The flood at the foot of the classroom door: secondary mathematics and English teachers describe data-driven decision making

PROBLEM: Data-driven decision making has been a focus of school reform efforts for decades. As new testing and teacher evaluation regimes take hold, the focus on data analysis in schools only sharpens. Policy makers assume that teachers and school leaders have capacity for and common conceptions of that work, but the profession still wrestles over basic definitions. Researchers have connected outcomes to specific data analysis projects, described effective data analysis tools and structures, and uncovered normative cases, but have not yet described teacher practice with data (Coburn & Turner, 2012). Teachers are frontline implementers of policy, so their conceptions and practice are of utmost importance. Guided by the following research questions, this study explores how teachers engage with data. How do high school math and English teachers describe their use of data to inform instructional decision making? What obstacles influence their decision making as they plan for and engage in data analysis? METHOD: This comparative case study collected data from 18 teachers and 4 administrators working in 3 New Jersey high schools that vary in size and socioeconomics. Interviews provided the basis for data collection, followed up by reviews of professional literature from publishers that participants discussed. Transcribed interviews were coded and analyzed according to a conceptual framework and questions that guided the inquiry. FINDINGS: Teachers describe practices along a continuum of formality—the degree of codification and standardization of data. As formality increases, teacher control over data and teacher perceptions of usefulness of data decrease. Teachers value informal data the most, and rely on their experience and status as trained specialists to lend validity and reliability to those data, even if they believe that administrators and policy makers may believe the data to be invalid and/or unreliable. Teachers describe time and tools as structural obstacles to data analysis, and appreciate the efforts of administrators who try to mitigate those barriers. Teachers also describe students as obstacles; student motivation and other qualities affect the validity and reliability of data. Professional literature offers some suggestions on how to overcome many obstacles, but does not often address the notion of students as obstacles. Where the professional literature does, it describes teacher bias as the most likely cause. SIGNIFICANCE: Though policy mandates data-driven decision making in schools, there is little understanding of teacher practice and conceptions. This study answers research agendas calling for more inquiry in this direction, but recognizes that basic definitions are not yet resolved. The findings have informed the development of a typology of data in schools, which future researchers may use to further explore teacher practice and conceptions.Ed. D.Includes bibliographical referencesby Jeffrey P. Moor