Composite scores are an exceptionally important psychometric tool for behavioral science research applications. A prototypical example occurs with self-report data, where researchers routinely use questionnaires with multiple items that tap into different features of a target construct. Item-level missing data are endemic to composite score…

This book explores the transformative role of artificial intelligence in educational assessment, catering to researchers, educators, administrators, policymakers, and technologists involved in shaping the future of education. It delves into the foundations of AI-assisted assessment, innovative question types and formats, data analysis techniques,…

In this article we present a general approach not relying on item response theory models (non-IRT) to detect differential item functioning (DIF) in dichotomous items with presence of guessing. The proposed nonlinear regression (NLR) procedure for DIF detection is an extension of method based on logistic regression. As a non-IRT approach, NLR can…

The chapters in this online volume comprise the TIMSS & PIRLS International Study Center's technical report of the methods and procedures used to develop, implement, and report the results of TIMSS 2019. There were various technical challenges because TIMSS 2019 was the initial phase of the transition to eTIMSS, with approximately half the…

In multiple-choice items, differential item functioning (DIF) in the correct response may or may not be caused by differentially functioning distractors. Identifying distractors as causes of DIF can provide valuable information for potential item revision or the design of new test items. In this paper, we examine a two-step approach based on…

This study explored the impact of partial credit scoring of one type of innovative items (multiple-response items) in a computerized adaptive version of a large-scale licensure pretest and operational test settings. The impacts of partial credit scoring on the estimation of the ability parameters and classification decisions in operational test…

When using IRT models in Educational Achievement Testing, the model is as a rule too simple to catch all the relevant dimensions in the test. It is argued that a simple model may nevertheless be useful but that it can be complemented with additional analyses. Such an analysis, called profile analysis, is proposed and applied to the reading data of…

This article refutes a recent claim that computer-based tests produce biased scores for very proficient test takers who make mistakes on one or two initial items and that the "bias" can be reduced by using a four-parameter IRT model. Because the same effect occurs with pattern scores on nonadaptive tests, the effect results from IRT scoring, not…

Research in automated creation of test items for assessment purposes became increasingly important during the recent years. Due to automatic question creation it is possible to support personalized and self-directed learning activities by preparing appropriate and individualized test items quite easily with relatively little effort or even fully…

The 2012 National Survey of Science and Mathematics Education was designed to provide up-to-date information and to identify trends in the areas of teacher background and experience, curriculum and instruction, and the availability and use of instructional resources. This compendium, one of a series, details the results of a survey of high school…

This study tracked gender differential item functioning (DIF) on the English subtest of the Korean College Scholastic Aptitude Test (KCSAT) over a nine-year period across three data points, using both the Mantel-Haenszel (MH) and item response theory likelihood ratio (IRT-LR) procedures. Further, the study identified two factors (i.e. reading…

Nested logit item response models for multiple-choice data are presented. Relative to previous models, the new models are suggested to provide a better approximation to multiple-choice items where the application of a solution strategy precedes consideration of response options. In practice, the models also accommodate collapsibility across all…

Psycholinguistic data are often analyzed with repeated-measures analyses of variance (ANOVA), but this paper argues that mixed-effects (multilevel) models provide a better alternative method. First, models are discussed in which the two random factors of participants and items are crossed, and not nested. Traditional ANOVAs are compared against…

Lord (1980) proposed formulas that provide direct relationships between IRT discrimination and difficulty parameters and conventional item statistics. The purpose of the present study was to determine the robustness of the formulas beyond the initial and restrictive conditions identified by Lord. Simulation and real achievement data were employed.…

In operational testing programs using item response theory (IRT), item parameter invariance is threatened when an item appears in a different location on the live test than it did when it was field tested. This study utilizes data from a large state's assessments to model change in Rasch item difficulty (RID) as a function of item position change,…