• DocumentCode
    3713316
  • Title

    Using an analytical formalism to diagnostic and evaluate Massive Open Online Courses

  • Author

    Jihane Sophia Tahiri;Samir Bennani;Mohammed Khalidi Idrissi

  • Author_Institution
    RIME Team- Networking, Modeling and E-learning - LRIE Laboratory- Research in Computer Science and Education, Laboratory - EMI- Mohammadia School of Engineering- University Mohammed V of Rabat, Morocco
  • fYear
    2015
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Evaluation is a key element in the pedagogical strategy of all learning environments, especially Massive Open Online Courses (MOOC) since it allows quality improving of educational content and training tools. Recently, MOOC have proven the need for diagnostic and evaluation in terms of huge amount of potential data. In this context, this present paper describes our logical stepwise analytical approach which represents the process we have developed to effectively evaluate MOOC. This approach is based on a combination of Learning Analytics and traces.
  • Keywords
    "Analytical models","Data collection","Data models","Context","Instruments","History","Education"
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Systems: Theories and Applications (SITA), 2015 10th International Conference on
  • Type

    conf

  • DOI
    10.1109/SITA.2015.7358389
  • Filename
    7358389
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3713316