The concept of computational thinking (CT) has become more prevalent across the engineering education research and teaching landscape. Yet much of the research to date has been more definitional and has not offered many ways to convert CT theory to practice. One prominent set of tools used across engineering disciplines is modeling and simulation,…

This dissertation compares the performance of equivalence test (EQT) and null hypothesis test (NHT) procedures for identifying invariant and noninvariant factor loadings under a range of experimental manipulations. EQT is the statistically appropriate approach when the research goal is to find evidence of group similarity rather than group…

There is growing consensus that data-informed decision-making through human-centered inquiry and design process results in improved outcomes for designed artifacts. Among the latest trends is a group of tools and processes loosely assimilated under the umbrella term, "design thinking." These "designerly ways of knowing" are…

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…

As the number of STEM opportunities and the need for a scientifically literate society increases, educators in STEM fields require tools that help support these needs. Chemistry is one STEM content area that would benefit from exploring educational technology that supports conceptual understanding. An action research study was conducted to…

This study examined whether athletic training students in a four-year undergraduate entry-level accredited athletic training program in a postsecondary institution perceived the PEARLS model as effective in providing feedback. Although students look to the feedback process to help them better understand their skill and performance level when…

Item Response Theory (IRT) models are a popular analytic method for self report data. We show how traditional IRT models can be vulnerable to specific kinds of asymmetric measurement error (AME) in self-report data, because the models spread the error to all estimates -- even those of items that do not contribute error. We quantify the impact of…

Bayesian network is a probabilistic graphical model that has wide applications in various domains due to its peculiarity of knowledge representation and reasoning under uncertainty. This research aims at Bayesian network structure learning and how the learned model can be used for reasoning. Learning the structure of Bayesian network from data is…

Although virtual reality (VR) is commonly used in science classes, for example, to enable students to do simulated human dissections and other medical procedures, research on the use of VR as a learning tool in the humanities, more specifically the literature classroom, are few. This grounded theory study sought to understand better the use of VR…

This research examined how a Digital Escape Room (DER) about accessibility contributed to the potential change of faculty behavioral intentions toward developing accessible online course content. This paper describes the design of the DER and a pilot study of its initial implementation that consisted of two phases, (1 a usability test with 3…

Preparing students for science, technology, engineering, and mathematics (STEM) education is one of the United States' K-12 educational concerns (Gandhi et al., 2016). Despite the National Science Foundation's (NSF) report that the number of students participating in STEM fields continues to increase, the number of underrepresented students…

The purpose of this qualitative descriptive case study was to explore how recent nursing graduates understand and describe their online clinical experience during the COVID-19 pandemic and examine perceptions of the impact on their preparedness for transitioning into professional practice. The problem addressed was the closure of clinical sites to…

As the engineering education system continuously evolves to meet the demands of modern industry and society, there is a need for a methodology that would manage and resolve the complexities inherent in engineering educational systems. Model-based Systems Engineering (MBSE) is a structured approach to system design that utilizes models across all…

This dissertation proposes novel Domain Adaptation (DA) methods in real-world industrial settings, where the availability of labeled data is limited and test data can significantly differ from training data. Particularly, our research addresses key challenges in DA, including the applicability of DA methods in industrial settings, strategies to…

In order to comprehend complex and abstract phenomena, students must partake in the process of learning by integrating complex and invisible components without ever physically encountering or manipulating such components. Prior knowledge and experiences will influence the way students assimilate and model new experiences and knowledge. If prior…