Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/37252
Full metadata record
DC FieldValueLanguage
dc.contributor.authorAinley, Janet M.-
dc.contributor.authorGould, R.-
dc.contributor.authorPratt, D.-
dc.date.accessioned2016-04-12T08:19:22Z-
dc.date.available2016-04-12T08:19:22Z-
dc.date.issued2015-02-01-
dc.identifier.citationEducational Studies In Mathematics, 2015, 88 (3), pp. 405-412 (8)en
dc.identifier.issn0013-1954-
dc.identifier.urihttp://link.springer.com/article/10.1007%2Fs10649-015-9592-4en
dc.identifier.urihttp://hdl.handle.net/2381/37252-
dc.description.abstractThis paper is in the form of a reflective discussion of the collection of papers in this Special Issue on Statistical reasoning: learning to reason from samples drawing on deliberations arising at the Seventh International Collaboration for Research on Statistical Reasoning, Thinking, and Literacy (SRTL7). It is an important part of the structure of the academic work of SRTL community that at the end of each conference, a small group of discussants are given the space to present their reflections and reactions with the aim of raising questions and issues which may carry forward into the future work of the community of researchers. Traditionally, they have the freedom to choose the perspectives from which they do this, and this paper has been developed in the same spirit. At SRTL7, the authors of this paper addressed issues on which they have been working for some time, namely, task design and the emergence of big data and are now able to offer a commentary from these two perspectives on what might be learnt from the papers in this special issue.en
dc.language.isoenen
dc.publisherSpringer Netherlandsen
dc.rightsCopyright © Springer Science+Business Media Dordrecht 2015. The file associated with this record is distributed under the Creative Commons “Attribution Non-Commercial No Derivatives” licence, further details of which can be found via the following link: http://creativecommons.org/licenses/by-nc-nd/4.0/en
dc.subjectSocial Sciencesen
dc.subjectEducation & Educational Researchen
dc.subjectTask designen
dc.subjectBig dataen
dc.subjectSamplesen
dc.subjectSTATISTICSen
dc.titleLearning to reason from samples: commentary from the perspectives of task design and the emergence of "big data"en
dc.typeJournal Articleen
dc.identifier.doi10.1007/s10649-015-9592-4-
dc.identifier.eissn1573-0816-
dc.description.statusPeer-revieweden
dc.description.versionPost-printen
dc.type.subtypeArticle;Journal-
pubs.organisational-group/Organisationen
pubs.organisational-group/Organisation/COLLEGE OF SOCIAL SCIENCES, ARTS AND HUMANITIESen
pubs.organisational-group/Organisation/COLLEGE OF SOCIAL SCIENCES, ARTS AND HUMANITIES/School of Educationen
Appears in Collections:Published Articles, School of Education

Files in This Item:
File Description SizeFormat 
Learning to Reason from Samples Commentary.docxPost-review (final submitted)44.8 kBUnknownView/Open
Learning to Reason from Samples Commentary.pdfPost-review (final submitted)249.93 kBAdobe PDFView/Open


Items in LRA are protected by copyright, with all rights reserved, unless otherwise indicated.