• DocumentCode
    3595591
  • Title

    Research on Quality Evaluation of Multimedia Courseware Based on Neural Network

  • Author

    Guancheng, Lin ; Weiliang, Luo

  • Author_Institution
    Coll. of Marine Eng., Northwestern Polytech. Univ., Xi´´an, China
  • Volume
    1
  • fYear
    2009
  • Firstpage
    283
  • Lastpage
    286
  • Abstract
    It is of great significance to study the index weight that plays an important role in the system of comprehensive evaluation-signs of multimedia courseware. To eliminate the randomicity in the process of overall evaluation, this paper analyses and constructs the evaluation model of index weight based on artificial neural network back propagation (BP) algorithm as well as the method of designing and realization. By comparing the emulation with the artificial evaluation, the results indicate that the evaluation model could effectively avoid the subjective factors and uncertainty in the process of computing weight and the relevance modulus, which provides not only the objective criterion, but also reasonable and scientific method for the qualitative and quantitive evaluation of multimedia courseware.
  • Keywords
    backpropagation; courseware; multimedia computing; neural nets; artificial neural network backpropagation algorithm; index weight; multimedia courseware; quality evaluation; relevance modulus; Algorithm design and analysis; Artificial neural networks; Courseware; Education; Educational institutions; Feedforward neural networks; Multi-layer neural network; Multimedia systems; Neural networks; Neurofeedback; artificial neural network; multimedia courseware; quality evaluation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Information Technology Application, 2009. IITA 2009. Third International Symposium on
  • Print_ISBN
    978-0-7695-3859-4
  • Type

    conf

  • DOI
    10.1109/IITA.2009.220
  • Filename
    5369652