Background/purpose: This study aimed to reveal the accuracy of estimation of multiple-choice test items parameters following the models of the item-response theory in measurement. Materials/methods: The researchers depended on the measurement accuracy indicators, which express the absolute difference between the estimated and actual values of the…

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…

Testing programs have explored the use of technology-enhanced items alongside traditional item types (e.g., multiple-choice and constructed-response items) as measurement evidence of latent constructs modeled with item response theory (IRT). In this report, we discuss considerations in applying IRT models to a particular type of adaptive testlet…

The distinguishing feature of dynamic assessment (DA) is the dialectical integration of assessment and instruction. However, how to design the targeted instruction or mediation has been relatively underexplored. To address this gap, this study proposes the attribute-based mediation model (AMM), an English-as-a-foreign-language listening mediation…

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…

Categorical data become increasingly ubiquitous in the modern big data era. In this dissertation, we propose novel statistical learning and inference methods for large-scale categorical data, focusing on latent variable models and their applications to psychometrics. In psychometric assessments, the subjects' underlying aptitude often cannot be…

Large scale international assessments depend on invariance of measurement across countries. An important consideration when observing cross-national differential item functioning (DIF) is whether the DIF actually reflects a source of bias, or might instead be a methodological artifact reflecting item response theory (IRT) model misspecification.…

This work presents a study that used distributed language representations of test items to model test item difficulty. Distributed language representations are low-dimensional numeric representations of written language inspired and generated by artificial neural network architecture. The research begins with a discussion of the importance of item…

Purpose: Well-designed assessment methodologies and various cognitive diagnosis models (CDMs) to extract diagnostic information about examinees' individual strengths and weaknesses have been developed. Due to this novelty, as well as educational specialists' lack of familiarity with CDMs, their applications are not widespread. This article aims at…

The trans-contextual model (TCM) offers a heuristic-based theoretical framework to understand fifth-grade Danish schoolchildren's motivation to participate in the 11 for Health in Denmark educational football concept, as well as their intention and behaviour to participate in vigorous physical activity (PA) in a leisure-time context. The…

Multidimensional item response theory (MIRT) models have generated increasing interest in the psychometrics literature. Efficient approaches for estimating MIRT models with dichotomous responses have been developed, but constructing an equally efficient and robust algorithm for polytomous models has received limited attention. To address this gap,…

Analyses that reveal how treatment effects vary allow researchers, practitioners, and policymakers to better understand the efficacy of educational interventions. In practice, however, standard statistical methods for addressing Heterogeneous Treatment Effects (HTE) fail to address the HTE that may exist within outcome measures. In this study, we…

Measurement errors attributable to cultural issues are complex and challenging for educational assessments. We need assessment tests sensitive to the cultural heterogeneity of populations, and psychometric methods appropriate to address fairness and equity concerns. Built on the research of culturally responsive assessment, this dissertation…

Testing organizations are faced with increasing demand to provide subscores in addition to the total test score. However, psychometricians argue that most subscores do not have added value to be worth reporting. To have added value, subscores need to meet a number of criteria: they should be reliable, distinctive, and distinct from each other and…

Assessing job applicants' general mental ability online poses psychometric challenges due to the necessity of having brief but accurate tests. Recent research (Myszkowski & Storme, 2018) suggests that recovering distractor information through Nested Logit Models (NLM; Suh & Bolt, 2010) increases the reliability of ability estimates in…