Ranking Metrics and Search Guidance for Learning Object Repository

doi:10.1109/TLT.2010.15

機構典藏 > College of Engineering > Graduate Institute & Department of Computer Science and Information Engineering > Journal Article > Item 987654321/118129

Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/118129

Title:	Ranking Metrics and Search Guidance for Learning Object Repository
Authors:	Yen, Neil Y.;Shih, Timothy K.;Chao, Louis R.;Jin, Qun
Keywords:	CORDRA;LOM;learning object repository;ranking metrics;search guidance;reusability tree;social feedback, information retrieval;distance learning
Date:	2010-07-23
Issue Date:	2020-02-25 12:10:30 (UTC+8)
Publisher:	IEEE
Abstract:	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.
Relation:	IEEE Transactions on Learning Technologies 3(3), p.250-264
DOI:	10.1109/TLT.2010.15
Appears in Collections:	[Graduate Institute & Department of Computer Science and Information Engineering] Journal Article

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