Understanding Distributions by Modeling Them |
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Authors: | Cliff Konold Anthony Harradine and Sibel Kazak |
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Institution: | (1) University of Massachusetts Amherst, Amherst, MA 01003, USA;(2) Prince Alfred College, Adelaide, Australia |
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Abstract: | In current curriculum materials for middle school students in the US, data and chance are considered as separate topics. They
are then ideally brought together in the minds of high school or university students when they learn about statistical inference.
In recent studies we have been attempting to build connections between data and chance in the middle school by using a modeling
approach made possible by new software capabilities that will be part of TinkerPlots 2.0 (TinkerPlots is published by Key Curriculum Press and has been developed with grants from the National Science Foundation (ESI-9818946, REC-0337675, ESI-0454754). Opinions
expressed here are our own and not necessarily those of the Foundation.). Using a new Sampler object, students build “factories”
to model not only prototypical chance events, but also distributions of measurement errors and of heights of people. We provide
the rationale for having students model a wide range of phenomena using a single software tool and describe how we are using
this capability to help young students develop a robust, statistical perspective. |
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Keywords: | Probability Modeling Computer simulations Statistical reasoning Distributions Data analysis Co-variation |
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