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,…

Once research questions are posed, researchers must answer many a priori questions regarding research design before analysis can be performed and any conclusions can be made, including sample selection criteria, data collection method, model specification, analysis and estimation technique. The choices made by researchers along this forking path…

Speech is a complex, redundant and variable signal happening in a noisy and ever changing world. How do listeners navigate these complex auditory scenes and continuously and effortlessly understand most of the speakers around them? Studies show that listeners can quickly adapt to new situations, accents and even to distorted speech. Although prior…

To make sense of our interconnected and algorithm driven world, students increasingly need proficiency with computational thinking (CT), systems thinking (ST), and computational modeling. One aspect of computational modeling that can support students with CT, ST, and modeling is testing and debugging. Testing and debugging enables students to…

Student growth percentiles (SGPs) have become a common means to measure and report on student academic growth for state education accountability, and some states have adopted SGP cutscores as a means of classifying student growth into categories like "high/medium/low" growth. It has therefore become important to understand properties of…

In many psychological and educational applications, it is imperative to obtain valid and reliable score estimates of multilevel processes. For example, in order to assess the quality and characteristics of high impact learning processes, one must compute accurate scores representative of student- and classroom-level constructs. Currently, there…

Most mathematicians state mathematics is a field of beauty, creativity, and innovation, yet what is echoed by students is not how mathematics allows students to explore, but rather the ways in which it constrains and does not necessitate creativity. In comparison, many students associate coding with freedom, and the ability to create and express…

Response time data from educational and psychological assessments have become more widely available in recent years. Although much research has been done on response time models, there is large variability between assessments and the factors that may affect response times. On the person's side, familiarity with online environments may largely…

Previous research has been limited regarding the measurement of computational thinking, particularly as a learning progression in K-12. This study proposes to apply a multidimensional item response theory (IRT) model to a newly developed measure of computational thinking utilizing both selected response and open-ended polytomous items to establish…

The ability to efficiently optimize or re-optimize an algorithm for high performance on a particular processor architecture is crucial in a wide spectrum of engineering and scientific applications. To help bridge the gap between fully automated optimization, which does not reliably produce optimal code, and fully manual optimization, which is…

Observable data in empirical social and behavioral science studies are often categorical (i.e., binary, ordinal, or nominal). When categorical data are outcomes, they fail to maintain the scale and distributional properties of linear regression and factor analysis. Attempting to estimate model parameters for categorical outcome data with the…

There are many concerns from early childhood educators regarding allowing children to use technology, pointing to the adverse effects of screen time and barriers such as lack of resources. To support advocating CT in early childhood settings using technology, this dissertation proposes solutions and resources for early childhood educators by…

In Huggins-Manley & Han (2017), it was shown that WLSMV global model fit indices used in structural equating modeling practice are sensitive to person parameter estimate RMSE and item difficulty parameter estimate RMSE that results from local dependence in 2-PL IRT models, particularly when conditioning on number of test items and sample size.…

Educational data mining focuses on exploring increasingly large-scale data from educational settings, such as Learning Management Systems (LMS), and developing computational methods to understand students' behaviors and learning settings better. There has been a multitude of research dedicated to studying the student learning process, leading to…

As science becomes increasingly computationally intensive, the need for computational thinking (CT) and computer science (CS) practices in K-12 science education is becoming paramount. Incorporation of CT/CS practices in K-12 education can be seen in national standards and a variety of allied initiatives. One way to build capacity around an…