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How Students Learn Statistics Revisited: A Current Review of Research on Teaching and Learning Statistics

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  • Joan Garfield
  • Dani Ben‐Zvi

Abstract

This paper provides an overview of current research on teaching and learning statistics, summarizing studies that have been conducted by researchers from different disciplines and focused on students at all levels. The review is organized by general research questions addressed, and suggests what can be learned from the results of each of these questions. The implications of the research are described in terms of eight principles for learning statistics from Garfield (1995) which are revisited in the light of results from current studies. Cet article présente une vue d'ensemble de la recherche actuelle sur l'enseignement et l'étude de la statistique. Il résume les analyses qui ont été menées par des chercheurs de disciplines différentes. Le travail s'organise autour de questions de recherche générales qui ont été adressées, et suggère ce que l'on peut apprendre à partir de ces résultats au sujet de chacune de ces questions. Les implications de la recherche sont décrites en termes de huit principes sur l'étude de la statistique de Garfield (1995) qui sont repris selon les résultats d'études actuelles.

Suggested Citation

  • Joan Garfield & Dani Ben‐Zvi, 2007. "How Students Learn Statistics Revisited: A Current Review of Research on Teaching and Learning Statistics," International Statistical Review, International Statistical Institute, vol. 75(3), pages 372-396, December.
  • Handle: RePEc:bla:istatr:v:75:y:2007:i:3:p:372-396
    DOI: 10.1111/j.1751-5823.2007.00029.x
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    Cited by:

    1. Forney Andrew & Mueller Scott, 2022. "Causal inference in AI education: A primer," Journal of Causal Inference, De Gruyter, vol. 10(1), pages 141-173, January.
    2. Ángel Peiró-Signes & Óscar Trull & Marival Segarra-Oña & J. Carlos García-Díaz, 2020. "Attitudes Towards Statistics in Secondary Education: Findings from fsQCA," Mathematics, MDPI, vol. 8(5), pages 1-17, May.
    3. Robert Gould, 2010. "Statistics and the Modern Student," International Statistical Review, International Statistical Institute, vol. 78(2), pages 297-315, August.
    4. Peter Petocz & Anna Reid, 2010. "On Becoming a Statistician—A Qualitative View," International Statistical Review, International Statistical Institute, vol. 78(2), pages 271-286, August.
    5. Lisa Dierker & Jane Robertson Evia & Karen Singer-Freeman & Kristin Woods & Janet Zupkus & Alan Arnholt & Elizabeth G Moliski & Natalie Delia Deckard & Kristel Gallagher & Jennifer Rose, 2018. "Project-Based Learning in Introductory Statistics: Comparing Course Experiences and Predicting Positive Outcomes for Students from Diverse Educational Settings," International Journal of Educational Technology and Learning, Scientific Publishing Institute, vol. 3(2), pages 52-64.
    6. Heejoo Suh & Sohyung Kim & Seonyoung Hwang & Sunyoung Han, 2020. "Enhancing Preservice Teachers’ Key Competencies for Promoting Sustainability in a University Statistics Course," Sustainability, MDPI, vol. 12(21), pages 1-21, October.
    7. Dina El Kayaly, 2013. "Towards more real-live teachings of business statistics: a Review of Challenges, Teaching Innovations and Strategies for Reform in Egypt," Working Papers 2013/21, Maastricht School of Management.
    8. Chris Wild, 2007. "Virtual Environments and the Acceleration of Experiential Learning," International Statistical Review, International Statistical Institute, vol. 75(3), pages 322-335, December.
    9. David Delgado-Gómez & Franks González-Landero & Carlos Montes-Botella & Aaron Sujar & Sofia Bayona & Luca Martino, 2020. "Improving the Teaching of Hypothesis Testing Using a Divide-and-Conquer Strategy and Content Exposure Control in a Gamified Environment," Mathematics, MDPI, vol. 8(12), pages 1-14, December.
    10. Constance H. McLaren & Bruce J. McLaren, 2014. "Possible or Probable? An Experiential Approach to Probability Literacy," INFORMS Transactions on Education, INFORMS, vol. 14(3), pages 129-136, May.

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