• DocumentCode
    481962
  • Title

    An inspection of a system for improving learning abilities 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
  • fYear
    2008
  • fDate
    10-13 Nov. 2008
  • Firstpage
    3479
  • Lastpage
    3484
  • Abstract
    In this paper we propose a method to determine the optimal combination to improve learning effect through approaches of system engineering. A neural network model is applied for predicting the learning results of learners. This model has input values which are potential abilities and personalities of learners and has one output value which is the correctness rate for learning problems. In order to determine the optimal combination of learners, a genetic algorithm is applied by using the prediction results. An average value of scores in collaborative learning in an optimal combination of pairs of learners obtained through the use of a genetic algorithm is higher than that of scores in pairs based on a voluntary basis of learners. This proposed method can realize the combination of learners by a simple process.
  • Keywords
    computer aided instruction; genetic algorithms; neural nets; collaborative learning ability; genetic algorithm; learner personality; neural network model; system engineering; system inspection; Collaborative work; Educational institutions; Genetic algorithms; Genetic engineering; Information science; Inspection; Neural networks; Predictive models; Systems engineering and theory; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics, 2008. IECON 2008. 34th Annual Conference of IEEE
  • Conference_Location
    Orlando, FL
  • ISSN
    1553-572X
  • Print_ISBN
    978-1-4244-1767-4
  • Electronic_ISBN
    1553-572X
  • Type

    conf

  • DOI
    10.1109/IECON.2008.4758521
  • Filename
    4758521