• DocumentCode
    735176
  • Title

    Drawing micro learning into MOOC: Using fragmented pieces of time to enable effective entire course learning experiences

  • Author

    Sun, Geng ; Tingru Cui ; Jianming Yong ; Jun Shen ; Shiping Chen

  • Author_Institution
    Sch. of Inf. Syst. & Technol., Univ. of Wollongong, Wollongong, NSW, Australia
  • fYear
    2015
  • fDate
    6-8 May 2015
  • Firstpage
    308
  • Lastpage
    313
  • Abstract
    Recently the massive open online course (MOOC) is an emerging trend that attracts many educators´ and researchers´ attentions. Based on our pilot study focusing on the development and operation of MOOC in Australia, we found MOOC is featured with mastery learning and blended learning, but it suffers from low completion rates. Brining micro learning into MOOC can be a feasible solution to improve current MOOC delivery and learning experience. We design a system which aims to provide adaptive micro learning contents as well as learning path identifications customized for each individual learner. To investigate how micro learning can impact learning experience and knowledge acquisitions of learners participated in MOOC, we suggest a potential scheme including hypotheses to evaluate our proposed approach.
  • Keywords
    computer aided instruction; educational courses; Australia; MOOC; course learning; drawing micro learning; learning path identifications; massive open online course; Australia; Data mining; Education; Lead; World Wide Web; Blended Learning; MOOC; Mastery Learning; Micro Learning; Resource Adaptation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Supported Cooperative Work in Design (CSCWD), 2015 IEEE 19th International Conference on
  • Conference_Location
    Calabria
  • Print_ISBN
    978-1-4799-2001-3
  • Type

    conf

  • DOI
    10.1109/CSCWD.2015.7230977
  • Filename
    7230977