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Journal of Information Science and Engineering, Vol. 21 No. 5, pp. 1053-1075 (September 2005)

A Content Management Scheme in a SCORM Compliant Learning Object Repository

Jun-Ming Su, Shian-Shyong Tseng*, Ching-Yao Wang*,
Ying-Chieh Lei*, Yu-Chang Sung* and Wen-Nung Tsai
Department of Computer Science and Information Engineering
*Department of Computer and Information Science
National Chiao Tung University
Hsinchu, 300 Taiwan
E-mail: {jmsu; tsaiwn},
E-mail: {sstseng; cywang; gis90529; is88036}

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.

Keywords: learning object repository (LOR), e-learning, SCORM, content management, XML

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Received July 4, 2004; revised February 1, 2005; accepted March 15, 2005.
Communicated by Robert Lewis.