• DocumentCode
    3018003
  • Title

    A method for Development of collaborative learning by using a neural network and a genetic algorithm

  • Author

    Shin-Ike, Kazuhiro ; Iima, Hitoshi

  • Author_Institution
    Electr. & Inf. Eng., Maizuru Nat. Coll. of Technol., Kyoto, Japan
  • fYear
    2009
  • fDate
    23-25 March 2009
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    In school education, there are many kinds of learning styles, and it is known that group learning (collaborative learning) is more effective than individual learning. In collaborative learning, it is very important how to determine the optimal combination of students in order to improve the learning effect. In this paper, we propose a method to improve the learning effect of collaborative learning. A neural network model is first applied for predicting learning results of pairs of students in collaborative learning. Then, in order to determine the optimal pairs of students, a genetic algorithm is applied with the prediction results obtained from the neural network. Based on this combination of students, we carried out an experiment of collaborative learning at a college in Japan. It was confirmed from the experimental results that the proposed method was effective.
  • Keywords
    computer aided instruction; genetic algorithms; groupware; neural nets; collaborative learning; genetic algorithm; group learning; neural network; Collaboration; Collaborative work; Educational institutions; Educational technology; Genetic algorithms; Genetic engineering; Information science; Neural networks; Predictive models; Testing; Academic Background; Collaborative Learning; Genetic Algorithm; Neural Network; Personality;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Autonomous Decentralized Systems, 2009. ISADS '09. International Symposium on
  • Conference_Location
    Athens
  • Print_ISBN
    978-1-4244-4327-7
  • Type

    conf

  • DOI
    10.1109/ISADS.2009.5207353
  • Filename
    5207353