The nonparametric classification (NPC) method has been proven to be a suitable procedure for cognitive diagnostic assessments at a classroom level. However, its nonparametric nature impedes the obtention of a model likelihood, hindering the exploration of crucial psychometric aspects, such as model fit or reliability. Reporting the reliability and…

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…

Despite substantial evidence for the link between an individual's intelligence and successful life outcomes, questions about what defines intelligence have remained the focus of heated dispute. The most common approach to understanding intelligence has been to investigate what performance on tests of intellect is and is not associated with. This…

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…

Our primary objective was to examine the impact of acquiescent responding on empathy measures. We selected the Affective and Cognitive Measure of Empathy (ACME) as the measure for this case study due to its composition--the affective dissonance scale consists solely of items that are semantically reversed relative to the empathy construct, while…

Latent class models with covariates are widely used for psychological, social, and educational research. Yet the fundamental identifiability issue of these models has not been fully addressed. Among the previous research on the identifiability of latent class models with covariates, Huang and Bandeen-Roche (Psychometrika 69:5-32, 2004) studied the…

Computational thinking (CT) is a set of cognitive skills that every child should acquire. K-12 classrooms are expected to provide students opportunities (tasks) to think computationally. We introduce a CT competency assessment for middle school students. The assessment design process started by establishing a cognitive model of CT domain mastery,…

For 40 years there has been a call for improvement in assessing the academic potential of children and young people (CYP) with visual impairment. Anecdotal evidence regarding the use of psychometric assessments with CYP with visual impairment suggests that some professional practice has involved the use of assessments normed on a sighted…

One of the primary goals of higher education is to enhance students' critical thinking skills as they work to complete their program of study. As such, it is for critical educators and academic program coordinators to have access to assessment tools that can provide accurate estimates of the cognitive and dispositional domains of higher-order…

To provide personalized support on educational platforms, it is crucial to model the evolution of students' knowledge states. Knowledge tracing is one of the most popular technologies for this purpose, and deep learning-based methods have achieved state-of-the-art performance. Compared to classical models, such as Bayesian knowledge tracing, which…

Feedback is a powerful instructional tool for motivating learning. But effective feedback, requires that instructors have accurate information about their students' current knowledge status and their learning progress. In modern educational measurement, two major theoretical perspectives on student ability and proficiency can be distinguished.…

Cognitive diagnosis models (CDMs) have gained increasing popularity recently because of their potential to provide diagnostic inferences that can inform learning and teaching. However, the development of cognitive diagnostic assessments (CDAs) is lagging behind the development of the associated psychometric models. At present, it is not clear…

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…

Although much research has been conducted on the psychometric properties of cognitive diagnostic models, they are only recently being used in operational settings to provide results to examinees and other stakeholders. Using this newer class of models in practice comes with a fresh challenge for diagnostic assessment developers: effectively…