Cognitive diagnostic models (CDMs) provide pedagogically relevant information in the form of a student profile of multiple binary categorizations of students into mastery or nonmastery statuses on latent traits called attributes. Federal educational accountability requires accountability measures to designate students into one of at least three…

Cognitive and academic assessment are fundamental to learning disability diagnosis in children and adults. This study sought to evaluate the relationships between cognitive abilities and reading skills in a sample of referred postsecondary students. It was hypothesized that the relationship between cognitive ability and reading skills may change…

As the research on feigning has grown, the number and quality of performance validity tests (PVTs) has increased as well. However, while several PVTs have been developed from assessments commonly used as part of neuropsychological batteries, there has been less exploration for PVTs scored from items in cognitive screeners. The Montreal Cognitive…

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…

The collegiate aviation programs of higher education are seeking to adapt their capabilities and expertise toward educating a generation of airmen who will operate Remotely Piloted Aircraft (RPA). The collection of studies presented in this dissertation address this interest as higher education programs investigate the value of modalities and…

The multiple-choice (MC) item format has been widely used in educational assessments across diverse content domains. MC items purportedly allow for collecting richer diagnostic information. The effectiveness and economy of administering MC items may have further contributed to their popularity not just in educational assessment. The MC item format…

Standard assessments of cognitive ability have been the preferred method of assessing the probability of student achievement at community colleges, but there is a growing trend in the use of noncognitive factors to assess student potential. Factors related to a student's race/ethnicity and family income have been shown to be correlated with…

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…

In order to achieve broadening participation in computer science and other careers related to computing, middle school classrooms should provide students opportunities (tasks) to think like a computer scientist. Researchers in computing education promote the idea that programming skill should not be a pre-requisite for students to display…

Transactive memory systems (TMSs) describe the structures and processes that teams use to share information, work together, and accomplish shared goals. First introduced over three decades ago, TMSs have been measured in a variety of ways. This dissertation proposes the use of network analysis in measuring TMS. This is accomplished by describing…

Cognitive diagnostic models can uncover students' mastery of multiple fine-grained skill attributes or problem-solving processes. A number of studies have applied cognitive diagnostic models to detect students' knowledge mastery in mathematics and language testing. However, few studies focus on cognitive diagnostic assessment in K-12 science…

To maintain America's status as a global technological leader, there has been a longstanding effort to increase the quality and quantity of engineers in the workforce. Previous research and government reports have called on the education system at all levels to increase enrollment and persistence in college engineering programs. Additionally,…

This dissertation aims to investigate the effect size measures of differential item functioning (DIF) detection in the context of cognitive diagnostic models (CDMs). A variety of DIF detection techniques have been developed in the context of CDMs. However, most of the DIF detection procedures focus on the null hypothesis significance test. Few…

A primary purpose of cognitive diagnosis models (CDMs) is to classify examinees based on their attribute patterns. The Q-matrix (Tatsuoka, 1985), a common component of all CDMs, specifies the relationship between the set of required dichotomous attributes and the test items. Since a Q-matrix is often developed by content-knowledge experts and can…

Employee engagement and retention are two areas of focus within industry that help organizations assess business metrics such as training effectiveness, hiring practices, and workplace culture. Several methods exist with which to research engagement and retention levels within an organization and research to date has primarily focused on employee…