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…

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…

The authors aimed to incorporate learning into the cognitive assessment framework that exists for static assessment data. In order to accomplish this, they derive a common likelihood function for dynamic models and introduce Parameter Driven Process for Change + Cognitive Diagnosis Model (PDPC + CDM), a dynamic model which tracks learning…

Directors of educational projects need to be aware of the consequences their decisions may have for evaluation and appreciate the need for working closely with their evaluators from the earliest planning stage. Attempting to address the needs of project directors and evaluators, this guidebook deals with one central aspect of project…

Piaget's model of children's conceptual learning and development was compared with Klausmeier's Conceptual Learning and Development (CLD) model in a longitudinal study. The CLD model suggests four successive levels of concept learning: (1) concrete--recognizing an object which has been encountered previously; (2) identity--recognizing a known…

The paper discusses an experiment in which regression analysis was used to examine predictors of information retention following a college economics course. It was hypothesized that students taught in small classes with self-instructional materials would place a higher value on basic economic concepts and retain these concepts longer than students…

Abstracts are presented of the major conference papers and thematic discussions delivered at the 1978 Measurement and Methodology Conference. The titles of the presentations are: Policy-Responsive Evaluation (Wiley); When Educators Set Standards (Glass); Comments on Wiley and Glass (Schutz); Key Standard-Setting Considerations for Minimal…