Abstract
New capabilities in TinkerPlots 2.0 supported the conceptual development of fifth- and sixth-grade students as they pursued several weeks of instruction that emphasized data modeling. The instruction highlighted links between data analysis, chance, and modeling in the context of describing and explaining the distributions of measures that result from repeatedly measuring multiple objects (i.e., the height of the school’s flagpole, a teacher’s head circumference, the arm-span of a peer). We describe the variety of data representations, statistics, and models that students invented and how these inscriptions were grounded both in their personal experience as measurers and in the affordances of TinkerPlots, which assisted them in quantifying what they could readily display with the computer tool. By inventing statistics, students explored the relation between qualities of distribution and methods for expressing these qualities as a quantity. Attention to different aspects of distribution resulted in the invention of different statistics. Variable invention invited attention to the qualities of “good” measures (statistics), thus meshing conceptual and procedural knowledge. Students used chance simulations, built into TinkerPlots, to generate models that explained variability in a sample of measurements as a composition of true value and chance error. Error was, in turn, decomposed into a variety of sources and associated magnitudes—a form of analysis of variance for children. The dynamic notations of TinkerPlots altered the conceptual landscape of modeling, placing simulation and world on more equal footing, as first suggested by Kaput (Journal of Mathematical Behavior, 17(2), 265–281, 1998).
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Support for this work was provided by the National Science Foundation, REC 0337675. The views expressed do not necessarily represent those of the Foundation.
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Lehrer, R., Kim, Mj. & Schauble, L. Supporting the Development of Conceptions of Statistics by Engaging Students in Measuring and Modeling Variability. Int J Comput Math Learning 12, 195–216 (2007). https://doi.org/10.1007/s10758-007-9122-2
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DOI: https://doi.org/10.1007/s10758-007-9122-2