Although the generalized deterministic inputs, noisy "and" gate model (G-DINA; de la Torre, 2011) is a general cognitive diagnosis model (CDM), it does not account for the heterogeneity that is rooted from the existing latent groups in the population of examinees. To address this, this study proposes the mixture G-DINA model, a CDM that…

Recently, Bayesian diagnostic classification modeling has been becoming popular in health psychology, education, and sociology. Typically information criteria are used for model selection when researchers want to choose the best model among alternative models. In Bayesian estimation, posterior predictive checking is a flexible Bayesian model…

Diagnostic tests are typically administered in a multiple-choice (MC) format due to their advantages of objectivity and time efficiency. The MC-deterministic input, noisy "and" gate (DINA) family of models, a representative class of cognitive diagnostic models for MC items, efficiently and parsimoniously estimates the mastery profiles of…

Background: Cognitive load theory is widely used in educational research and instructional design, which relies heavily on conceptual constructs and measurement instruments of cognitive load. Due to its implicit nature, cognitive load is usually measured by other related instruments, such as commonly-used self-report scales of mental effort or…

Cognitive diagnosis models (CDMs) are the assessment tools that provide valuable formative feedback about skill mastery at both the individual and population level. Recent work has explored the performance of CDMs with small sample sizes but has focused solely on the estimates of individual profiles. The current research focuses on obtaining…

Without the ability to analyze their own learning (metacognition), students can find it difficult to manage their educational journey. The good news is, future learning environments on online platforms offer innovative ways to develop these skills, even for those who are digital natives. This study aims to ascertain the effectiveness of online…

One of the central components of cognitive diagnostic assessment is the Q-matrix, which is an essential loading indicator matrix and is typically constructed by subject matter experts. Nonetheless, to a large extent, the construction of Q-matrix remains a subjective process and might lead to misspecifications. Many researchers have recognized the…

Purpose: The contributions from the central auditory and cognitive systems play a major role in communication. Understanding the relationship between auditory and cognitive abilities has implications for auditory rehabilitation for clinical patients. The purpose of this systematic review is to address the question, "In adults, what is the…

Free-listing is a quick, semi-quantitative methodology commonly used by anthropologists to uncover information within a cultural domain. In this method note, we review how anthropologists have used free-listing in a variety of research settings. We then apply the social-ecological framework to describe how free-listing can be used for formative,…

Background: Dementia is a cognitive decline that leads to the progressive deterioration of an individual's ability to perform daily activities independently. As a result, a considerable amount of time and resources are spent on caretaking. Early detection of dementia can significantly reduce the effort and resources needed for caretaking. Aims:…

Background: Individuals with dementia have communication limitations resulting from cognitive impairments that define the syndrome. Whereas there are numerous cognitive assessments for individuals with dementia, there are far fewer communication assessments. The Profiling Communication Ability in Dementia (P-CAD) was developed to address this gap.…

This study aims to assess the overall impact of vocabulary development interventions on cognitive vocabulary outcomes. To achieve this, 43 theses on vocabulary teaching, each involving a specific intervention, were analyzed using meta-analysis. The findings from the meta-analysis, based on the random effects model, indicated that the average…

Diagnostic classification models (DCMs) are psychometric models that yield probabilistic classifications of respondents according to a set of discrete latent variables. The current study examines the recently introduced one-parameter log-linear cognitive diagnosis model (1-PLCDM), which has increased interpretability compared with general DCMs due…

Diagnostic classification models (DCMs) have grown in popularity as stakeholders increasingly desire actionable information related to students' skill competencies. Longitudinal DCMs offer a psychometric framework for providing estimates of students' proficiency status transitions over time. For both cross-sectional and longitudinal DCMs, it is…

Accurate measurement of wisdom is the cornerstone of wisdom research. To provide a representative reference for the reliability level and moderating factors of various wisdom self-rating scales, we carried out a reliability generalization meta-analysis of Chinese and English references retrieved from 2004 to 2023. A total of 149 articles were…