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Title: Automatic Generation of Contents Models for Digital Learning Materials
Authors: FLANAGAN, Brendan
MAJUMDAR, Rwitajit
OGATA, Hiroaki  kyouindb  KAKEN_id
Author's alias: 緒方, 広明
Keywords: contents model
text mining
learner knowledge
Issue Date: 24-Nov-2018
Publisher: Asia-Pacific Society for Computers in Education (APSCE)
Journal title: 26th International Conference on Computers in Education Main Conference Proceedings
Start page: 804
End page: 806
Abstract: There has been much research that demonstrates the effectiveness of usingontology to support the construction of knowledge during the learning process. However, the widespread adoption in classrooms of such methods are impeded by the amount of timeand effort that is required to create and maintain an ontology by a domain expert. In thispaper, we propose a method to automatically generate a contents model by analyzinglearning materials with the aim of supporting the construction of knowledge structures. Amap of the keyword nodes is constructed by applying text mining techniques to find theimportant words and phrases and their relations contained within the learning materials. Theprocess retains links between the nodes and the original learning materials, and it istherefore possible to recommend and rank sections that cover a concept contained within thecontents model map.
Description: 26th International Conference on Computers in Education, Metro Manila, Philippines, November 26-30, 2018.
Rights: Copyright 2018 Asia-Pacific Society for Computers in Education. All rights reserved. No part of this book may be reproduced, stored in a retrieval system, transmitted, in any forms or any means, without the prior permission of the Asia-Pacific Society for Computers in Education. Individual papers may be uploaded on to institutional repositories or other academic sites for self-archival purposes.
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