The purpose of this quantitative study was to provide school district leaders and policymakers information of the impact grade configuration had on academic performance using math and ELA ILEARN scores over a three-year period. The study included data from 585 schools that were classified into four groups: Elementary Setting, Intermediate Setting,…

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…

Public school teachers are at the forefront of education in the United States; they must employ methods such as data-driven decision making (DDDM) to ensure that all students are learning. Quality decision making is vital in this age of accountability under the No Child Left Behind Act (NCLB) that includes mandated state testing such as the…

School districts are charged with the task of improving standardized test scores and closing the gaps between specific groups of students. Numerous programs, school improvement strategies, changes in instruction and leadership have been implemented to close the gap. Data are becoming more abundant at the state, district, and school levels. Many…

The purpose of this study was to determine how teacher perceptions of data and use of data-driven instruction affect student performance in English language arts (ELA). This study investigated teachers' perceptions of using data in the classroom and what supports they need to do so. The goal of the research was to increase the level of knowledge…