Promoting Statistical Literacy Through Data Modelling in the Early School Years
This chapter addresses data modelling as a means of promoting statistical literacy in the early grades. Consideration is first given to the importance of increasing young children’s exposure to statistical reasoning experiences and how data modelling can
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Abstract This chapter addresses data modelling as a means of promoting statistical literacy in the early grades. Consideration is first given to the importance of increasing young children’s exposure to statistical reasoning experiences and how data modelling can be a rich means of doing so. Selected components of data modelling are then reviewed, followed by a report on some findings from the third-year of a three-year longitudinal study across grades one through three.
1 Statistical Literacy and Young Children Across all walks of life, the need to understand and to apply statistical literacy is paramount. Statistics underlie not only every economic report and census, but also every clinical trial and opinion poll in modern society. Our unprecedented access to a vast array of numerical information means we can engage increasingly in democratic discourse and public decision-making—that is, provided we have an appropriate understanding of statistics and statistical literacy. Statistical literacy, however, requires a long time to develop and must begin in the earliest years of schooling (English 2010; Franklin and Garfield 2006; Watson 2006). Numerous definitions of statistical literacy abound (e.g. Gal 2002). The notion adopted here is that of Watson (2006), namely, statistical literacy is “the meeting point” of the statistics and probability strand of a given curriculum and “the everyday world, where encounters involve unrehearsed contexts and spontaneous decision-making based on the ability to apply statistical tools, general contextual knowledge, and critical literacy skills” (Watson 2006, p. 11). Young children are very much a part of our data-driven society. They have early access to computer technology, the source of our information explosion. They have daily exposure to the mass media where various displays of data and related reports (e.g. weather reports and popularity contests) can easily mystify or misinform, rather than inform, their young minds. The need to advance children’s statistical
L.D. English (B) Queensland University of Technology, Brisbane, Queensland, Australia e-mail: [email protected] E.J. Chernoff, B. Sriraman (eds.), Probabilistic Thinking, Advances in Mathematics Education, DOI 10.1007/978-94-007-7155-0_23, © Springer Science+Business Media Dordrecht 2014
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reasoning abilities, from the earliest years of schooling, has thus been stressed in recent years (e.g. Langrall et al. 2008; Shaughnessy 2010; Whitin and Whitin 2011). One approach to enhancing children’s statistical abilities is through data modelling (English 2010; Lehrer and Romberg 1996; Lehrer and Schauble 2007).
2 Data Modelling Data modelling is a developmental process, beginning with young children’s inquiries and investigations of meaningful phenomena, progressing to identifying various attributes of the phenomena, and then moving towards organising, structuring, visualising, and representing data (Lehrer and Lesh 2003). Data modelling should be a fundamental component of early childhood curricu
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