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European Conference on Technology Enhanced Learning

EC-TEL 2015: Design for Teaching and Learning in a Networked World pp 240–253Cite as

Automatic Tagging of Learning Objects Based on Their Usage in Web Portals

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9307))

Abstract

Data sets coming from the educational domain often suffer from sparsity. Hence, many learning objects are not accessible by the users as they are not able to find these objects using for example a text-based search. Furthermore, the lack of information makes it difficult or even impossible to recommend such hidden learning resources. In order to address the data sparsity problem, this paper presents a new way to enhance the objects’ semantic representations. This is done by automatically assigning tags and classifications to learning objects offered by educational web portals. This way, we aim to increase the accessibility of the learning objects as well as to enable their recommendation. In contrast to popular tagging approaches that usually base the tagging of a learning object on its content or on the tags already assigned to it, the approach proposed in this paper is solely based on the objects’ usage. Therefore, tags and classifications can be exchanged between the objects and also previously un-tagged objects that do not hold any textual content can be automatically assigned with tags and classifications.

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Notes

  1. 1.

    http://lreforschools.eun.org/web/guest/travel-well.

  2. 2.

    http://lreforschools.eun.org.

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Acknowledgments

This work has been partly supported by the project Open Discovery Space project that is funded by the European Commission’s CIP-ICT Policy Support Program (Project Number: 297229).

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Authors and Affiliations

  1. Fraunhofer Institute for Applied Information Technology (FIT), Schloss Birlinghoven, 53754, Sankt Augustin, Germany

    Katja Niemann

Authors
  1. Katja Niemann
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Correspondence to Katja Niemann .

Editor information

Editors and Affiliations

  1. University of Bath Spa, Bath, UK

    Gráinne Conole

  2. Jožef Stefan Institute, Ljubljana, Slovenia

    Tomaž Klobučar

  3. Technische Universität Darmstadt, Darmstadt, Germany

    Christoph Rensing

  4. Technische Universität Darmstadt, Darmstadt, Germany

    Johannes Konert

  5. IAE Lyon, Université Jean Moulin Lyon 3, Lyon, France

    Elise Lavoué

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Niemann, K. (2015). Automatic Tagging of Learning Objects Based on Their Usage in Web Portals. In: Conole, G., Klobučar, T., Rensing, C., Konert, J., Lavoué, E. (eds) Design for Teaching and Learning in a Networked World. EC-TEL 2015. Lecture Notes in Computer Science(), vol 9307. Springer, Cham. https://doi.org/10.1007/978-3-319-24258-3_18

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  • DOI: https://doi.org/10.1007/978-3-319-24258-3_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24257-6

  • Online ISBN: 978-3-319-24258-3

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