Ranking metrics and search guidance for learning object repository

Neil Y. Yen, Timothy K. Shih, Louis R. Chao, Qun Jin

Research output: Contribution to journalArticlepeer-review

59 Scopus citations


In line with the popularity of the Internet and the development of search engine, users request information through web-based services. Although general-purpose searching such as one provided by Google is powerful, searching mechanism for specific purposes could rely on metadata. In distance learning (or e-learning), SCORM provides an efficient metadata definition for learning objects to be searched and shared. To facilitate searching in a federated repository, CORDRA provides a common architecture for discovering and sharing Learning Objects. We followed SCORM and CORDRA specifications to develop a registry system, called the MINE Registry, for storing and sharing 20,738 Learning Objects created in the past five years. As a contribution, we propose the concept of Reusability Tree to represent the relationships among relevant Learning Objects and enhance CORDRA. We further collect relevant information, while users are utilizing Learning Objects, such as citations and time period persisted. The feedbacks from the user community are also considered as critical elements for evaluating significance degree of Learning Objects. Through theses factors, we propose a mechanism to weight and rank Learning Objects in the MINE Registry, in addition to other external learning objects repositories. As a practical contribution, we provide a tool called Search Guider to assist users in finding relevant information in Learning Objects based on individual requirements.

Original languageEnglish
Article number5518759
Pages (from-to)250-264
Number of pages15
JournalIEEE Transactions on Learning Technologies
Issue number3
StatePublished - 2010


  • LOM
  • distance learning.
  • information retrieval
  • learning object repository
  • ranking metrics
  • reusability tree
  • search guidance
  • social feedback


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