Developing an Evaluation Framework of Quality Indicators for Learning Analytics

Maren Scheffel, Hendrik Drachsler, Marcus Specht

    Research output: Chapter in Book/Report/Conference proceedingConference Article in proceedingAcademicpeer-review

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    Abstract

    This paper presents results from the continuous process of developing an evaluation framework of quality indicators for learning analytics (LA). Building on a previous study, a group concept mapping approach that uses multidimensional scaling and hierarchical clustering, the study presented here applies the framework to a collection of LA tools in order to evaluate the framework. Using the quantitative and qualitative results of this study, the rst version of the framework was revisited so as to allow work towards an improved version of the evaluation framework of quality indicators for LA.
    Original languageEnglish
    Title of host publicationProceedings of the Fifth International Conference on Learning Analytics And Knowledge
    Place of PublicationNew York, NY, USA
    PublisherAssociation for Computing Machinery (ACM)
    Pages16-20
    Number of pages5
    ISBN (Print)978-1-4503-3417-4
    DOIs
    Publication statusPublished - 2015
    EventThe 5th International Learning Analytics and Knowledge (LAK) Conference: Scaling Up: Big Data to Big Impact - Marist College, Poughkeepsie, United States
    Duration: 16 Mar 201520 Mar 2015
    Conference number: 5
    http://lak15.solaresearch.org/home

    Conference

    ConferenceThe 5th International Learning Analytics and Knowledge (LAK) Conference
    Abbreviated titleLAK'15
    Country/TerritoryUnited States
    CityPoughkeepsie
    Period16/03/1520/03/15
    Internet address

    Keywords

    • evaluation framework
    • learning analytics
    • quality indicators
    • group concept mapping
    • assessment of learning analytics tools

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