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Article: Knowledge visualization for self-regulated learning
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TitleKnowledge visualization for self-regulated learning
 
AuthorsWang, M2
Peng, J2
Cheng, B2
Zhou, H2 1
Liu, J2
 
KeywordsE-learning
Knowledge structure
Knowledge visualization
Online learning
Self-regulation
 
Issue Date2011
 
PublisherInternational Forum of Educational Technology & Society. The Journal's web site is located at http://www.ifets.info/
 
CitationEducational Technology And Society, 2011, v. 14 n. 3, p. 28-42 [How to Cite?]
 
AbstractThe Web allows self-regulated learning through interaction with large amounts of learning resources. While enjoying the flexibility of learning, learners may suffer from cognitive overload and conceptual and navigational disorientation when faced with various information resources under disparate topics and complex knowledge structures. This study proposed a knowledge visualization (KV) approach to this problem in an online course. The investigation involved the design, development, and evaluation of an enhanced learning system for the course using the proposed approach. The focus was on visualization of domain knowledge structure and integrating the structure with curriculum design, learning resources, learning assessment, intellectual process, and social learning. Survey and interviews with students demonstrated high user satisfaction and acceptance with the developed system and its functions for KV. These findings lay the foundation for further exploration with the system to determine its impact on reducing cognitive load and improving the learning process. © International Forum of Educational Technology & Society (IFETS).
 
DescriptionFulltext link: http://www.ifets.info/journals/14_3/4.pdf
Special Issue on 'Knowledge Visualization for Learning and Knowledge Management'
 
ISSN1176-3647
 
ReferencesReferences in Scopus
 
DC FieldValue
dc.contributor.authorWang, M
 
dc.contributor.authorPeng, J
 
dc.contributor.authorCheng, B
 
dc.contributor.authorZhou, H
 
dc.contributor.authorLiu, J
 
dc.date.accessioned2011-08-26T14:28:05Z
 
dc.date.available2011-08-26T14:28:05Z
 
dc.date.issued2011
 
dc.description.abstractThe Web allows self-regulated learning through interaction with large amounts of learning resources. While enjoying the flexibility of learning, learners may suffer from cognitive overload and conceptual and navigational disorientation when faced with various information resources under disparate topics and complex knowledge structures. This study proposed a knowledge visualization (KV) approach to this problem in an online course. The investigation involved the design, development, and evaluation of an enhanced learning system for the course using the proposed approach. The focus was on visualization of domain knowledge structure and integrating the structure with curriculum design, learning resources, learning assessment, intellectual process, and social learning. Survey and interviews with students demonstrated high user satisfaction and acceptance with the developed system and its functions for KV. These findings lay the foundation for further exploration with the system to determine its impact on reducing cognitive load and improving the learning process. © International Forum of Educational Technology & Society (IFETS).
 
dc.description.natureLink_to_subscribed_fulltext
 
dc.descriptionFulltext link: http://www.ifets.info/journals/14_3/4.pdf
 
dc.descriptionSpecial Issue on 'Knowledge Visualization for Learning and Knowledge Management'
 
dc.identifier.citationEducational Technology And Society, 2011, v. 14 n. 3, p. 28-42 [How to Cite?]
 
dc.identifier.epage42
 
dc.identifier.hkuros189147
 
dc.identifier.issn1176-3647
 
dc.identifier.issue3
 
dc.identifier.scopuseid_2-s2.0-80053469119
 
dc.identifier.spage28
 
dc.identifier.urihttp://hdl.handle.net/10722/137562
 
dc.identifier.volume14
 
dc.languageeng
 
dc.publisherInternational Forum of Educational Technology & Society. The Journal's web site is located at http://www.ifets.info/
 
dc.publisher.placeNew Zealand
 
dc.relation.ispartofEducational Technology and Society
 
dc.relation.referencesReferences in Scopus
 
dc.subjectE-learning
 
dc.subjectKnowledge structure
 
dc.subjectKnowledge visualization
 
dc.subjectOnline learning
 
dc.subjectSelf-regulation
 
dc.titleKnowledge visualization for self-regulated learning
 
dc.typeArticle
 
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Author Affiliations
  1. Nanjing University of Aeronautics and Astronautics
  2. The University of Hong Kong