• DocumentCode
    2724118
  • Title

    Selecting the Right Peer Schools for AACSB Accreditation - A Data Mining Application

  • Author

    Kiang, Melody Y. ; Fisher, Dorothy M. ; Fisher, D.M. ; Chi, Robert T.

  • Author_Institution
    California State Univ., Long Beach, CA
  • fYear
    2007
  • fDate
    March 1 2007-April 5 2007
  • Firstpage
    31
  • Lastpage
    34
  • Abstract
    For a business school, the selection of its peer schools is an important component of its International Association for Management Education (AACSB) (re)accreditation process. A school typically compares itself with other institutions having similar structural and identity-based attributes. The identification of peer schools is critical and can have a significant impact on a business school´s accreditation efforts. For many schools the selection of comparable peer schools is a judgmental process. This study offers an alternative means for selection; a quantitative technique called Kohonen´s self-organizing map (SOM) network for clustering. SOM as a software agent uses visualization to present information to the school in choosing its peer schools.
  • Keywords
    accreditation; data mining; data visualisation; educational administrative data processing; self-organising feature maps; software agents; International Association for Management Education reaccreditation; Kohonen self-organizing map network; business school; data mining application; information visualization; peer school selection; software agent; Accreditation; Computational intelligence; Computer networks; Data mining; Data visualization; Educational institutions; Multidimensional systems; Neural networks; Software agents; Unsupervised learning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Data Mining, 2007. CIDM 2007. IEEE Symposium on
  • Conference_Location
    Honolulu, HI
  • Print_ISBN
    1-4244-0705-2
  • Type

    conf

  • DOI
    10.1109/CIDM.2007.368849
  • Filename
    4221273