• DocumentCode
    2925423
  • Title

    Automatic learning sequence template generation for educational reuse

  • Author

    Yen, Neil Y. ; Jin, Qun ; Shih, Timothy K. ; Lin, Li-Chieh

  • Author_Institution
    Dept. of Human Inf. & Cognitive Sci., Waseda Univ., Saitama, Japan
  • fYear
    2011
  • fDate
    8-10 Nov. 2011
  • Firstpage
    773
  • Lastpage
    778
  • Abstract
    Sharing resources and information on Internet has become an important activity for education. The learning object repository has been developed to achieve efficient management of learning objects. Following usage experiences of learning objects collected in the past, this study concentrates on investigating implicit information between learning objects. We define a social structure for identifying relationship between learning objects and define a set of metrics to evaluate the interdependency. The structure identifies usage experiences and can be graphed in terms of implicit and explicit relations among learning objects. As a practical contribution, an adaptive algorithm is proposed to mine the social structure. The algorithm generates adaptive learning sequence by identifying possible interactive search input and assists them in completing self-paced learning situation.
  • Keywords
    Internet; educational computing; social networking (online); Internet; adaptive algorithm; adaptive learning sequence; automatic learning sequence template generation; education activity; educational reuse; information sharing; learning object management; learning object repository; resource sharing; self-paced learning situation; social structure mining; Arrays; Correlation; Measurement; Object recognition; Organizations; Peer to peer computing; Social network services; automatic mechanism; learning object; learning sequence; reusability; social network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Granular Computing (GrC), 2011 IEEE International Conference on
  • Conference_Location
    Kaohsiung
  • Print_ISBN
    978-1-4577-0372-0
  • Type

    conf

  • DOI
    10.1109/GRC.2011.6122696
  • Filename
    6122696