Structures and Supports for Data Use in Schools: A Qualitative Case Study of One Urban Elementary School
Date of Award
Doctor of Philosophy
Barbara Daley, Thomas Joynt, Patricia Greco, Latish Reed
Assessments, Data-Driven Instructional-System, Distributed Leadership, Efficacy, Professional Learning Community, Structures and Strategies
A federal policy in the United States has required sweeping changes in K-12 education. With No Child Left Behind legislation, schools are challenged to create conditions that bring each student to federally-set academic proficiency levels. Many schools have become more attentive to data about student performance and how it can inform their teaching decisions to meet federal goals under No Child Left Behind. How one urban elementary school in the Midwestern United States used data for decision-making in 2010-2011 was the focus of this research. The purpose of this study was to gain understanding about how personnel in one academically successful urban elementary school use data to guide instructional decisions. Findings show that beyond structures and supports provided by the district for data informed decision-making at the school level, teacher efficacy and guided inquiry into data use were powerful factors contributing to student learning and academic success.
This research was a qualitative case study guided by naturalistic inquiry. Qualitative, interview data were coded through content analysis and meaning was made from participant interviews and document analysis.
In this study, data were defined as results stemming from formative and summative assessments within the learning context. These questions were answered: What are the structures and strategies used for data-driven decision-making, and what are the roles of the school principal, the teachers and other stakeholders in the decision-making framework?
Key findings emerged. First, there are differences in data-driven decision making models at the federal policymaking level and school level. Still, both federal policy and district policy provided limited value to practitioners at the local level. This underscores the need for localized innovative practices and for local representation in larger policy decisions. Another finding is the role of instructional leadership in facilitating data-driven decision making in the classroom. Instructional leadership that is grounded in relationships of trust and caring impacts teacher growth. Transformational change is most responsive to strategies that engage teachers as co-authors of reform including professional learning communities, teacher efficacy, and community building around improvement efforts. In this way, institutionalized supports and genuine care work hand in hand to transform teaching and learning.
Groh, Anne Marie, "Structures and Supports for Data Use in Schools: A Qualitative Case Study of One Urban Elementary School" (2013). Theses and Dissertations. 109.
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