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Cummings, Kelli D.; Stoolmiller, Michael L.; Baker, Scott K.; Fien, Hank; Kame'enui, Edward J. – Reading and Writing: An Interdisciplinary Journal, 2015
We present a method for data-based decision making at the school level using student achievement data. We demonstrate the potential of a national assessment database [i.e., the University of Oregon DIBELS Data System (DDS)] to provide comparative levels of school-level data on average student achievement gains. Through the DDS as a data source,…
Descriptors: Academic Achievement, Formative Evaluation, Achievement Gains, Bayesian Statistics