Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/102257
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dc.contributor.authorAtapattu Mudiyanselage, T.-
dc.contributor.authorFalkner, K.-
dc.contributor.authorTarmazdi, H.-
dc.contributor.editorBarnes, T.-
dc.contributor.editorChi, M.-
dc.contributor.editorFeng, M.-
dc.date.issued2016-
dc.identifier.citationProceedings of the 9th International Conference on Educational Data Mining, 2016 / Barnes, T., Chi, M., Feng, M. (ed./s), pp.276-281-
dc.identifier.urihttp://hdl.handle.net/2440/102257-
dc.description.abstractWith a goal of better understanding the online discourse within the Massive Open Online Course (MOOC) context, this paper presents an open source visualisation dashboard developed to identify and classify emergent discussion topics (or themes). As an extension to the authors’ previous work in identifying key topics from MOOC discussion contents, this work visualises lecture-related discussions as a graph of relationships between topics and threads. We demonstrate the visualisation using three popular MOOCs offered during 2013. This work facilitates the course staff to locate and navigate the most influential topic clusters as well as the discussions that require intervention by connecting the topics with the corresponding weekly lectures. Further, we demonstrate how our interactive visualisation can be used to explore correlation between discussion topics and other variables such as views, posts, votes, and instructor intervention.-
dc.description.statementofresponsibilityThushari Atapattu, Katrina Falkner, Hamid Tarmazdi-
dc.language.isoen-
dc.publisherIEDMS-
dc.rightsCopyright 2015 © International Educational Data Mining Society (IEDMS)-
dc.source.urihttp://www.educationaldatamining.org/EDM2016/proceedings/paper_109.pdf-
dc.subjectVisualisation; learning analytics; topic model; MOOC; online discourse; discussion forum-
dc.titleTopic-wise classification of MOOC discussions: a visual analytics approach-
dc.typeConference paper-
dc.contributor.conference9th International Conference on Educational Data Mining (EDM) (29 Jun 2016 - 2 Jul 2016 : Raleigh, NC, USA)-
pubs.publication-statusPublished-
dc.identifier.orcidAtapattu Mudiyanselage, T. [0000-0002-0632-4482]-
dc.identifier.orcidFalkner, K. [0000-0003-0309-4332]-
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Computer Science publications

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