• DocumentCode
    683581
  • Title

    Data Mining Methods to Assess Student Behavior in Adaptive e-Learning Processes

  • Author

    Marengo, Agostino ; Pagano, Annachiara ; Barbone, Alessio

  • Author_Institution
    Dept. of Econ. & Math. (DEM), Univ. of Bari Aldo Moro, Bari, Italy
  • fYear
    2013
  • fDate
    7-9 May 2013
  • Firstpage
    303
  • Lastpage
    309
  • Abstract
    How could data mining help the development of e-learning methodologies? How could an instructional designer take benefit from the use of adaptive learning? How could adaptive learning be implemented in an Open Source platform? In this paper will be described the implementation of adaptivity technology in a specific, Open Source, Learning Management System (LMS). After a preliminary study about the adaptive features already built-in and the capabilities ready to perform a suitable student modeling, the research team extended those capabilities with a specific data model, student model and tutoring engine to perform automatic monitoring and sequencing of Learning Objects for each particular learner. The future implementation of this project is related to testing activities in order to prove the efficiency method in content and course delivery. This paper describes some best practices developed during a Tempus IV Project granted by EU.
  • Keywords
    behavioural sciences; data mining; data models; educational courses; learning management systems; public domain software; user modelling; LMS; Tempus IV project; adaptive e-learning processes; adaptivity technology; content delivery; course delivery; data mining; data model; e-learning methodologies; instructional designer; learning management system; learning objects automatic monitoring; learning objects sequencing; open source platform; student behavior assessment; student modeling; testing activities; tutoring engine; Adaptation models; Adaptive systems; Data mining; Data models; Educational institutions; Least squares approximations; Adaptive; Data Mining; Learning Styles Activity locking; Open Source; Predicting; e-learning; learning management system; student modeling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    e-Learning "Best Practices in Management, Design and Development of e-Courses: Standards of Excellence and Creativity" , 2013 Fourth International Conference on
  • Conference_Location
    Manama
  • Type

    conf

  • DOI
    10.1109/ECONF.2013.60
  • Filename
    6745564