IDEAS home Printed from https://ideas.repec.org/a/bla/istatr/v75y2007i3p322-335.html
   My bibliography  Save this article

Virtual Environments and the Acceleration of Experiential Learning

Author

Listed:
  • Chris Wild

Abstract

Darius et al. (2007) and Nolan & Temple Lang (2007) give examples of virtual environments that can, for specific purposes, substitute for the real world. We are in the early stages of developments that could revolutionize statistics education by making it possible to capture efficiently important aspects of the thinking and practice of professional statisticians previously learned only from long years of experience. The ability of virtual environments to automate processes provides a potent weapon for tackling the tyranny that Time exercises over such modes of learning. We discuss the many new possibilities that are opened up by virtual environments together with cognitive and pedagogical imperatives to be addressed to ensure that environments actually do teach the lessons they were designed to teach. We echo Nolan and Temple Lang's call for the development of environments to be modular and open source. Taking the R‐project as a model, this can lead to a growing repository of building blocks that make the construction of future environments less costly, thus facilitating the realization of more and more ambitious conceptions.

Suggested Citation

  • Chris Wild, 2007. "Virtual Environments and the Acceleration of Experiential Learning," International Statistical Review, International Statistical Institute, vol. 75(3), pages 322-335, December.
    • Handle: RePEc:bla:istatr:v:75:y:2007:i:3:p:322-335
    DOI: 10.1111/j.1751-5823.2007.00033.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1751-5823.2007.00033.x
    Download Restriction: no
    File URL: https://libkey.io/10.1111/j.1751-5823.2007.00033.x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. 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.
    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. George W. Cobb, 2007. "One Possible Frame for Thinking about Experiential Learning," International Statistical Review, International Statistical Institute, vol. 75(3), pages 336-347, December.
    4. Paul L. Darius & Kenneth M. Portier & Eddie Schrevens, 2007. "Virtual Experiments and Their Use in Teaching Experimental Design," International Statistical Review, International Statistical Institute, vol. 75(3), pages 281-294, December.
    5. Joan B. Garfield & Iddo Gal, 1999. "Assessment and Statistics Education: Current Challenges and Directions," International Statistical Review, International Statistical Institute, vol. 67(1), pages 1-12, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. Chris J. Wild & Maxine Pfannkuch & Matt Regan & Ross Parsonage, 2017. "Accessible Conceptions of Statistical Inference: Pulling Ourselves Up by the Bootstraps," International Statistical Review, International Statistical Institute, vol. 85(1), pages 84-107, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Robert Gould, 2010. "Statistics and the Modern Student," International Statistical Review, International Statistical Institute, vol. 78(2), pages 297-315, August.
    2. 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.
    3. George W. Cobb, 2007. "One Possible Frame for Thinking about Experiential Learning," International Statistical Review, International Statistical Institute, vol. 75(3), pages 336-347, December.
    4. 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.
    5. 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.
    6. 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.
    7. Andreea Cujba & Manoli Pifarré, 2024. "Enhancing students’ attitudes towards statistics through innovative technology-enhanced, collaborative, and data-driven project-based learning," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-14, December.
    8. 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.
    9. 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.
    10. Wolfgang Härdle & Sigbert Klinke & Uwe Ziegenhagen, 2007. "On the Utility of E‐Learning in Statistics," International Statistical Review, International Statistical Institute, vol. 75(3), pages 355-364, December.
    11. 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.
    12. Chris J. Wild & Maxine Pfannkuch & Matt Regan & Ross Parsonage, 2017. "Accessible Conceptions of Statistical Inference: Pulling Ourselves Up by the Bootstraps," International Statistical Review, International Statistical Institute, vol. 85(1), pages 84-107, April.
    13. Carl J. Schwarz, 2007. "Computer‐Aided Statistical Instruction—Multi‐Mediocre Techno‐Trash?," International Statistical Review, International Statistical Institute, vol. 75(3), pages 348-354, December.
    14. 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.
    15. 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.
    16. Sinjini Mitra, 2023. "How Are Students Learning in a Business Statistics Course? Evidence from Both Direct and Indirect Assessment," INFORMS Transactions on Education, INFORMS, vol. 23(2), pages 95-103, January.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:istatr:v:75:y:2007:i:3:p:322-335. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/isiiinl.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.