Many Library and Information Science (LIS) training programs are gradually expanding their curricula to include computational data science courses such as supervised and unsupervised machine learning. These programs focus on developing both "classic" information science competencies as well as core data science competencies among their…

Variability is underemphasized in domains such as engineering. Statistics and data science education research offers a variety of frameworks for understanding variability, but new frameworks for domain applications are necessary. This study investigated the professional practices of working engineers to develop such a framework. The Neglected,…

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…

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…