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Enhancing Educational-Material Retrieval Using Authored-Lesson Metadata

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String Processing and Information Retrieval (SPIRE 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4726))

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Abstract

Many authors believe that in order to achieve coherence and flexibility at the same time in multimedia-based learning units, it is highly recommendable to structure the different components as a graph. In a lesson graph, educational resources are encapsulated into learning objects (LO) along with their respective metadata and are interconnected through different kind of rhetorical and semantical relationships. The LOs of these graphs are stored within repositories, where their metadata are used to ease their retrieval. In this paper we propose to integrate the processes of searching LOs and editing the lesson graph. This new framework extends traditional keyword and metadata search to take advantage of the information stored implicitly in the lesson graph structure, making LOs retrieval more effective and the expression of queries more intuitive. The retrieval of the learning material consists of two processes: (1) The user first defines the topological location of a required piece of educational material within the lesson graph, this is, its relationships with other pieces. (2) Then, the user issues a traditional keyword query, which is processed by an IR system modified to take the graph structure into account. Experiments show the advantages of this approach.

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Nivio Ziviani Ricardo Baeza-Yates

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Motelet, O., Piwowarski, B., Dupret, G., Pino, J.A., Baloian, N. (2007). Enhancing Educational-Material Retrieval Using Authored-Lesson Metadata. In: Ziviani, N., Baeza-Yates, R. (eds) String Processing and Information Retrieval. SPIRE 2007. Lecture Notes in Computer Science, vol 4726. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75530-2_23

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  • DOI: https://doi.org/10.1007/978-3-540-75530-2_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-75529-6

  • Online ISBN: 978-3-540-75530-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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