School districts have recognized the undeniable power of using data to enhance performance. As a result, teachers are now required to use data to prepare for critical state assessments and to improve district levels. These assessments are crucial in determining the school's rating by the state and can even result in a state takeover if scores are…

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…

Data-based decision-making has been a frequently used policy and practice intervention used in schools to help inform the decision-making processes of educational practitioners, with the aim of improving student outcomes. Interim benchmark assessments are designed by commercial test developers to support educators in this framework. In fact, the…

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.…

Teacher turnover continues to be a significant problem in the United States. Teacher turnover is expensive because it costs money to continue recruiting, hiring, and training new teachers to replace those leaving (Carver-Thomas & Darling-Hammond, 2017). Most important though, teacher turnover hurts student achievement and success (Sorensen…

Decision-making, a key factor of organizational performance, is based on information retrieved from processing raw data. As businesses and consumers are shifting toward digital channels, more and more data is being generated through digital services and electronic devices. Big Data is argued to have significant benefits to businesses, and yet data…

This qualitative case study sought to discover how school-level data teams can intentionally use effective data practices to identify and implement high-leverage interventions that support all students, including Black and Latinx boys, in attaining the necessary academic requirements for high school graduation. The researcher analyzed data from…

The shortage of qualified administrators who can utilize data analytics means that institutions are not able to harness data analytics to its fullest potential in order to remain competitive in a higher education market that continued to reward institutions that embrace entrepreneurship. Examining how new student affairs professionals in US higher…

Leveraging big data for student data analytics is increasingly integrated throughout university operations from admissions to advising to teaching and learning. Though the possibilities are exciting to consider, they are not without risks to student autonomy, privacy, equity, and educational value. There has been little research showing how…

Using data to inform decision-making in the educational environment has increased over the last decade due to accountability requirements at the federal, state, and local level (Bernhardt, 2013; Datnow & Hubbard, 2016; Garland, 2014; Mandinach & Gummer, 2016; McKay, 2018; Wayman, 2005). While research supported the inclusion of data in…

This study seeks to understand the big-data analytics readiness of four-year public and private higher education institutions (HEIs) in North Carolina. The higher education landscape has been experiencing unprecedented challenges including declines in enrollment, graduation rates, and student retention rates. Coupled with cuts in funding at the…

This action research study examined how faculty development workshops affected how testing grade level teachers disaggregate standardized data. It also examined how teachers used the information to improve communication and classroom instruction. The rationale for the study was that teachers were asked to be data driven, but were not taught how to…

The exponential growth of digital libraries and the proliferation of scholarly content in electronic formats have made data mining and information retrieval essential tools for effectively managing, organizing, and disseminating knowledge. This thesis provides a comprehensive analysis of the advancements and challenges in these fields, with a…

To analyze educational outcomes or evaluate operations, academic institutions need to produce high-quality data. Unfortunately, many institutions do not have accurate, timely, and useful data and information despite investments to manage technology. Furthermore, data management issues in education, including access, quality, and ownership, inhibit…

This study has three primary objectives. First to provide insight into possibilities for moderation/mediation analysis in education research by discussing analytical methods based on the counterfactual and developed in other disciplines. Second is to highlight specific issues related to mediation and the estimation of effects when the outcome is…