Data Sharing for Learning Analytics - Questioning the Risks and Benefits

Hoel Tore, Jonathan Charles Mason, Weiqin Chen

    Research output: Chapter in Book/Report/Conference proceedingConference Paper published in Proceedingspeer-review

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    Moving learning analytics from the research labs to the classrooms and lecture halls requires data sharing. Data are not any longer gathered in controlled settings but have to be combined from different sources within the institution and maybe beyond. This scaling up of learning analytics raises a host of questions on behalf of the data subjects providing requirements for design of new solutions and practices. This paper analyses a corpus of more than 200 questions gathered by a European learning analytics support action and explores how these questions could be used to understand the problem space of data sharing and the solution space to be carved out by research and development within this emerging field of learning technologies. The paper concludes the discussion on data sharing and big data for education is still at an early stage, where conceptual issues dominate and there is a long way to go before one can move towards solving issues of technical development and implementation.
    Original languageEnglish
    Title of host publicationWorkshop Proceedings of the 23rd International Conference on Computers in Education ICCE 2015
    EditorsHiroaki Ogata, Weiqin Chen, Siu Cheng Kong, Feiyue Qiu
    Place of PublicationJapan
    PublisherAsia Pacific Society for Computers in Education (APSCE)
    Number of pages10
    ISBN (Print)978-4-9908014-7-2
    Publication statusPublished - 2015
    EventInternational Conference on Computers in Education (ICCE 2015) - Hangzhou China, Hangzhou, China
    Duration: 30 Nov 20154 Dec 2015
    Conference number: 2015 (23rd)


    ConferenceInternational Conference on Computers in Education (ICCE 2015)
    Abbreviated titleICCE


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