Abstract
This chapter argues for the need to restructure children’s statistical experiences from the beginning years of formal schooling, with a particular focus on data modelling. An increasingly important component of young children’s mathematical development, data modelling draws upon their abilities to impose structure on complex data, detect relationships between seemingly diverse concepts and representations, and organise, structure, visualise, and represent data. The chapter begins with an overview of some core components of data modelling, namely, structuring and representing data, informal inference (specifically, making predictions), and conceptual and metarepresentational competence. A selection of findings from a longitudinal study of data modelling across grades one to three is then addressed. Four main issues arising from the study include the role of task context, children’s posing of investigative questions, their application of conceptual and metarepresentational competence, and the role of model sharing in learning and the transfer of learning.
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Acknowledgements
This project was supported by a three-year Australian Research Council (ARC) Discovery Grant DP0984178 (2009–2011). Any opinions, findings, and conclusions or recommendations expressed in this paper are those of the author and do not necessarily reflect the views of the ARC. I wish to acknowledge the excellent support provided by the senior research assistant, Jo Macri.
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English, L.D. (2013). Reconceptualizing Statistical Learning in the Early Years. In: English, L., Mulligan, J. (eds) Reconceptualizing Early Mathematics Learning. Advances in Mathematics Education. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-6440-8_5
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