As a prominent aspect of modeling learners in the education domain, knowledge tracing attempts to model learner's cognitive process, and it has been studied for nearly 30 years. Driven by the rapid advancements in deep learning techniques, deep neural networks have been recently adopted for knowledge tracing and have exhibited unique advantages…

This study aims to conduct differential item functioning analyses in the context of cognitive diagnosis assessments using various formulations of the Wald test. In implementing the Wald test, two scenarios are considered: one where the underlying reduced model can be assumed; and another where a saturated CDM is used. Illustration of the different…

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…

The current paper investigates the structural validity of the Children's Concentration and Empathy Scale (CCES), which was designed based on Montessori's developmental theory to assess, using teacher ratings, the coherence of attention-related characteristics (concentration, empathy, and normalization) in children from 1.5 to 12 years old. The…

Cognitive diagnosis models (CDMs) allow for the extraction of fine-grained, multidimensional diagnostic information from appropriately designed tests. In recent years, interest in such models has grown as formative assessment grows in popularity. Many dichotomous as well as several polytomous CDMs have been proposed in the last two decades, but…

We propose a general cognitive diagnosis model framework to diagnose mental disorders using item scores obtained from clinical measurement instruments. This framework can be used to validate the extent to which the items measure the specific disorders. The method is illustrated using data obtained with the Dutch version of Millon Clinical…

We review the GIDNA and CDM packages in R for fitting cognitive diagnosis/diagnostic classification models. We first provide a summary of their core capabilities and then use both simulated and real data to compare their functionalities in practice. We found that the most relevant routines in the two packages appear to be more similar than…

A family of learning models that integrates a cognitive diagnostic model and a higher-order, hidden Markov model in one framework is proposed. This new framework includes covariates to model skill transition in the learning environment. A Bayesian formulation is adopted to estimate parameters from a learning model. The developed methods are…

Educational transformation in the 21st century demands in-depth knowledge and understanding in order to promote the development of higher-order thinking skills (HOTS). However, the most commonly reported problem with respect to developing a knowledge of chemistry is poor mastery of basic concepts. Chemistry laboratory educational activities are…