Automatic learning sequence template generation for educational reuse

Neil Y. Yen, Qun Jin, Timothy K. Shih, Li Chieh Lin

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Sharing resources and information on Internet has become an important activity for education. The learning object repository has been developed to achieve efficient management of learning objects. Following usage experiences of learning objects collected in the past, this study concentrates on investigating implicit information between learning objects. We define a social structure for identifying relationship between learning objects and define a set of metrics to evaluate the interdependency. The structure identifies usage experiences and can be graphed in terms of implicit and explicit relations among learning objects. As a practical contribution, an adaptive algorithm is proposed to mine the social structure. The algorithm generates adaptive learning sequence by identifying possible interactive search input and assists them in completing self-paced learning situation.

Original languageEnglish
Title of host publicationProceedings - 2011 IEEE International Conference on Granular Computing, GrC 2011
Pages773-778
Number of pages6
DOIs
StatePublished - 2011
Event2011 IEEE International Conference on Granular Computing, GrC 2011 - Kaohsiung, Taiwan
Duration: 8 Nov 201110 Nov 2011

Publication series

NameProceedings - 2011 IEEE International Conference on Granular Computing, GrC 2011

Conference

Conference2011 IEEE International Conference on Granular Computing, GrC 2011
Country/TerritoryTaiwan
CityKaohsiung
Period8/11/1110/11/11

Keywords

  • automatic mechanism
  • learning object
  • learning sequence
  • reusability
  • social network

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