At an elementary school in the northeastern region of the United States elementary teachers struggled with using data to make instructional decisions. The purpose of this qualitative study was to explore elementary teachers' perceptions about how their teaching experiences prepared them to use data to make lesson decisions. The…

Effective instruction derives from collecting and analyzing student data. Data collection can be a series of observations, or progress monitoring assessments, where students are assessed regularly on a targeted skill to see if a program or instructional model is effective, or any other type of collected information that reveals knowledge to…

A multiple case study was designed to examine the components of data literacy used by formal and informal leaders to support the work of Data Teams. Nine formal leaders and ten informal leaders constituted the participants. One overarching central question and seven subquestions guided the research. The answer to the central question, How do…

The purpose of this investigation is to study and pursue a user-defined approach in preserving data privacy while maintaining an acceptable level of data utility using machine learning classification techniques as a gauge in the generation of synthetic data sets. This dissertation will deal with data privacy, data utility, machine learning…

This study examined the effect of various district and site level conditions that influence the frequency of teacher data-driven decision-making behaviors. This study is motivated by four research questions: 1) Among various kinds of data available to teachers and principals in making data-driven decisions: a. What is the relative level of…

This study explored the interplay of a community college's vision, its leaders' behaviors, strategic planning, and the use of data that contributed to an organizational culture that led to the improvement of student success. The researcher used a grounded theory approach to delve into the relationships and connections between these four…

The national focus in education continues to center on school accountability and student results. Districts and states are continually searching for ways to improve student performance and learning outcomes. There are several Data Driven Decision Making models currently being used in school districts across the country. Research continues to…

Previous research indicates that pre- and in-service teachers are not receiving adequate training to implement data-informed instructional decision making. This is problematic given the promise this decision making process holds for improving instruction and student learning. At the same time, many educators do not see the value of different types…

The objectives of this research are to demonstrate how text was used in (1) developing a theory to examine collaborative interaction in virtual worlds, (2) creating a framework for improving the efficiency and effectiveness of dealing with large text datasets for social network analysis, and (3) approaching an understanding of the role of meaning…

Signed into Law on January 8, 2002, the 1,180 page No Child Left Behind Act (NCLB) shifted the course of public education in America. For the first time accountability was firmly placed at the center of school operations by requiring a systematic approach to achieving reform and improving all areas of school life (Wanker & Christie, 2005). As…

All programs of healthcare education face increasing change and daunting challenges to prepare new graduates for the real world of practice as care providers in complex systems. The necessity for change in nursing education is at a critical level, called on from a variety of sources. New nurses must be able to enter practice as competent, safe,…

Academic integrity (AI) and academic dishonesty (AD) have been intensified areas of concern in higher education. This research study explored issues of students' AD at the University of New Mexico (UNM). With the rise in academic dishonesty, this study was conducted with the intention of determining how AD can be deterred or discouraged. Students…

This dissertation is developed around two studies created with the goal of describing and quantifying current educators' knowledge and perceptions of reading assessment and subsequent data-based instructional decision making. Unique to the field, a critical component of this study is an emphasis on educators' development of "data…

This study identified the variables associated with data-driven instruction (DDI) that are perceived to best predict student achievement. Of the DDI variables discussed in the literature, 51 of them had a sufficient enough research base to warrant statistical analysis. Of them, 26 were statistically significant. Multiple regression and an…

Increasing demands for accountability from both the public and the government have resulted in increasing pressure for higher education professionals to use data to support their choices. There is significant speculation that professionals at all levels of education lack the knowledge to implement data-driven decision making. However, empirical…