Cutting Through the “Data Driven” Mantra: Different Conceptions of Data-driven Decision Making
by Gina Schuyler Ikemoto & Julie Marsh — 2007
High-stakes accountability policies such as the federal No Child Left Behind (NCLB) legislation require districts and schools to use data to measure progress toward standards and hold them accountable for improving student achievement. One assumption underlying these policies is that data use will enhance decisions about how to allocate resources and improve teaching and learning. Yet these calls for data-driven decision making (DDDM) often imply that data use is a relatively straightforward process. As such, they fail to acknowledge the different ways in which practitioners use and make sense of data to inform decisions and actions.
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