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Analysing Probability Teaching Practices in Primary Education: What Tasks Do Teachers Implement?

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  • Claudia Vásquez

    (Campus Villarrica, Pontificia Universidad Católica de Chile, Villarrica 4930445, Chile)

  • Ángel Alsina

    (Departament of Subject-Specific Didactics, Universitat de Girona, 17004 Girona, Spain)

Abstract

This study analyses probability tasks proposed by primary education teachers to promote probabilistic literacy. To this end, eight class sessions at various levels of the Chilean educational system were recorded on video and analysed through the ”probability tasks” dimension from the “Observation Instrument for Probability Classes” (IOC-PROB), which includes five components: use of resources, probabilistic contexts, cognitive challenge, procedures and strategies, and probability meanings. The results show that probability tasks focus mainly on technical knowledge, causing the probability class to become an arithmetic class in which only formulas are applied, mechanically and with no meaning. As a result, we see no use of technological resources, a low use of physical materials, and an absolute predominance of solving decontextualised exercises. We conclude that it is necessary to enhance the probability teaching practices based on lesson plans that consider a wide variety of resources and contexts to gradually advance towards a representation of probabilistic knowledge that relies on conventional procedures and notations.

Suggested Citation

  • Claudia Vásquez & Ángel Alsina, 2021. "Analysing Probability Teaching Practices in Primary Education: What Tasks Do Teachers Implement?," Mathematics, MDPI, vol. 9(19), pages 1-21, October.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:19:p:2493-:d:650133
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    References listed on IDEAS

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    1. C. J. Wild & M. Pfannkuch, 1999. "Statistical Thinking in Empirical Enquiry," International Statistical Review, International Statistical Institute, vol. 67(3), pages 223-248, December.
    2. David S. Moore, 1997. "New Pedagogy and New Content: The Case of Statistics," International Statistical Review, International Statistical Institute, vol. 65(2), pages 123-137, August.
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