The detection of differential item functioning (DIF) is important in psychological and behavioral sciences. Standard DIF detection methods perform an item-by-item test iteratively, often assuming that all items except the one under investigation are DIF-free. This article proposes a Bayesian adaptive Lasso method to detect DIF in graded response…

The field of studies in metacognition points to some limitations in the way the construct has traditionally been measured and shows a near absence of performance-based tests. The Meta-Text is a performance-based test recently created to assess components of cognition regulation: planning, monitoring, and judgment. This study presents the first…

In recent years, some models for binary and graded format responses have been proposed to assess unipolar variables or "quasi-traits." These studies have mainly focused on clinical variables that have traditionally been treated as bipolar traits. In the present study, we have made a proposal for unipolar traits measured with continuous…

Diagnostic classification models (DCMs) have recently become very popular both for research purposes and for real testing endeavors for student assessment. A plethora of DCM models give researchers and practitioners a wide range of options for student diagnosis and classification. One intriguing option that some DCM models offer is the possibility…

Survey score interpretations are often plagued by sources of construct-irrelevant variation, such as response styles. In this study, we propose the use of an IRTree Model to account for response styles by making use of self-report items and anchoring vignettes. Specifically, we investigate how the IRTree approach with anchoring vignettes compares…

This convergent, parallel, mixed-methods study with qualitative and quantitative content analysis methods was conducted to identify what type of thinking is required by the College and Career Readiness Assessment (CCRA+) by (a) determining the frequency and percentage of questions categorized as higher-level thinking within each cell of Hess'…

Psychometricians at an organization named the Education and Training Evaluation Commission (ETEC) developed a new test scoring method called the latent D-scoring method (DSM-L) where it is believed that the new method itself is much easier and more efficient to use compared to the Item Response Theory (IRT) method. However, there are no studies…

Automated scoring of student responses to open-ended questions, including short-answer questions, has great potential to scale to a large number of responses. Recent approaches for automated scoring rely on supervised learning, i.e., training classifiers or fine-tuning language models on a small number of responses with human-provided score…

The C-test is a type of gap-filling test designed to efficiently measure second language proficiency. The typical C-test consists of several short paragraphs with the second half of every second word deleted. The words with deleted parts are considered as items nested within the corresponding paragraph. Given this testlet structure, it is commonly…

To address response style or bias in rating scales, forced-choice items are often used to request that respondents rank their attitudes or preferences among a limited set of options. The rating scales used by raters to render judgments on ratees' performance also contribute to rater bias or errors; consequently, forced-choice items have recently…

This study focuses on developing and validating a questionnaire to assess the integration of ICT by EFL teachers in higher education settings in Vietnam. Twenty EFL teachers from three language institutes participated in semi-structured interviews, generating 20 questionnaire items. Qualitative content analysis of the interview data provided…

Purpose: ParAlg (Paraphasia Algorithms) is a software that automatically categorizes a person with aphasia's naming error (paraphasia) in relation to its intended target on a picture-naming test. These classifications (based on lexicality as well as semantic, phonological, and morphological similarity to the target) are important for…

The present paper introduces a general multidimensional model to measure individual differences in learning within a single administration of a test. Learning is assumed to result from practicing the operations involved in solving the items. The model accounts for the possibility that the ability to learn may manifest differently for correct and…

Differential item functioning (DIF) analysis refers to procedures that evaluate whether an item's characteristic differs for different groups of persons after controlling for overall differences in performance. DIF is routinely evaluated as a screening step to ensure items behavior the same across groups. Currently, the majority DIF studies focus…

There has been increasing interest in applying integrative data analysis (IDA) to analyze data across multiple studies to increase sample size and statistical power. Measures of a construct are frequently not consistent across studies. This article provides a tutorial on the complex decisions that occur when conducting harmonization of measures…