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…

Attribute hierarchy, the underlying prerequisite relationship among attributes, plays an important role in applying cognitive diagnosis models (CDM) for designing efficient cognitive diagnostic assessments. However, there are limited statistical tools to directly estimate attribute hierarchy from response data. In this study, we proposed a…

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…

To provide intelligent learning guidance for students in e-learning systems, it is necessary to accurately predict their performance in future exams by analyzing score data in past exams. However, existing research has not addressed the uncertain and dynamic features of students' cognitive status, whereas these features are essential for improving…

Cognitive diagnosis models (CDMs) are the statistical framework for cognitive diagnostic assessment in education and psychology. They generally assume that subjects' latent attributes are dichotomous--mastery or nonmastery, which seems quite deterministic. As an alternative to dichotomous attribute mastery, attention is drawn to the use of a…

In this study, we developed machine learning algorithms to automatically score students' written arguments and then applied the cognitive diagnostic modeling (CDM) approach to examine students' cognitive patterns of scientific argumentation. We abstracted three types of skills (i.e., attributes) critical for successful argumentation practice:…

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 global shortage of skilled programmers remains a persistent challenge. High dropout rates in introductory programming courses pose a significant obstacle to graduation. Previous studies highlighted learning difficulties in programming students, but their specific weaknesses remained unclear. This gap exists due to the predominant focus on the…

Forty-five children aged four-and-a-half to five-and-a-half years old were given number conservation tasks in three conditions: (1) a count condition in which children were helped to count each set after the transformation; (2) a match condition in which children were helped to connect by a string each animal with its peanut; and (3) the standard…

Presents a computational framework for modeling cognitive development that provides a language paradigm with which to compare and contrast different facets of children's knowledge. Describes the generative connectionist algorithm "cascade-correlation," the successful use of the algorithm to model cognitive development in various…

Analyzes differences in students' performance on algorithmic, lower-order cognitive skills (LOCS), and conceptual exam questions and the correlations between their achievements on these categories across different populations.Reports that the highest scores were obtained for the algorithmic questions, the lowest for the conceptual questions, and…

This report summarizes the results of research designed to study the psychometric and technological feasibility of adaptive testing to assess spatial ability. Data was collected from high school students on two types of spatial items: three-dimensional cubes and hidden figure items. The analysis of the three-dimensional cubes focused on the fit of…