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Introducing data-driven learning to PhD students for research writing purposes: A territory-wide project in Hong Kong

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Introducing data-driven learning to PhD students for research writing purposes: A territory-wide project in Hong Kong. / Chen, Meilin; Flowerdew, John.
In: English for Specific Purposes, Vol. 50, 04.2018, p. 97-112.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Chen, M & Flowerdew, J 2018, 'Introducing data-driven learning to PhD students for research writing purposes: A territory-wide project in Hong Kong', English for Specific Purposes, vol. 50, pp. 97-112. https://doi.org/10.1016/j.esp.2017.11.004

APA

Chen, M., & Flowerdew, J. (2018). Introducing data-driven learning to PhD students for research writing purposes: A territory-wide project in Hong Kong. English for Specific Purposes, 50, 97-112. https://doi.org/10.1016/j.esp.2017.11.004

Vancouver

Chen M, Flowerdew J. Introducing data-driven learning to PhD students for research writing purposes: A territory-wide project in Hong Kong. English for Specific Purposes. 2018 Apr;50:97-112. Epub 2018 Feb 3. doi: 10.1016/j.esp.2017.11.004

Author

Chen, Meilin ; Flowerdew, John. / Introducing data-driven learning to PhD students for research writing purposes : A territory-wide project in Hong Kong. In: English for Specific Purposes. 2018 ; Vol. 50. pp. 97-112.

Bibtex

@article{e98c2f02fcef4b0ea2caca88241c9261,
title = "Introducing data-driven learning to PhD students for research writing purposes: A territory-wide project in Hong Kong",
abstract = "This paper reports on a project aimed at disseminating the data-driven learning (DDL) approach to research writing among PhD students in Hong Kong universities. A 3.5-h workshop was offered for over 20 sessions across six universities addressing 473 postgraduate research students, accounting for 6.7% of the whole research graduate student population in Hong Kong. Students were first introduced to the free online corpus, BNCweb, which can help to solve lexico-grammatical problems encountered during research writing. They were then given access to teacher-built discipline-specific corpora with the concordancing tool AntConc. Through hands-on activities and interactive discussion students were able to compare discourse strategies employed across different disciplines and identify their linguistic realisations. Participants were finally guided through the process of building a corpus of their own, thereby catering for their personal needs. The self-selected participants' evaluation of the workshop was highly positive and they showed evident enthusiasm for this new approach. Their suggestions for improvement are also discussed. The description of the workshop programme and feedback from learners may provide useful insights for DDL practitioners who wish to spread this approach in their own institutions.",
keywords = "Corpus linguistics, Data-driven learning, DDL, Discipline-specific corpora, General corpora, Research writing",
author = "Meilin Chen and John Flowerdew",
year = "2018",
month = apr,
doi = "10.1016/j.esp.2017.11.004",
language = "English",
volume = "50",
pages = "97--112",
journal = "English for Specific Purposes",
issn = "0889-4906",
publisher = "Elsevier BV",

}

RIS

TY - JOUR

T1 - Introducing data-driven learning to PhD students for research writing purposes

T2 - A territory-wide project in Hong Kong

AU - Chen, Meilin

AU - Flowerdew, John

PY - 2018/4

Y1 - 2018/4

N2 - This paper reports on a project aimed at disseminating the data-driven learning (DDL) approach to research writing among PhD students in Hong Kong universities. A 3.5-h workshop was offered for over 20 sessions across six universities addressing 473 postgraduate research students, accounting for 6.7% of the whole research graduate student population in Hong Kong. Students were first introduced to the free online corpus, BNCweb, which can help to solve lexico-grammatical problems encountered during research writing. They were then given access to teacher-built discipline-specific corpora with the concordancing tool AntConc. Through hands-on activities and interactive discussion students were able to compare discourse strategies employed across different disciplines and identify their linguistic realisations. Participants were finally guided through the process of building a corpus of their own, thereby catering for their personal needs. The self-selected participants' evaluation of the workshop was highly positive and they showed evident enthusiasm for this new approach. Their suggestions for improvement are also discussed. The description of the workshop programme and feedback from learners may provide useful insights for DDL practitioners who wish to spread this approach in their own institutions.

AB - This paper reports on a project aimed at disseminating the data-driven learning (DDL) approach to research writing among PhD students in Hong Kong universities. A 3.5-h workshop was offered for over 20 sessions across six universities addressing 473 postgraduate research students, accounting for 6.7% of the whole research graduate student population in Hong Kong. Students were first introduced to the free online corpus, BNCweb, which can help to solve lexico-grammatical problems encountered during research writing. They were then given access to teacher-built discipline-specific corpora with the concordancing tool AntConc. Through hands-on activities and interactive discussion students were able to compare discourse strategies employed across different disciplines and identify their linguistic realisations. Participants were finally guided through the process of building a corpus of their own, thereby catering for their personal needs. The self-selected participants' evaluation of the workshop was highly positive and they showed evident enthusiasm for this new approach. Their suggestions for improvement are also discussed. The description of the workshop programme and feedback from learners may provide useful insights for DDL practitioners who wish to spread this approach in their own institutions.

KW - Corpus linguistics

KW - Data-driven learning

KW - DDL

KW - Discipline-specific corpora

KW - General corpora

KW - Research writing

U2 - 10.1016/j.esp.2017.11.004

DO - 10.1016/j.esp.2017.11.004

M3 - Journal article

VL - 50

SP - 97

EP - 112

JO - English for Specific Purposes

JF - English for Specific Purposes

SN - 0889-4906

ER -