IDEAS home Printed from https://ideas.repec.org/a/bla/jamist/v58y2007i14p2295-2309.html
   My bibliography  Save this article

Adaptive technology for e‐learning: principles and case studies of an emerging field

Author

Listed:
  • Kathleen Scalise
  • Diana J. Bernbaum
  • Mike Timms
  • S. Veeragoudar Harrell
  • Kristen Burmester
  • Cathleen A. Kennedy
  • Mark Wilson

Abstract

This article discusses the rapidly emerging field of computer‐based assessment for adaptive content in e‐learning (National Research Council, 2001), which we call differentiated e‐learning. In e‐learning products, a variety of assessment approaches are being used for such diverse purposes as adaptive delivery of content, individualizing learning materials, dynamic feedback, cognitive diagnosis, score reporting, and course placement (Gifford, 2001). A recent paper at the General Teaching Council Conference in London, England, on teaching, learning, and accountability described assessment for personalized learning through e‐learning products as a “quiet revolution” taking place in education (Hopkins, 2004). In our study, we examine approaches for the use of assessment evidence in e‐learning in four case studies. The products in the case studies were selected for exhibiting at least one exemplary aspect regarding assessment and measurement. The principles of the Berkeley Evaluation & Assessment Research Center Assessment System (Wilson & Sloane, 2000) are used as a framework of analysis for these products with respect to key measurement principles.

Suggested Citation

  • Kathleen Scalise & Diana J. Bernbaum & Mike Timms & S. Veeragoudar Harrell & Kristen Burmester & Cathleen A. Kennedy & Mark Wilson, 2007. "Adaptive technology for e‐learning: principles and case studies of an emerging field," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 58(14), pages 2295-2309, December.
  • Handle: RePEc:bla:jamist:v:58:y:2007:i:14:p:2295-2309
    DOI: 10.1002/asi.20701
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/asi.20701
    Download Restriction: no

    File URL: https://libkey.io/10.1002/asi.20701?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
    ---><---

    Citations

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


    Cited by:

    1. Shuo Xu & Liyuan Hao & Xin An & Hongshen Pang & Ting Li, 2020. "Review on emerging research topics with key-route main path analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 607-624, 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:jamist:v:58:y:2007:i:14:p:2295-2309. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: http://www.asis.org .

    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.