| The growing body of research on data-driven decision making (DDDM) details the implementation and positive results at the district and elementary school levels (Armstrong & Anthes, 2001; Datnow, Park, & Wohlstetter, 2007; Supovitz & Klein, 2003; Togneri & Anderson, 2003). However, theoretically grounded studies of DDDM and the impact of data use in high schools in particular remains limited. This study focused on how urban high school teachers conceptualized data use and how their local contexts shaped their implementation of DDDM.;Using case study research design and drawing on interview, observations, document reviews and teacher survey, I examined how high school teachers in two urban schools perceive and use data for school improvement. To guide instrument design and data analysis, I developed a theoretical framework building on organizational theories and frame analysis, concentrating on how people construct and enact policy messages.;This dissertation presents two major findings on how urban high school teachers make sense of DDDM. First, teachers' sensemaking of DDDM was filtered by how they conceptualized data, their motivations for data use, and the outcomes they expected for using data. From these patterns, a typology of teachers' orientation on DDDM was developed. There were distinctions amongst teachers who view DDDM through an inquiry-centered, solution-centered, bureaucratic-centered, or compliance-centered orientation.;Second, teachers' sensemaking of DDDM was mediated by the accountability, district, and departmental contexts. Policy implementation is ultimately a distributive process where multiple types of contexts play different roles in determining how teachers make sense of data and ultimately, how they use data. The accountability system prioritized the use of data while framing at the district level shaped teachers' construction of DDDM. Departmental structures and norms on sharing data along with the degree of joint work determined the extent to which teachers used data to inform instructional practices. Finally, even when these contextual factors align to promote a robust version of DDDM practices, ignoring teacher learning and professional development will likely lead to a surface level use of data for instructional decision making. |
