• DocumentCode
    3234128
  • Title

    Personalized web based English learning system using artificial neural networks

  • Author

    Wang, Shiqiang ; He, Yuhang ; Liu, Zheng ; Wu, Huimin

  • Author_Institution
    Sch. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
  • fYear
    2009
  • fDate
    25-28 July 2009
  • Firstpage
    1263
  • Lastpage
    1268
  • Abstract
    Traditional educational systems are usually presented in a course based and static way, without taking into account the learner´s interests and learning progress. Language learning by that means could be accompanied by boredom and lack of real experiences, which is a great barrier to improving language skills. This paper presents an English learning system that is based on Web browsing. Users browse English websites of their own interests and the system grabs the proper words for the user to learn. A personalized forgetting curve is stored in the system and adapted to the user using a back-propagation artificial neural network. The system selects the learning contents according to the personalized forgetting curve. The learning data is sent to the server through Web service, to get assistance from a tutor or share the vocabulary list with other users.
  • Keywords
    backpropagation; computer aided instruction; educational courses; natural languages; neural nets; online front-ends; Web based English learning system; Web browsing; Web service; back-propagation artificial neural network; educational course; personalized forgetting curve; vocabulary; Artificial neural networks; Computer science; Computer science education; Electronic learning; Helium; Learning systems; Natural languages; System testing; Systems engineering education; Vocabulary; English learning; artificial neural networks; e-learning; intelligent system;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science & Education, 2009. ICCSE '09. 4th International Conference on
  • Conference_Location
    Nanning
  • Print_ISBN
    978-1-4244-3520-3
  • Electronic_ISBN
    978-1-4244-3521-0
  • Type

    conf

  • DOI
    10.1109/ICCSE.2009.5228407
  • Filename
    5228407