• DocumentCode
    148449
  • Title

    Representing examination question knowledge into Genetic Algorithm

  • Author

    Teo, Noor Hasimah Ibrahim ; Abu Bakar, Nordin ; Abd Rashid, Mohamad Rezduan

  • Author_Institution
    Fac. of Comput. & Math. Sci., Univ. Technol. MARA, Shah Alam, Malaysia
  • fYear
    2014
  • fDate
    3-5 April 2014
  • Firstpage
    900
  • Lastpage
    904
  • Abstract
    Examination is a medium of knowing the IQ of a person and how far is the understanding of certain subjects. Normally, the questions are prepared by course instructor in sets and become a burden if the subject is new to them as they needs to prepare it in a given time. This paper describes a method of auto generating a new set of final exam questions. The objectives of this paper are: to optimize selection of final examination question based on the Cognitive Level of Blooms Taxonomy; to design and develop a prototype of auto-generator examination question using Genetic Algorithm and to evaluate performance of this tool. There are many types of questions in an examination; but this system chooses to analyze the structured question only. The newly populated examination questions are based on the fittest value of the fitness function calculated. This technique can be upgraded and be used by other type of question too.
  • Keywords
    educational administrative data processing; educational courses; genetic algorithms; auto-generator examination question; blooms taxonomy cognitive level; course instructor; examination question knowledge representation; fitness function; genetic algorithm; Biological cells; Conferences; Generators; Genetic algorithms; Sociology; Statistics; Taxonomy; Genetic Algorithm; cognitive knowledge; examination question; knowledge extraction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Global Engineering Education Conference (EDUCON), 2014 IEEE
  • Conference_Location
    Istanbul
  • Type

    conf

  • DOI
    10.1109/EDUCON.2014.6826203
  • Filename
    6826203