Large-Scale Data, Big Possibilities: A Review of Large-Scale Studies in Mathematics Education

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Emily Miller West Chester University

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Martha Makowski University of Illinois at Urbana, Champaign

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Yasemin Copur-Gencturk University of Southern California

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Sarah Lubienski University of Illinois at Urbana, Champaign

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Large–Scale Studies in Mathematics Education, edited by James A. Middleton, Jinfa Cai, and Stephen Hwang, presents mathematics education research covering a broad range of topics using a variety of data sources and analysis techniques. By spotlighting this work, the editors hope to encourage the use of large–scale data sets, which they argue are underutilized by mathematics education researchers. Middleton, Cai, and Hwang contend that “large scale studies can be both illuminative—uncovering patterns not yet seen in the literature, and critical—changing how we think about teaching, learning, policy, and practice” (p. 12). With its inclusion of studies using large–scale data sets and expository papers concerning methodological considerations, the book effectively challenges the reader to consider issues of scale. The book has 18 chapters organized into four sections on curriculum, teaching, learning, and methodology. Although the volume is organized by these areas of interest, we suggest that prospective readers peruse chapters in all sections. As the book editors note, the boundaries between sections are far from clear–cut, and readers may find work relevant to their area of interest throughout the book.

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Journal for Research in Mathematics Education
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