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Improving instructional practices, policies, and student outcomes for early childhood language and literacy through data-driven decision making

Description:
Since the passage of No Child Left Behind, data-driven decision making has become one of the central foci in schools in their attempt to attain and maintain adequate levels of student academic performance. The importance of early childhood education is well established with language and literacy proficiency in the early years being viewed as a leading indicator in children's educational development. It provides schools with the initial signs of progress towards academic achievement. In this article, a conceptual framework for improving instructional practice and student outcomes in early childhood language and literacy through data-driven decision making was described. Four questions served as the structure around which the conceptual framework was built. These questions include (1) Why do data need to be collected? (2) What kinds of data need to be collected? (3) How are the data collected? (4) How are the data used for making decisions? Responses to these questions serve as tenets for guiding the decision making process. (author abstract)
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