What Are You Driving At?: How School Leaders Use Data When Making School-level Decisions About Instructional Improvement

Abstract

Increasingly, educational policies include mandates for school leaders to use data to "drive" their school-level decisions about instructional improvement. Extant research suggests that school leaders are trying to use data in their school-level instructional improvement decisions--decisions that impact instruction across multiple classrooms--but provides little guidance about the types of data school leaders use and how they use them when making such decisions. This dissertation begins to address these gaps through a qualitative, embedded case study of two middle schools implementing data-driven decision making at the school-level. Drawing on concepts from the theory of organizational decision making under conditions of uncertainty and ambiguity, the study relies heavily on observational methods to examine the full breadth of data school leaders use, how they use them, and how data usage relates to the outcomes of the decisions. Findings reveal that the leaders in the two study schools used a broad array of data, including student test scores, data on their schools' resources, data on the implementation of current programs and school operations, and data on potential strategies, programs, or interventions. Because these data were rarely available, the school leaders spent significant amounts of time gathering additional data and they, at times, used their personal knowledge in place of data. Further, this study demonstrates that leaders used these data throughout the decision making process, and that how leaders used these data was related to the outcomes of the decisions.