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New Pedagogy and New Content: The Case of Statistics

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  • David S. Moore

Abstract

Statistical education now takes place in a new social context. It is influenced by a movement to reform the teaching of the mathematical sciences in general. At the same time, the changing nature of our discipline demands revised content for introductory instruction, and technology strongly influences both what we teach and how we teach. The case for substantial change in statistics instruction is built on strong synergies between content, pedagogy, and technology. Statisticians who teach beginners should become more familiar with research on teaching and learning and with changes in educational technology. The spirit of contemporary introductions to statistics should be very different from the traditional emphasis on lectures and on probability and inference. L'éducation statistique se déroule maintenant dans un nouveau contexte social. Eile se trouve influcncée par un mouvenment de réforme de l'enseignement géneacute;ral des sciences mathématiques. de plus la nature changeante de discipline exige un un contenu revisé au niveau des cours d'introduction et la technoligie influence fortement aussi bien ce qui est enseigné que la facon dont on l'enseigne. Le arguments en faveur de changements subtantiels dans l'enseignement de la statistique reposent dur de familiariser davantage avec recherches sur l'enseignement et l'apprentissage et avec les changements dans les technologies d'éducation. L'esprit de l'introducation á la statistique contemporaine devriat se détacher de l'importance traditionellement accordée au cours magistral et la probabilité et á la probabilité et l'inférence.

Suggested Citation

  • 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.
    • Handle: RePEc:bla:istatr:v:65:y:1997:i:2:p:123-137
    DOI: 10.1111/j.1751-5823.1997.tb00390.x
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    Cited by:

    1. Robert Gould, 2010. "Statistics and the Modern Student," International Statistical Review, International Statistical Institute, vol. 78(2), pages 297-315, August.
    2. Deborah Nolan & Duncan Temple Lang, 2007. "Dynamic, Interactive Documents for Teaching Statistical Practice," International Statistical Review, International Statistical Institute, vol. 75(3), pages 295-321, December.
    3. Gilberte Schuyten & Olivier Thas, 2007. "Statistical Thinking in Computer‐Based Learning Environments," International Statistical Review, International Statistical Institute, vol. 75(3), pages 365-371, December.
    4. Peter K. Dunn & Michael D. Carey & Michael B. Farrar & Alice M. Richardson & Christine McDonald, 2017. "Introductory Statistics Textbooks and the GAISE Recommendations," The American Statistician, Taylor & Francis Journals, vol. 71(4), pages 326-335, October.
    5. Adam R. Cocco & Matthew Katz & Marion E. Hambrick, 2021. "Co-Attendance Communities: A Multilevel Egocentric Network Analysis of American Soccer Supporters’ Groups," IJERPH, MDPI, vol. 18(14), pages 1-18, July.
    6. Yunkee Ahn & Buhn Nam & Chul Eung Kim, 2003. "The Future Direction of Statistical Training for the Promotion of Cooperation between Government and Academy," International Statistical Review, International Statistical Institute, vol. 71(2), pages 461-467, August.
    7. Tommy Soesmanto & Suzanne Bonner, 2018. "Dual mode delivery in introductory statistics: Design and evaluation," Discussion Papers in Economics economics:201801, Griffith University, Department of Accounting, Finance and Economics.
    8. Maria Jureckova & Lucia Csachova, 2020. "Statistical literacy of Slovak lower secondary school students," Technium Social Sciences Journal, Technium Science, vol. 9(1), pages 163-173, July.
    9. 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.
    10. repec:thr:techub:1009:y:2020:i:1:p:163-173 is not listed on IDEAS
    11. Paula Carroll & Arthur White, 2017. "Identifying Patterns of Learner Behaviour: What Business Statistics Students Do with Learning Resources," INFORMS Transactions on Education, INFORMS, vol. 18(1), pages 1-13, September.
    12. Scotland Leman & Leanna House & Andrew Hoegh, 2015. "Developing a New Interdisciplinary Computational Analytics Undergraduate Program: A Qualitative-Quantitative-Qualitative Approach," The American Statistician, Taylor & Francis Journals, vol. 69(4), pages 397-408, November.

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