized adaptive testing (CD-CAT) has provided a new perspective for gaining information about examinees' mastery on a set of cognitive attributes. This study proposes a new item selection method within the framework of dual-objective CD-CAT that simultaneously addresses examinees' attribute mastery…

Item exposure control is, relative to adaptive testing, a nascent concept that has emerged only in the last two to three decades on an academic basis as a practical issue in high-stakes computerized adaptive tests. This study aims to implement a new strategy in item exposure control by incorporating the standard error of the ability estimate into…

In this commentary, University of North Carolina's associate dean of research and assessment at the School of Education Terry Ackerman poses questions and shares his thoughts on David Thissen's essay, "Bad Questions: An Essay Involving Item Response Theory" (this issue). Ackerman begins by considering the two purposes of Item Response…

Purpose: This study aims to reveal effects of content balancing and item selection method on ability estimation in computerized adaptive tests by comparing Fisher's maximum information (FMI) and likelihood weighted information (LWI) methods. Research Methods: Four groups of examinees (250, 500, 750, 1000) and a bank of 500 items with 10 different…