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Article: Characterising postgraduate students' corpus query and usage patterns for disciplinary data-driven learning

TitleCharacterising postgraduate students' corpus query and usage patterns for disciplinary data-driven learning
Authors
KeywordsCorpora
Data-driven learning
Disciplinary writing
English for academic purposes
L2 writing
Issue Date2019
PublisherCambridge University Press. The Journal's web site is located at http://journals.cambridge.org/action/displayJournal?jid=REC
Citation
ReCall, 2019, v. 31 n. 3, p. 255-275 How to Cite?
AbstractData-driven learning (DDL; Johns, 1991), involving students' hands-on use of corpora for self-guided language learning, is a methodology now increasingly used in many tertiary contexts to enhance the teaching of disciplinary postgraduate thesis writing. However, there are still few studies tracking students' actual engagement with corpora for DDL. This mixed-methods study reports on the tracking of students' corpus use via a purpose-built corpus query and data visualisation platform integrated into a large postgraduate disciplinary thesis writing program at a university in Hong Kong. Data on corpus usage history (e.g. times of access, duration of use), query syntax (e.g. query lexis/phraseology and use of wildcards and part-of-speech tags), query function (e.g. frequency lists/distribution, concordance sorting and collocation) and query filters (e.g. searches by faculty, discipline, or thesis section) were collected from 327 students spanning over 11,000 individual corpus queries. The results show significant interdisciplinary and inter-/intra-user trends and variation in the use of particular corpus functions and query syntax adopted by corpus users. Students varied in the type of knowledge (e.g. domain-specific, language-specific) they were accessing, and frequently went beyond the exemplars of the DDL course materials to generate unique queries under their own initiative. Qualitative case study data from three corpus users' activity logs also show distinctive individual corpus engagement by query frequency and function. These data provide a clearer insight into what students actually do during DDL and the different directions and trajectories that individual users take as a result of DDL. All accompanying DDL tasks are also included as supplementary materials. © European Association for Computer Assisted Language Learning 2019.
Persistent Identifierhttp://hdl.handle.net/10722/275493
ISSN
2017 Impact Factor: 2.206
2015 SCImago Journal Rankings: 1.412
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorCrosthwaite, P-
dc.contributor.authorWong, LLC-
dc.contributor.authorCheung, J-
dc.date.accessioned2019-09-10T02:43:38Z-
dc.date.available2019-09-10T02:43:38Z-
dc.date.issued2019-
dc.identifier.citationReCall, 2019, v. 31 n. 3, p. 255-275-
dc.identifier.issn0958-3440-
dc.identifier.urihttp://hdl.handle.net/10722/275493-
dc.description.abstractData-driven learning (DDL; Johns, 1991), involving students' hands-on use of corpora for self-guided language learning, is a methodology now increasingly used in many tertiary contexts to enhance the teaching of disciplinary postgraduate thesis writing. However, there are still few studies tracking students' actual engagement with corpora for DDL. This mixed-methods study reports on the tracking of students' corpus use via a purpose-built corpus query and data visualisation platform integrated into a large postgraduate disciplinary thesis writing program at a university in Hong Kong. Data on corpus usage history (e.g. times of access, duration of use), query syntax (e.g. query lexis/phraseology and use of wildcards and part-of-speech tags), query function (e.g. frequency lists/distribution, concordance sorting and collocation) and query filters (e.g. searches by faculty, discipline, or thesis section) were collected from 327 students spanning over 11,000 individual corpus queries. The results show significant interdisciplinary and inter-/intra-user trends and variation in the use of particular corpus functions and query syntax adopted by corpus users. Students varied in the type of knowledge (e.g. domain-specific, language-specific) they were accessing, and frequently went beyond the exemplars of the DDL course materials to generate unique queries under their own initiative. Qualitative case study data from three corpus users' activity logs also show distinctive individual corpus engagement by query frequency and function. These data provide a clearer insight into what students actually do during DDL and the different directions and trajectories that individual users take as a result of DDL. All accompanying DDL tasks are also included as supplementary materials. © European Association for Computer Assisted Language Learning 2019.-
dc.languageeng-
dc.publisherCambridge University Press. The Journal's web site is located at http://journals.cambridge.org/action/displayJournal?jid=REC-
dc.relation.ispartofReCall-
dc.rightsReCall. Copyright © Cambridge University Press.-
dc.rightsThis article has been published in a revised form in [Journal] [http://doi.org/XXX]. This version is free to view and download for private research and study only. Not for re-distribution, re-sale or use in derivative works. © copyright holder.-
dc.subjectCorpora-
dc.subjectData-driven learning-
dc.subjectDisciplinary writing-
dc.subjectEnglish for academic purposes-
dc.subjectL2 writing-
dc.titleCharacterising postgraduate students' corpus query and usage patterns for disciplinary data-driven learning-
dc.typeArticle-
dc.identifier.emailWong, LLC: llcwong@hku.hk-
dc.identifier.doi10.1017/S0958344019000077-
dc.identifier.scopuseid_2-s2.0-85067419817-
dc.identifier.hkuros304802-
dc.identifier.volume31-
dc.identifier.issue3-
dc.identifier.spage255-
dc.identifier.epage275-
dc.identifier.isiWOS:000481819200004-
dc.publisher.placeUnited Kingdom-

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