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…

This study explored the core competencies, technological skills, functional proficiencies, and professional experiences of data scientists at higher education institutions. The specific population of interest was higher education administrators and staff professionals identified as data scientists. This study was informed by the following guiding…

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…

Institutional researchers use skills from their diverse backgrounds to collect, analyze and report data about their institutions to stakeholders representing various interests and levels of data literacy. However, there is little research into how these professionals process data and none into what aspects are important to institutional…

The purpose of this quantitative causal-comparative study is an empirical examination of the differences in business intelligence capability and the value and competitive advantage of mid-level higher education academia professionals from community colleges, four-year public, and four-year private institutions within the United States.…

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…

All chemistry students must develop competency in analyzing and making sense of data. However, there are many difficulties that chemistry students may experience while analyzing data. Many students may not use relevant prior knowledge to aid in making sense of data, or they may not form conclusions using all the data provided. Additionally, prior…

There has been a great deal of news, discussion, and outcry regarding the lack of diversity in science, technology, engineering, and math (STEM) related fields, be it industry or academia. On many comparative lists regarding STEM students and workers, African American males are an unacceptably low percentage of the population. The problem is quite…

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…

Digital learning environments are becoming increasingly ubiquitous as a wide range of EdTech products and services enter classrooms and households across the globe. One salient attribute of these environments is their capacity to generate large amounts of data as students interact with the technology. These data logs can help construct a detailed…

Many departments seek to improve their equity, diversity, and inclusion using data-informed methods; however, not much is known about how closely department leadership aligns their review practices with appropriate theory. This dissertation seeks to explore four areas: 1) how are equity, diversity, and inclusion are being conceptualized (implied…

The purpose of this descriptive research study was to evaluate the web-based practice experience tracking system at a school of public health (SPH) at a large southeastern university. Applied practice experiences (APEs) are a key component of public health education, and schools and programs of public health in the United States must provide…

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.…

The emerging field of data science has brought attention to how we teach statistics and data science (Bargagliotti et al., 2020; Franklin et al., 2007) and prepare the next generation of statistics and data science teachers (Franklin et al., 2013). To realize the full potential of statistics and data science, researchers have also called for using…

This dissertation documented how undergraduate students made sense of data in news media. The participants were 30 undergraduate students enrolled in a course called "Numbers and Social Justice." The study used argument analysis (Toulmin, 2003) and ethnographic methodology to examine students' written work in a naturalistic setting.…