The purpose of this qualitative case study was to describe one Connecticut middle school's voluntary implementation of a data-driven decision making process in order to improve student academic performance. Data-driven decision making is a component of Connecticut's accountability system to assist schools in meeting the requirements of the No Child Left Behind Act (2001). The school was chosen due to preliminary progress and its participation in data-driven decision making. After the study was conducted, state standardized achievement tests indicated that, indeed, the middle school raised student academic performance and met Adequate Yearly Progress in all areas. In-depth interviews were conducted with the school's principal and teachers to collect their perceptions of how the principal implemented data-driven decision making. Principal and teacher responses were reported and areas of agreement and differences among reports were identified. The Balanced Leadership Framework (Waters, Marzano, & McNulty, 2004) was used to guide the investigation and organize findings. Eleven of the 21 Balanced Leadership responsibilities were chosen because they each correlated to the type of changes that would result from the implementation of data-driven decision making. Data analysis revealed that the principal of Knight Middle School employed practices to implement data-driven decision making consistent with those recommended in previous research, as well as newly identified practices that were specific to this school. The study's most strongly supported conclusion indicated that the principal promoted collaboration among and professional development for teachers and support staff to focus attention on assessment data and improving instruction. Conclusions based on less frequently occurring reports indicated: (1) the principal strategically utilized a wide variety of frequently scheduled meetings to support the vision of best practices, collaboration, and professional development; (2) the principal relied on her personal accessibility and support to assist teachers with improving student academic achievement; and (3) rather than stipulating the steps of data-driven decision making within the participating school, the principal encouraged a discovery process in connection with the data-driven decision making process. The final conclusion was based on unique principal responses that described how the principal required multiple behaviors of faculty, and utilized specific methods to obtain teacher input to drive data-driven decision making. Recommendations for practice and future research are offered. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]