Considering the 5 Practices Through a Statistical Lens

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Karoline Smucker Eastern Oregon University

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Francisco Sepúlveda Cinvestav, Mexico City

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Travis Weiland University of Houston

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Susan Cannon University of Georgia

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Stephanie Casey Eastern Michigan University in Ypsilanti

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Sunghwan Byun North Carolina State University

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An adaptation of The 5 Practices framework for statistical investigations that accounts for differences between mathematics and statistics.

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Mathematics Teacher: Learning and Teaching PK-12
  • Bargagliotti, A., Franklin, C., Arnold, P., Johnson, S., Perez, L., & Spangler, S. (2020). Pre-K–12 guidelines for assessment and instruction in statistics education II (GAISE II): A framework for statistics and data science education. American Statistical Association.

    • Search Google Scholar
    • Export Citation
  • Byun, S., Weiland, T., Cannon, S., Fernandes, A., Nti-Asante, E., Peterson, F., Smucker, K., & Engledowl, C. (2023). Teaching and learning with data investigation: Working group report from 2022. In T. Lamberg & D. Moss (Eds.), Proceedings of the forty-fifth annual meeting of the North American Chapter of the International Group for the Psychology of Mathematics Education (Vol. 2, pp. 674678). University of Nevada Reno.

    • Search Google Scholar
    • Export Citation
  • Cobb, G. W., & Moore, D. S. (1997). Mathematics, statistics, and teaching. The American Mathematical Monthly, 104(9), 801823. https://doi.org/10.1080/00029890.1997.11990723

    • Search Google Scholar
    • Export Citation
  • Concord Consortium. (2023). Common online data analysis platform (CODAP) [computer software]. https://codap.concord.org/

  • Franklin, C. A., Bargagliotti, A. E., Case, C. A., Kader, G. D., Scheaffer, R. L., &, Spangler, D. A. (2015). Statistical education of teachers. American Statistical Association. https://www.amstat.org/asa/files/pdfs/EDU-SET.pdf

    • Search Google Scholar
    • Export Citation
  • Groth, R. E. (2015). Using the five practices model to promote statistical discourse. Teaching Statistics, 37(1), 1317. https://doi.org/10.1111/test.12052

    • Search Google Scholar
    • Export Citation
  • Konold, C., Higgins, T., Russell, S. J., & Khalil, K. (2015). Data seen through different lenses. Educational Studies in Mathematics, 88(3), 305325. https://doi.org/10.1007/s10649-013-9529-8

    • Search Google Scholar
    • Export Citation
  • Makar, K., & Rubin, A. (2009). A framework for thinking about informal statistical inference. Statistics Education Research Journal, 8(1), 82105.

    • Search Google Scholar
    • Export Citation
  • Mojica, G. F., Azmy, C. N., & Lee, H. S. (2019). Exploring data with CODAP. Mathematics Teacher, 112(6), 473476. https://doi.org/10.5951/mathteacher.112.6.0473.

    • Search Google Scholar
    • Export Citation
  • National Council of Teachers of Mathematics. (2000). Principles and standards for school mathematics.

  • National Council of Teachers of Mathematics. (2014). Principles to action: Ensuring mathematical success for all.

  • Smith, M., Bill, V., & Sherin, M. G. (2020). The 5 practices in practice: Successfully orchestrating mathematics discussions in your elementary classroom. Corwin Press.

    • Search Google Scholar
    • Export Citation
  • Smith, M., & Stein, M. K. (2018). 5 practices for orchestrating productive mathematics discussions .National Council of Teachers of Mathematics.

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    • Export Citation
  • Wild, C. J., & Pfannkuch, M. (1999). Statistical thinking in empirical enquiry. International Statistical Review, 67(3), 223248.

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