• DocumentCode
    1858787
  • Title

    An Automatic Grading Model for Learning Assessment

  • Author

    Liu, Yang

  • Author_Institution
    Sch. of Inf. & Electron. Eng., Zhejiang Univ. of Sci. & Technol., Hangzhou, China
  • fYear
    2010
  • fDate
    22-24 Jan. 2010
  • Firstpage
    217
  • Lastpage
    220
  • Abstract
    Particle swarm optimization (PSO) is an algorithm modelled on swarm intelligence that finds a solution to an optimization problem in a search space. In this paper, a PSO-based artificial neural network algorithm is proposed to automatically grading the learning results. Basically, the PSO algorithm is utilized to adjust the connection weights of the selected ANN topology. Taken mandarin learning as example, we introduced the PSO-based ANN algorithm to grading mandarin learning, the experimental results shown it´s an effective method.
  • Keywords
    educational administrative data processing; neural nets; particle swarm optimisation; ANN topology; PSO algorithm; artificial neural network; automatic grading model; learning assessment; particle swarm optimization; search space; swarm intelligence; Artificial neural networks; Birds; Education; Electronic learning; Equations; Network topology; Neurofeedback; Particle swarm optimization; Quality management; Space technology; artificial neural network; learning assessment; particle swarm optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    e-Education, e-Business, e-Management, and e-Learning, 2010. IC4E '10. International Conference on
  • Conference_Location
    Sanya
  • Print_ISBN
    978-1-4244-5680-2
  • Electronic_ISBN
    978-1-4244-5681-9
  • Type

    conf

  • DOI
    10.1109/IC4E.2010.32
  • Filename
    5432425