A new paradigm of ranking & searching in learning object repository

Neil Y. Yen, Timothy K. Shih, Qun Jin

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

5 Scopus citations

Abstract

With the development of internet and search engine, users are thought to obtain everything through corresponding web services. Although general purpose searching such as one provided by Google is powerful, searching mechanism for different purposes has to rely on specific metadata. We followed SCORM and CORDRA to develop a registry system named MINE Registry for storing and managing the learning objects. As a contribution, we propose the concept of "Reusability Tree" to represent the relationships among relevant Learning Objects and to enhance CORDRA. We further collect relevant information while users are utilizing Learning Objects, such as citations and time period persisted. The feedbacks from community users are also considered as critical elements for evaluating significance degree of Learning Objects. Through these factors, we propose a mechanism to weight and rank Learning Objects in the MINE Registry, in addition to other external learning objects repositories.

Original languageEnglish
Title of host publicationMTDL'10 - Proceedings of the 2010 ACM Workshop on Multimedia Technologies for Distance Leaning, Co-located with ACM Multimedia 2010
Pages1-6
Number of pages6
DOIs
StatePublished - 2010
Event2nd ACM International Workshop on Multimedia Technologies for Distance Leaning, MTDL 2010, Co-located with ACM Multimedia 2010 - Firenze, Italy
Duration: 29 Oct 201029 Oct 2010

Publication series

NameMTDL'10 - Proceedings of the 2010 ACM Workshop on Multimedia Technologies for Distance Leaning, Co-located with ACM Multimedia 2010

Conference

Conference2nd ACM International Workshop on Multimedia Technologies for Distance Leaning, MTDL 2010, Co-located with ACM Multimedia 2010
Country/TerritoryItaly
CityFirenze
Period29/10/1029/10/10

Keywords

  • Distance learning
  • Information retrieval
  • Learning object repository
  • Ranking metrics
  • Reusability tree
  • Social feedback

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