Statistical modelling and repeatable structures: purpose, process and prediction

Abstract

Children have limited exposure to statistical concepts and processes, yet researchers have highlighted multiple benefits of experiences in which they design and/or engage informally with statistical modelling. A study was conducted with a classroom in which students developed and utilised data-based models to respond to the inquiry question, Which origami animal jumps the furthest? The students used hat plots and box plots in Tinkerplots to make sense of variability in comparing distributions of their data and to support them to write justified conclusions of their findings. The study relied on classroom video and student artefacts to analyse aspects of the students’ modelling experiences which exposed them to powerful statistical ideas, such as key repeatable structures and dispositions in statistics. Three principles—purpose, process and prediction—are highlighted as ways in which the problem context, statistical structures and inquiry dispositions and cycle extended students’ opportunities to reason in sophisticated ways appropriate for their age. The research question under investigation was, How can an emphasis on purpose, process and prediction be implemented to support children’s statistical modelling? The principles illustrated in the study may provide a simple framework for teachers and researchers to develop statistical modelling practices and norms at the school level.

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Acknowledgements

We gratefully acknowledge funding for this work from the Australian Research Council (ARC DP120100690, ARC DP170101993) and our research assistants Janine and Ali who transcribed these data and assisted with preliminary analysis.

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Correspondence to Katie Makar.

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Makar, K., Allmond, S. Statistical modelling and repeatable structures: purpose, process and prediction. ZDM Mathematics Education 50, 1139–1150 (2018). https://doi.org/10.1007/s11858-018-0956-y

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Keywords

  • Statistics education
  • Informal statistical inference
  • Statistical modelling
  • Repeatable structures