• DocumentCode
    3143275
  • Title

    Using a Competence Model to Aggregate Learning Knowledge Objects

  • Author

    Zouaq, Amal ; Nkambou, Roger ; Frasson, Claude

  • Author_Institution
    Univ. of Montreal, Montreal
  • fYear
    2007
  • fDate
    18-20 July 2007
  • Firstpage
    836
  • Lastpage
    840
  • Abstract
    Competence-based learning models have great importance for learning resources: they constitute a meaningful structure for just-in-time and just-enough learning. In this paper, we present an ontology-based competence model that allows the on-the-fly generation of learning knowledge objects (LKOs). The automatic aggregation process relies on knowledge objects and ontologies created through text mining and natural language processing. It is guided by instructional theories encoded declaratively through SWRL. Our framework offers a constructivist learning approach through the presentation of the LKO´s context to the learner based on domain ontology. Finally, it allows the standardization of the generated learning objects in SCORM and IMS-LD.
  • Keywords
    computer aided instruction; natural language processing; ontologies (artificial intelligence); text analysis; aggregate learning knowledge objects; automatic aggregation; competence-based learning models; constructivist learning; domain ontology; instructional theories; just-enough learning; just-in-time learning; learning resources; natural language processing; on-the-fly generation; ontologies; ontology-based competence model; text mining; Aggregates; Assembly; Content based retrieval; Electronic learning; Natural language processing; Ontologies; Semantic Web; Standardization; Taxonomy; Text mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Learning Technologies, 2007. ICALT 2007. Seventh IEEE International Conference on
  • Conference_Location
    Niigata
  • Print_ISBN
    0-7695-2916-X
  • Type

    conf

  • DOI
    10.1109/ICALT.2007.273
  • Filename
    4281171