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A SCORM-Based Caching Strategy for Supporting Ubiquitous Learning Environment

  • Conference paper
Autonomic and Trusted Computing (ATC 2006)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 4158))

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Abstract

With respect to the diverseness of learning devices and the different conditions of the internet connection availability, users might confront with some inevitable problems in traditional distance learning environment. The learning activities are always interfered while the network connection is failed. Furthermore, the learning contents become more and more miscellaneous with on-line multimedia presentations, and it is necessary for learners to wait for the learning resources to be downloaded from the remote learning server. In this paper, we propose a solution, called Caching Strategy, to solve those issues under the ubiquitous learning scope. According to some specific factors, we aim to provide the most needed learning resources for learners on the mobile learning devices even if the internet connection is not available intermittently. With our proposed methods, the waiting time of learning contents delivery can be reduced as well to smooth the learning activities online. In order to increase the efficiency of the strategy, we carefully examine some specific factors about the learning sequencing defined in the Sharable Content Object Reference Model (SCORM). After applying this strategy to distance learning system, the efficient ubiquitous learning will be easier to come true.

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© 2006 Springer-Verlag Berlin Heidelberg

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Sie, YL., Wang, TH., Chang, HP., Chang, SN., Shih, T.K. (2006). A SCORM-Based Caching Strategy for Supporting Ubiquitous Learning Environment. In: Yang, L.T., Jin, H., Ma, J., Ungerer, T. (eds) Autonomic and Trusted Computing. ATC 2006. Lecture Notes in Computer Science, vol 4158. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11839569_54

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  • DOI: https://doi.org/10.1007/11839569_54

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-38619-3

  • Online ISBN: 978-3-540-38622-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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