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Science Scope Volume 45, 2022 - Issue 3: Science Teaching Challenges
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Interdisciplinary Ideas: Why Is Variability Worth the Teaching Challenge?

Kristin Hunter-ThomsonView further author information
Pages 8-13 | Published online: 06 Oct 2023

References

  • Cobb, P. 2009. Individual and collective mathematical development: The case of statistical data analysis. Mathematical Thinking and Learning 1 [1]: 5–43.
  • Hunter-Thomson, K. 2019. Data Literacy 101: Which is the Best Graph to Use? Science Scope 42 [5]: 26–31.
  • Hunter-Thomson, K. 2020. Data Literacy 101: What can we actually claim from our data? Science Scope 43 [6]: 20–26.
  • Hunter-Thomson, K. 2021. Data Literacy 101: How can we better move from data to meaning? Get data ready to use! Science Scope 44 [3]: 20–26.
  • Konold, C., T. Higgins, S.J. Russell, and K. Khalil. 2015. Data seen through different lenses. Educational Studies in Mathematics 88 [3]: 305–325.
  • National Governors Association Center for Best Practices and Council of Chief State School Officers (NGAC and CCSSO). 2010. Common core state standards. Washington, DC: NGAC and CCSSO.
  • Schauffler, M. 2019. Embrace variability https://partnersindataliteracy.com/2019/02/08/variability/
  • Wheelan, C.J. 2014. Naked statistics: Stripping the dread from the data. New York, NY: W.W. Norton.

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