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
Link To Document :
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