• DocumentCode
    2953393
  • Title

    Applying knowledge engineering methods to didactic knowledge first steps towards an ultimate goal

  • Author

    Knauf, Rainer ; Sakurai, Yoshitaka ; Tsuruta, Setsuo

  • Author_Institution
    Fac. of Comput. Sci. & Autom., Univ. of Ilmenau, Ilmenau
  • fYear
    2008
  • fDate
    1-8 June 2008
  • Firstpage
    38
  • Lastpage
    45
  • Abstract
    Generally, learning systems suffer from a lack of an explicit and adaptable didactic design. Since E-Learning systems are digital by their very nature, their introduction rises the issue of modeling the didactic design in a way that implies the chance to apply Knowledge Engineering Techniques (like Machine Learning and Data Mining). A modeling approach called storyboarding, is outlined here. Storyboarding is setting the stage to apply Knowledge Engineering Technologies to verify and validate the didactics behind a learning process. Moreover, didactics can be refined according to revealed weaknesses and proven excellence and successful didactic patterns can be inductively inferred by analyzing the particular knowledge processing and its alleged contribution to learning success.
  • Keywords
    computer aided instruction; knowledge engineering; learning (artificial intelligence); adaptable didactic design; data mining; didactic knowledge; e-learning systems; explicit didactic design; knowledge engineering methods; knowledge engineering technologies; knowledge processing; machine learning; storyboarding; Electronic learning; Electrophysiology; Employment; Humans; Knowledge engineering; Organizing; Process design; Shape; Software systems; Technological innovation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on
  • Conference_Location
    Hong Kong
  • ISSN
    1098-7576
  • Print_ISBN
    978-1-4244-1820-6
  • Electronic_ISBN
    1098-7576
  • Type

    conf

  • DOI
    10.1109/IJCNN.2008.4633764
  • Filename
    4633764