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    Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/4755


    Title: A Content Management Scheme in SCORM Compliant Learning Object Repository
    Authors: Jun-Ming Su;S. S. Tseng;Ching-Yao Wang;Ying-Chieh Lei;Yu-Chang Sung;Wen-Nung Tsai
    Contributors: Department of Information Science and Applications
    Keywords: learning object repository (LOR);e-learning;SCORM;content management XML
    Date: 2005
    Issue Date: 2009-11-30 16:03:25 (UTC+8)
    Publisher: Asia University
    Abstract: With the rapid development of the Internet, e-learning systems have become more
    and more popular. For sharing and reusing teaching materials in different e-learning system,
    the Sharable Content Object Reference Model (SCORM) has become the most
    popular international standard among the existing ones. In an e-learning system, teaching
    materials are usually stored in a database, called the Learning Object Repository (LOR).
    In the LOR, a huge amount of SCORM teaching materials, including associated learning
    objects, will result in management problems in a wired/wireless environment. Recently,
    the SCORM organization has focused on devising ways to efficiently maintain, search,
    and retrieve desired learning objects in LORs for users. This effort is referred to as the
    Content Object Repository Discovery and Resolution Architecture (CORDRA).
    In this paper, we propose a management approach, called the Level-wise Content
    Management Scheme (LCMS), that can be used to efficiently maintain, search, and retrieve
    learning contents from a SCORM compliant LOR. LCMS includes two phases: the
    Construction phase and Search phase. In the former, the content structure of SCORM
    teaching materials (Content Package) is first transformed into a tree-like structure, called
    a Content Tree (CT), to represent each piece of teaching material. Based on Content
    Trees (CTs), the proposed Level-wise Content Clustering Algorithm (LCCAlg) then creates
    a multistage graph showing relationships among learning objects (LOs), e.g., a Directed
    Acyclic Graph (DAG), called the Level-wise Content Clustering Graph (LCCG).
    The LCCAlg determines the relationships among LOs in different teaching materials by
    clustering all of the LOs for each level from bottom to top, according to a similarity
    measure. Moreover, a maintenance strategy is employed to rebuild the LCCG if necessary
    by monitoring the condition of each node within the LCCG. The latter employs the
    LCCG Content Searching Algorithm (LCCG-CSAlg) to traverse the LCCG and retrieve
    desired learning content with both general and specific LOs, according to queries sent by
    users in the wire/wireless environment. Some experiments have been done conducted to
    test the proposed scheme, and the results are reported here.
    Relation: Journal of Information Science and Engineering 21(5):1053-1075
    Appears in Collections:[行動商務與多媒體應用學系] 期刊論文

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