• DocumentCode
    2434861
  • Title

    Diagnosing learning disabilities in a special education by an intelligent agent based system

  • Author

    ElSayed, Khaled Nasser

  • Author_Institution
    Comput. Sci. Dept., Umm Al-Qura Univ., Makkah AlMokaramah, Saudi Arabia
  • fYear
    2012
  • fDate
    12-13 Sept. 2012
  • Firstpage
    7
  • Lastpage
    12
  • Abstract
    Evaluation of Special education students is always done, manually, by specialists. The presented paper provides an intelligent agent based classification system for diagnosing and evaluation of learning disabilities with special education students. It provides pedagogy psychology profiles for those students and offer solution strategies with the best educational activities. It provides tools that allow class teachers to discuss psycho functions and basic skills for learning skills, then, performs psycho pedagogy evaluation by comprising a series of strategies in a semantic network knowledge base. The system´s agent performs its classification of student´s disabilities based on its past experience that it got from the exemplars that were classified by expert and acquired in its knowledge base.
  • Keywords
    intelligent tutoring systems; medical diagnostic computing; medical expert systems; psychology; intelligent agent-based classification system; learning disability diagnosis; learning disability evaluation; learning skills; pedagogy psychology profiles; psycho functions; psycho pedagogy evaluation; semantic network knowledge base; solution strategies; special education student evaluation; Cognition; Educational institutions; Intelligent agents; Knowledge based systems; Semantics; Writing; E-Health; Intelligent Agent; Learning Disabilities; Psych Pedagogy Evaluation; Semantic Network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Electronic Engineering Conference (CEEC), 2012 4th
  • Conference_Location
    Colchester
  • Print_ISBN
    978-1-4673-2665-0
  • Type

    conf

  • DOI
    10.1109/CEEC.2012.6375370
  • Filename
    6375370