• DocumentCode
    259216
  • Title

    ePortfolio System Design Based on Ontological Model of Self-Regulated Learning

  • Author

    Lap Trung Nguyen ; Ikeda, Makoto

  • Author_Institution
    Fac. of Sci. & Technol., Hoa Sen Univ., Ho Chi Minh City, Vietnam
  • fYear
    2014
  • fDate
    Aug. 31 2014-Sept. 4 2014
  • Firstpage
    301
  • Lastpage
    306
  • Abstract
    Self-regulated learning (SRL) has positive effects on learners´ success in and beyond school, and it may be fostered by technology enhanced learning environments, especially ePortfolio platform. However, the lack of explicit technological models leads to challenges in fostering SRL, such as capturing and sharing SRL principles, creating a platform for SRL´s processes implementation. The purpose of this research is to propose an ontological model and use it to design an ePortfolio system to promote SRL. We used ontologies to represent an integrated model that consists of ePortfolio model, competency model and SRL model. Based on this model, we implemented the ePortfolio system and used it for the first experiments at Hoa Sen University. The results indicate that students had a positive reaction to the ePortfolio system, and the system affected students´ achievement and SRL positively.
  • Keywords
    computer aided instruction; educational institutions; ontologies (artificial intelligence); systems analysis; Hoa Sen University; SRL model; SRL principles; competency model; eportfolio model; eportfolio platform; eportfolio system design; learners success; ontological model; school; self-regulated learning; students achievement; technological models; technology enhanced learning environments; Computational modeling; Educational institutions; Monitoring; Ontologies; Planning; Process control; ePortfolio; ontology; self-regulated learning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Applied Informatics (IIAIAAI), 2014 IIAI 3rd International Conference on
  • Conference_Location
    Kitakyushu
  • Print_ISBN
    978-1-4799-4174-2
  • Type

    conf

  • DOI
    10.1109/IIAI-AAI.2014.69
  • Filename
    6913313