Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/23239
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dc.contributor.authorPerrotta, Carlo-
dc.contributor.authorWilliamson, Ben-
dc.date.accessioned2018-04-07T02:37:42Z-
dc.date.available2018-04-07T02:37:42Z-
dc.date.issued2018-
dc.identifier.urihttp://hdl.handle.net/1893/23239-
dc.description.abstractThis paper argues that methods used for the classification and measurement of online education are not neutral and objective, but involved in the creation of the educational realities they claim to measure. In particular, the paper draws on material semiotics to examine cluster analysis as a ‘performative device’ that, to a significant extent, creates the educational entities it claims to objectively represent through the emerging body of knowledge of Learning Analytics (LA). It also offers a more critical and political reading of the algorithmic assemblages of LA, of which cluster analysis is a part. Our argument is that if we want to understand how algorithmic processes and techniques like cluster analysis function as performative devices, then we need methodological sensibilities that consider critically both their political dimensions and their technical-mathematical mechanisms. The implications for critical research in educational technology are discussed.en_UK
dc.language.isoen-
dc.publisherTaylor and Francis-
dc.relationPerrotta C & Williamson B (2018) The social life of Learning Analytics: cluster analysis and the 'performance' of algorithmic education, Learning, Media and Technology, 43 (1), pp. 3-16.-
dc.rights© 2016 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.-
dc.subjectAlgorithmsen_UK
dc.subjectcluster analysisen_UK
dc.subjectLearning Analyticsen_UK
dc.subjectmethodsen_UK
dc.subjectperformativityen_UK
dc.titleThe social life of Learning Analytics: cluster analysis and the 'performance' of algorithmic educationen_UK
dc.typeJournal Articleen_UK
dc.identifier.doihttp://dx.doi.org/10.1080/17439884.2016.1182927-
dc.citation.jtitleLearning, Media and Technology-
dc.citation.issn1743-9884-
dc.citation.volume43-
dc.citation.issue1-
dc.citation.spage3-
dc.citation.epage16-
dc.citation.publicationstatusPublished-
dc.citation.peerreviewedRefereed-
dc.type.statusPublisher version (final published refereed version)-
dc.author.emailben.williamson@stir.ac.uk-
dc.citation.date17/05/2016-
dc.contributor.affiliationUniversity of Leeds-
dc.contributor.affiliationEducation-
dc.identifier.isi000427058300002-
Appears in Collections:Faculty of Social Sciences Journal Articles



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