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Using Taxonomic Indexing Trees to Efficiently Retrieve SCORM-Compliant Documents in e-Learning Grids

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Journal of Educational Technology & Society Volume 11, Number 2, ISSN 1176-3647 e-ISSN 1176-3647


With the flourishing development of e-Learning, more and more SCORM-compliant teaching materials are developed by institutes and individuals in different sites. In addition, the e-Learning grid is emerging as an infrastructure to enhance traditional e-Learning systems. Therefore, information retrieval schemes supporting SCORM-compliant documents on grid environments are gaining its importance. To minimize the query processing time and content transmission time, our idea is to use a bottom-up approach to reorganize documents in these sites based on their metadata, and to manage these contents in a centralized manner. In this paper, we design an indexing structure named Taxonomic Indexing Trees (TI-trees). A TI-tree is a taxonomic structure and has two novel features: 1) reorganizing documents according to the Classification metadata such that queries by classes can be processed efficiently and 2) indexing dispersedly stored documents in a centralized manner which is suitable for common grid middleware. This approach is composed of a Construction phase and a Search phase. In the former, a local TI-tree is built from each Learning Object Repository. Then, all local TI-trees are merged into a global TI-tree. In the latter, a Grid Portal processes queries and presents results with estimated transmission time to users. Experimental results show that the proposed approach can efficiently retrieve SCORM-compliant documents with good scalability. (Contains 4 tables and 14 figures.)


Shih, W.C., Tseng, S.S. & Yang, C.T. (2008). Using Taxonomic Indexing Trees to Efficiently Retrieve SCORM-Compliant Documents in e-Learning Grids. Journal of Educational Technology & Society, 11(2), 206-226. Retrieved October 21, 2020 from .

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