Issues and considerations regarding sharable data sets for recommender systems in technology enhanced learning

Hendrik Drachsler*, Toine Bogers, Riina Vuorikari, Katrien Verbert, Erik Duval, Nikos Manouselis, Guenter Beham, Stephanie Lindstaedt, Hermann Stern, Martin Friedrich, Martin Wolpers

*Corresponding author for this work

    Research output: Contribution to journalArticleAcademicpeer-review

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    Abstract

    This paper raises the issue of missing standardised data sets for recommender systems in Technology Enhanced Learning (TEL) that can be used as benchmarks to compare different recommendation approaches. It discusses how suitable data sets could be created according to some initial suggestions, and investigates a number of steps that may be followed in order to develop reference data sets that will be adopted and reused within a scientific community. In addition, policies are discussed that are needed to enhance sharing of data sets by taking into account legal protection rights. Finally, an initial elaboration of a representation and exchange format for sharable TEL data sets is carried out. The paper concludes with future research needs.
    Original languageEnglish
    Pages (from-to)2849-2858
    Number of pages10
    JournalProcedia Computer Science
    Volume1
    Issue number2
    DOIs
    Publication statusPublished - 15 Dec 2010
    Event1st Workshop on Recommender Systems for Technology Enhanced Learning - Barcelona, Spain
    Duration: 29 Sep 201030 Sep 2010
    Conference number: 1
    http://adenu.ia.uned.es/workshops/recsystel2010/

    Keywords

    • STELLAR
    • datatel
    • datasets
    • recommender systems
    • privacy protection
    • pre-processing
    • open data
    • technology enhanced learning
    • data sharing

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