• DocumentCode
    2223489
  • Title

    Intelligent reflective e-portfolio framework supported by Problem Based Learning

  • Author

    Jaryani, Frahang ; Daneshvar, Hooman ; Sahibudin, Shamsul

  • Author_Institution
    Fac. of Comput. Sci. & Inf. Syst., Univ. Teknol. Malaysia, Kuala Lumpur, Malaysia
  • Volume
    5
  • fYear
    2010
  • fDate
    20-22 Aug. 2010
  • Abstract
    The aim of this paper is to present the role of Artificial Intelligence techniques to enhance reflective e-portfolios quality. Some AI techniques such as expert system; scheduling; Data Mining can support us to enhance our reflective e-portfolios quality. To get better result the designed portfolio has been supported by Problem Based Learning as an effective educational method. These tools together will define new intelligent Reflective e-portfolio that provides intelligent and customized learning method for each student based on their backgrounds and their realities. The final vision of intelligent reflective e-portfolio is to act as an expert to consult students and support them to make Right decisions for their learning complexities.
  • Keywords
    business data processing; data mining; expert systems; learning (artificial intelligence); scheduling; artificial intelligence techniques; data mining; expert system; intelligent reflective e-portfolio framework; problem based learning; reflective e-portfolio quality; scheduling; Artificial intelligence; Computational modeling; Databases; Educational institutions; Portfolios; Artificial Intelligence; Data Mining; Problem Based Learning; Reflective e-portfolio;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Computer Theory and Engineering (ICACTE), 2010 3rd International Conference on
  • Conference_Location
    Chengdu
  • ISSN
    2154-7491
  • Print_ISBN
    978-1-4244-6539-2
  • Type

    conf

  • DOI
    10.1109/ICACTE.2010.5579347
  • Filename
    5579347