IDEAS home Printed from https://ideas.repec.org/a/igg/jwsr00/v14y2017i4p50-74.html
   My bibliography  Save this article

A Framework of MLaaS for Facilitating Adaptive Micro Learning through Open Education Resources in Mobile Environment

Author

Listed:
  • Geng Sun

    (University of Wollongong, Wollongong, Australia)

  • Tingru Cui

    (School of Computing and Information Technology, University of Wollongong, Wollongong, Australia)

  • William Guo

    (Central Queensland University, North Rockhampton, Australia)

  • Shiping Chen

    (CSIRO Data61, Epping, Australia)

  • Jun Shen

    (University of Wollongong, Wollongong, Australia)

Abstract

Micro learning becomes popular in online open learning and it is effective and helpful for learning in mobile environment. However, the delivery of open education resources (OERs) is scarcely supported by the current online systems. In this research, the authors introduce an approach to bridge the gap by providing adaptive micro open education resources for individual learners to carry out learning activities in a short time span. They propose a framework for micro learning resource customization and a personalized learner model, which are supported by education data mining (EDM) and learning analysis (LA). A service-oriented architecture for Micro Learning as a Service (MLaaS) is designed to integrate all necessary procedures together as a complete Service for delivering micro OERs, providing a platform for resource sharing and exchanging in peer-to-peer learning environment. Working principle of a key step, namely the computational decision-making of micro OER adaptation, is also introduced.

Suggested Citation

  • Geng Sun & Tingru Cui & William Guo & Shiping Chen & Jun Shen, 2017. "A Framework of MLaaS for Facilitating Adaptive Micro Learning through Open Education Resources in Mobile Environment," International Journal of Web Services Research (IJWSR), IGI Global, vol. 14(4), pages 50-74, October.
    • Handle: RePEc:igg:jwsr00:v:14:y:2017:i:4:p:50-74
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJWSR.2017100103
    Download Restriction: no
    ---><---

    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:igg:jwsr00:v:14:y:2017:i:4:p:50-74. 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    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.