Projects
Data-Driven Decisionmaking
Data-driven decisionmaking commonly supposes that if data are available, they can be used to improve student achievement and foster more effective practices. All too often data from high-stakes tests are treated as the bottom line, and a mythology exists that a straight accounting of the system's effectiveness follows directly from an analysis of those data. However, all data are not created equal. Whether assessments are summative, formative, or diagnostic and at which level of the system they are targeting all influence the application of the data set. To make use of data in the interests of students, practitioners need appropriate measures, interpretative experience, and pedagogical knowledge about using data to inform instruction. Bringing practitioners more fully into proficiency in data use holds the potential to make accountability more than a watchdog, but a genuine educational component. CCT staff who have played prominent roles in this domain include Daniel Light, and Naomi Hupert. Select a snapshot below to learn more about the kinds of work we do in this area.
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Re-Engineering Public Health/Epidemiological Models to Predict the Spread of Literacy and Illiteracy
2006 - 2008
Abstract:Explore the use of available data to examine from a "macro" perspective the role that multiple school- and community-level factors may play in supporting or impeding student literacy development. More»