Computational learning theory studies the design and analysis of learning algorithms, and it is integral to the foundation of machine learning. In the modern era, classical computational learning theory is growingly unable to catch up with new practical demands. In particular, problems arise in the following aspects: i). "scalability":…

Multivariate Functional Principal Component Analysis (MFPCA) is a valuable tool for exploring relationships and identifying shared patterns of variation in multivariate functional data. However, interpreting these functional principal components (PCs) can sometimes be challenging due to issues such as roughness and sparsity. In this dissertation,…

This dissertation explores bridge n-sections of knotted surfaces in 4-manifolds by defining invariants that measure the complexity of their topology and by giving geometric constructions that determine Lagrangian surfaces in 4-manifolds under certain conditions. First, we present an elegant geometric construction that generates all triple grid…

This dissertation used synthetic datasets, semi-synthetic datasets, and a real-world dataset from an educational intervention to compare the performance of 15 machine learning and multiple imputation methods to estimate the individual treatment effect (ITE). In addition, it examined the performance of five evaluation metrics that can be used to…

Multidimensional Item Response Theory (MIRT) has been widely used in educational and psychological assessments. It estimates multiple constructs simultaneously and models the correlations among latent constructs. While it provides more accurate results, the unidimensional IRT model is still dominant in real applications. One major reason is that…

This dissertation studies the advancement of consensus-aware technologies in the context of collective decision-making, focusing on the integration of these technologies into information systems to effectively represent, detect, and characterize consensus among people and other agents. Despite the proven value of collective intelligence in…

This dissertation examines the response of a group of educators to a state mandate to integrate computational thinking (CT) into all levels of the curriculum. It explores the historical development of CT and its significance within the broader context of Science, Technology, Engineering, and Mathematics education, emphasizing the rapid growth and…

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…

Electronic textiles (e-textiles) weave computational and electronic components into fabric, enabling students to design and build fabric-based projects that interact with their surroundings. This meshing of physical hardware and virtual software can be difficult for students to untangle when debugging. Is an LED failing to light up because of an…

Knowledge-producing practices in sciences and engineering increasingly use computational means for modeling and working with data. Despite consensus regarding the importance of computational thinking in science and engineering, scholars differ in conceptualization of the primary purposes and role of its integration in K-12 science (Kafai &…

The study investigated best practices to increase students' skills in math fluency and computation and reduce math anxiety. The studies used in this Systematic Literature Review were analyzed using the TAPUPAS framework to ensure the studies chosen were quality and were relevant to the research questions. The results of these analyzed studies…

This purpose of this quasi-experimental, ex-post facto study was to examine the effect of SpringMath as a classwide intervention for students in grades kindergarten through second grade within one elementary school. In order to research the effects of SpringMath on the whole-number computational fluency of kindergarten through second grade…

This dissertation follows a manuscript-style format, beginning with an introduction and literature review, followed by three distinct studies and a concluding section. All three studies use "Lucky Codes," an educational board game designed to foster computational thinking skills in elementary students, as the intervention. The first…

Computational thinking (CT) has been supported as an important skill every young person should possess for the 21st century, with possible implications for problem-solving, self-expression, and creativity. Numerous initiatives, both within and outside classroom settings, have been developed in response to policy mandates aiming at broadening…