The recommendations in this brief create a framework for using data effectively to make instructional decisions. The availability of student-level data for educators has pushed forward the movement to strengthen the role of data to guide instruction and improve student learning. While improvements in technology and assessments, as well as recent…

Building on the research of National Board Certification and its effect on teacher quality, student achievement, and professional development, this dissertation seeks to explore the factors that influence teachers when it is time to renew their National Board Certification. Using a qualitative methodology, this study seeks to describe the process…

K-12 education resources are often allocated non-strategically, with schools spending time and money on activities that have little relationship to student outcomes. Most of these decisions take place within districts, rooted in the processes of setting schedules, staffing levels, and assignments, and creating final budgets. Local Education…

This study investigated the positive impact of a teaching practice on student learning outcomes in an online MBA program. An instructional project guideline was developed to help online students enhance their achieving required learning objectives corresponding to five categories of Bloom's Taxonomy. The course learning objectives are based on…

Launched in 2008, the Strategic Data Project, housed at the Center for Education Policy Research at Harvard University, seeks to bridge the divide between educational research and practice in order to transform the use of data in education to improve student achievement. Through the project, the authors build robust research partnerships with…

Communities face powerful challenges--a high-school dropout epidemic, youth unemployment, teen pregnancy--that require powerful solutions. In a climate of increasingly constrained resources, those solutions must help communities to achieve more with less. A new kind of community collaborative--an approach that aspires to significant,…

Data-driven decision making (DDDM), applied to student achievement testing data, is a central focus of many school and district reform efforts, in part because of federal and state test-based accountability policies. This paper uses RAND research to show how schools and districts are analyzing achievement test results and other types of data to…