In today's era of large-scale data, academic institutions, businesses, and government agencies are increasingly faced with heterogeneous datasets. Consequently, there is a growing need to develop effective methods for extracting meaningful insights from this type of data. Quantile, expectile, and expected shortfall regression methods offer useful…

The research is a descriptive correlational study that investigates new methods for the creation of innovation for institutions. The research addresses the need for organizations to generate a novel form of innovation for their competitiveness and survival. These novel methods in the generation of innovation include using an organization's big…

This dissertation address two significant challenges in the causal inference workflow for Big Observational Data. The first is designing Big Observational Data with high-dimensional and heterogeneous covariates. The second is performing uncertainty quantification for estimates of causal estimands that are obtained from the application of black box…

This paper seeks to empirically validate a sector agonistic instrument that measures the perceived critical success factors in data governance. Twelve constructs (Leadership and Management Commitment; Leadership and Management Alignment; Executive Sponsorship; Robust Data Governance Strategy; Change Management; Training and Education; Governance…

Performance-based funding policies for postsecondary institutions have been enacted throughout the United States as an answer to reductions in public funding and increased accountability mandates. Institutional effectiveness, as demonstrated through metrics such as graduation and retention rates, dictates the level of funding received. Educational…

The purpose of this quantitative study was to provide school district leaders and policymakers information of the impact grade configuration had on academic performance using math and ELA ILEARN scores over a three-year period. The study included data from 585 schools that were classified into four groups: Elementary Setting, Intermediate Setting,…

Data permeates our digital world. As data and data visualizations become more ubiquitous in our everyday lives, individuals are required to use it as a resource for meaning making, and we as literacy researchers need to understand the ways that our literacy practices are changing because of data collection, storage, analysis, and transmission.…

Data is everywhere, but not always accessible to everyone. Conventional data visualization tools and guidelines often assume a standard user, neglecting the neurodivergent needs of individuals with cognitive disabilities. These disabilities can create significant obstacles in data-driven reasoning, including difficulties in processing complex…

My dissertation studies the relationship between counseling and violence within U.S. schools. Much of the research on school security and school safety tends to lean heavily on routine activities theory and other opportunity theories, which limits the study of other factors critically relevant to this topic such as school climate. This…

Moving Beyond the Ordinal Methodological Controversy: A Systematic Review (Manuscript 1): Ordinal outcome data is a common byproduct of education research. Yet more than seventy-five years after the development of Stevens' original measurement framework, the permissibility of select analytic techniques to ordinal outcome data remains a topic of…

Having access to accurate and reliable data is essential in decision-making. A wealth of data is spread across the University of Delaware (UD). These data include, but are not limited to, financial information, budget information, student enrollment, credit hours taught, and numerous metrics about faculty, staff, and sponsored programs. These data…

This dissertation develops and applies sophisticated Item Response Theory (IRT) methods to address fundamental measurement challenges in cognitive testing, focusing on the Armed Services Vocational Aptitude Battery (ASVAB) data from the National Longitudinal Survey of Youth (NLSY). The first chapter implements a confirmatory multidimensional IRT…

Data are an essential factor in the fourth industrial revolution, demanding engineers and scientists to leverage and analyze their potential for significantly improving the efficiency of industrial processes and their control systems. In classical industrial process control systems, the models are constructed using linear data-driven approaches,…

This study focuses on undergraduates' preparation for college level courses. In recent international PISA results United States students fall behind seventeen countries on the computer-based reading proficiency test. They have scored low for over a decade, in spite of spending more than one hundred-thousand dollars per student on education. This…

Schools are frequently seen as the hubs of the community, providing resources and a gathering place for members of the community. The process of surveying the community in order to identify unique needs within the community, and then intentionally forging partnerships capable of ameliorating the specific needs, are strategies used by community…