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

Meilin Chen*, John Flowerdew

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

49 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)97-112
Number of pages16
JournalEnglish for Specific Purposes
Early online date3 Feb 2018
Publication statusPublished - Apr 2018

Scopus Subject Areas

  • Language and Linguistics
  • Education
  • Linguistics and Language

User-Defined Keywords

  • Corpus linguistics
  • Data-driven learning
  • DDL
  • Discipline-specific corpora
  • General corpora
  • Research writing


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