• DocumentCode
    13735
  • Title

    Educational Data Mining: An Advance for Intelligent Systems in Education

  • Author

    Baker, Ryan S.

  • Author_Institution
    Teachers Coll., Columbia Univ., New York, NY, USA
  • Volume
    29
  • Issue
    3
  • fYear
    2014
  • fDate
    May-June 2014
  • Firstpage
    78
  • Lastpage
    82
  • Abstract
    Educational data mining methods have been successful at modeling a range of phenomena relevant to student learning in online intelligent systems. Here, the author considers the current state of the field, outlining recent strides and remaining challenges.
  • Keywords
    data mining; intelligent tutoring systems; educational data mining methods; online intelligent systems; student learning; Data mining; Detectors; Educational institutions; Learning systems; Software development; MOOCs; MOOTs; Moment-by-Moment Learning Model; PSLC DataShop; education data mining; intelligent systems;
  • fLanguage
    English
  • Journal_Title
    Intelligent Systems, IEEE
  • Publisher
    ieee
  • ISSN
    1541-1672
  • Type

    jour

  • DOI
    10.1109/MIS.2014.42
  • Filename
    6871689
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=13735