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Developing Personalized Knowledge Navigation Service for Students Self-Learning based on Interpretive Structural Modeling
Sixth IEEE International Conference on Advanced Learning Technologies (ICALT'06)
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This paper designs a personalized navigation service based on the student cognitive levels. The personalized navigation service takes the interpretive structural modeling to generate concept navigation matrix by using the student cognitive background matrix (retrieved from tests and questionnaire) and the concept relation matrix (retrieved from textbooks). According to the knowledge structure and the concept navigation matrix, the service can provide different students their own knowledge navigation maps.
doi:10.1109/icalt.2006.1652463
dblp:conf/icalt/WuLCCL06
fatcat:2cap75gycfhndc7pb2gkb6jg5q