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,…

In the contemporary era, the landscape of innovation and entrepreneurship is dynamically evolving, fueled by a substantial surge in venture capital investments and the rapid expansion of the global startup ecosystem. This burgeoning growth not only highlights the vibrant nature of modern economies but also brings to the forefront the critical…

This quantitative study investigates the predictive power of machine learning (ML) models on degree completion among adult learners in higher education, emphasizing the enhancement of data-driven decision-making (DDDM). By analyzing three ML models - Random Forest, Gradient-Boosting machine (GBM), and CART Decision Tree - within a not-for-profit,…

What is the link between neuroscience and education? Can one measure the phenomenon of learning and make predictions by charting student performance? How does the knowledge of neuroscience inform educators to objectively and effectively meet the unique needs of all learners and address discrepancies in subsets of student population? Questions like…

Small Bible colleges have limited resources to recruit students. They must find strategies to recruit and retain college-ready students who fit with their mission. With limited or no endowments or reserves, these colleges rely primarily on enrollment tuition revenue. The purpose of this study, conducted at a small Bible college in the southeastern…

Accountability has pushed principals to use data to drive and inform decisions in schools to positively impact student achievement. Research has shown that principals are the second most important impact on student achievement, second only to teachers. Principals who can lead change in schools based on data driven response have a positive impact…

College and university enrollment has decreased nationwide every year for more than a decade as educational consumers increasingly question the value of higher education and discover alternatives to the traditional university system. Enrollment professionals seeking growth are tasked to develop and implement innovative solutions to address…

This dissertation's two primary purposes were to construct an alternative socioeconomic status model and estimate how it predicts student success in higher education. This research filled a gap in knowledge about the widely acknowledged disparities in higher education based on socioeconomic status. Prior research has often relied on parental…

This study highlights the role and importance of advanced, machine learning-driven predictive models in enhancing the accuracy and timeliness of identifying students at-risk of negative academic outcomes in data-driven Early Warning Systems (EWS). K-12 school districts have, at best, 13 years to prepare students for adulthood and success. They…

Regional comprehensive universities offer accessible and diverse undergraduate educational programs, while grappling with funding cuts and affordability. The study's first research question underscores the enduring importance of factors such as student characteristics, pre-college characteristics, and financial situations. The findings highlight…

New forms of visualizations are transforming how people interact with data. This dissertation explored how undergraduates learn with infographics. The following questions guided this research: (i) What do we know about the factors influencing the processing of data visualizations? (ii) How do task-level and learner-level characteristics impact the…

Before nursing graduates can practice as a registered nurse, they must successfully pass the National Council Licensure Examination for Registered Nurses (NCLEX-RN). Low first-time pass rates on this high-stakes test can cause concern for multiple stakeholders including graduate nurses, nursing programs, health care organizations, and society. The…

There has been substantial scholarly attention given to teachers' functioning over the past two decades. Much of this attention has been precipitated by accounts of increasing teacher burnout and attrition from the profession. Central to this scholarly focus has been the construct of teacher self-efficacy, which has been shown to be a predictor of…

This dissertation comprises three chapters. The first two address issues within the education system, focusing on strategies to attract and retain high-quality teachers in the public sector. The third chapter, a collaborative effort with Martin Martinez and Miguel Saldarriaga, explores the application of machine learning tools for nowcasting…

The persistent difficulty of retaining college students through graduation has become a global problem. The purpose of this quantitative, descriptive, and retrospective study was to apply data mining methods, tools, and algorithms to analyze enrollment data for issues affecting STEM students' retention at an historically black college (HBCU). The…