• DocumentCode
    147518
  • Title

    Metrics for effectiveness of e-learning objects in software engineering education

  • Author

    Escobar, Alvaro E. ; Reyes, P. ; Van Hilst, Michael

  • Author_Institution
    Div. of Math, Sci. & Technol., Nova Southeastern Univ., Fort Lauderdale, FL, USA
  • fYear
    2014
  • fDate
    13-16 March 2014
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    In this paper we present the rationale and beginning of work on improving e-learning objects through the use of analytics modeled after Google Analytics. Prior work on the use of metrics in e-learning has focused on user satisfaction, and the ranking and selection of learning objects from a set of available choices. This work differs in its focus on the kinds of metrics needed to improve an existing object, or even more specifically to make improvements to specific pages within an object. This work is based on the now well established track record of using Google Analytics for Web site optimization in e-commerce. We discuss adaptations needed to apply similar metrics in the context of e-learning and more specifically e-learning objects.
  • Keywords
    learning management systems; Google Analytics; Web site optimization; analytics modelling; e-Iearning object improvement; e-commerce; e-learning object effectiveness; software engineering education; Business; Calibration; Current measurement; Electronic learning; Training; World Wide Web; Google Analytics; learning management systems; learning objects;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    SOUTHEASTCON 2014, IEEE
  • Conference_Location
    Lexington, KY
  • Type

    conf

  • DOI
    10.1109/SECON.2014.6950671
  • Filename
    6950671