Correct specifications of hierarchical attribute structures in analyses using diagnostic classification models (DCMs) are pivotal because misspecifications can lead to biased parameter estimations and inaccurate classification profiles. This research is aimed to demonstrate DCM analyses with various hierarchical attribute structures via Bayesian…

A psychological framework for different types of items commonly used with mixed-format exams is proposed. A choice model based on signal detection theory (SDT) is used for multiple-choice (MC) items, whereas an item response theory (IRT) model is used for open-ended (OE) items. The SDT and IRT models are shown to share a common conceptualization…

Algebraic Thinking Skills (ATS) are one of the skills that students need to master in order to solve nonroutine problems. These skills are also necessary as a foundation for students preparing to enter university studies and fields of work that require logical and analytical thinking. However, Malaysian students' performance in solving algebraic…

In this article, we extend Liao's test for across-group comparisons of the fixed effects from the generalized linear model to the fixed and random effects of the generalized linear mixed model (GLMM). Using as our basis the Wald statistic, we developed an asymptotic test statistic for across-group comparisons of these effects. The test can be…

Cognitive diagnosis models (CDMs) are restricted latent class models that can be used to analyze response data from educational or psychological tests. The Deterministic Input Noisy Output "AND" gate (DINA) model and the Deterministic Input Noisy Output "OR" gate (DINO) model there are two popular cognitive diagnosis models…

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.…

Understanding whether or not different types of students master various attributes can aid future learning remediation. In this study, two-level diagnostic classification models (DCMs) were developed to represent the probabilistic relationship between external latent classes and attribute mastery patterns. Furthermore, variational Bayesian (VB)…

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,…

Cognitive diagnostic models can uncover students' mastery of multiple fine-grained skill attributes or problem-solving processes. A number of studies have applied cognitive diagnostic models to detect students' knowledge mastery in mathematics and language testing. However, few studies focus on cognitive diagnostic assessment in K-12 science…

Solving a constructed-response item usually requires successfully performing a sequence of tasks. Each task could involve different attributes, and those required attributes may be "condensed" in various ways to produce the responses. The sequential generalized deterministic input noisy "and" gate model is a general cognitive…

Large-scale assessments are generally designed for summative purposes to compare achievement among participating countries. However, these nondiagnostic assessments have also been adapted in the context of cognitive diagnostic assessment for diagnostic purposes. Following the large amount of investments in these assessments, it would be…

Modelling ability is one of the essential elements of the latest educational reforms, and Trends in International Mathematics and Science Study (TIMSS) is a curriculum-based assessment which allows educational systems worldwide to inspect the curricular influences. The aims of this study were to examine the role of modelling ability in the…

Automated scoring of free drawings or images as responses has yet to be used in large-scale assessments of student achievement. In this study, we propose artificial neural networks to classify these types of graphical responses from a TIMSS 2019 item. We are comparing classification accuracy of convolutional and feed-forward approaches. Our…

This paper presents a mixture item response tree (IRTree) model for extreme response style. Unlike traditional applications of single IRTree models, a mixture approach provides a way of representing the mixture of respondents following different underlying response processes (between individuals), as well as the uncertainty present at the…

This dissertation aims to investigate the effect size measures of differential item functioning (DIF) detection in the context of cognitive diagnostic models (CDMs). A variety of DIF detection techniques have been developed in the context of CDMs. However, most of the DIF detection procedures focus on the null hypothesis significance test. Few…