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Beyond Concordance Lines: Corpora in language education
Edited by Pascual Pérez-Paredes and Geraldine Mark
[Studies in Corpus Linguistics 102] 2021
► pp. 177–206

Chapter 8
Data-driven learning

Using #LancsBox in academic collocation learning

ORCID logo | Xi’an Jiaotong-Liverpool University
This chapter investigates the effect of data-driven learning (DDL) by comparing the use of a new corpus tool, #LancsBox, with the use of a corpus-based collocations dictionary for academic collocation learning. Learners in the study improved their collocational knowledge by using #LancsBox, although not significantly. No improvement was found through consulting the collocations dictionary. The majority of learners believed that direct corpus consultation using concordance lines and collocation graphs facilitated their collocation learning, whereas learners in the dictionary group considered the use of a dictionary to be more beneficial for writing than learning collocations. Interestingly, learners from both groups reported that they would continue using the assigned tools in future language learning and teaching.
Keywords: data-driven learning, collocations, #LancsBox, collocation graphs
Article outline
  • Introduction
  • Academic collocations
    • Collocations for L2 learners
    • Teaching collocations
  • DDL and collocation learning
  • Rationale and research aims
  • Research design
    • Participants
    • Corpus-based tools
      • #LancsBox and the BAWE corpus
      • Oxford Collocations Dictionary
      • Collocation test
    • Procedure
      • Before the treatment
      • During the treatment
      • After the treatment
  • Results
    • RQ1: Do Chinese learners of English improve their academic collocation knowledge through DDL compared with the use of a corpus-based dictionary?
    • RQ2: Learners’ perceptions of using DDL and the use of a corpus-based dictionary for collocation learning
  • Discussion
  • Conclusion
  • Acknowledgements
  • Notes
  • References
  • Appendix
Published online: 22 December 2021
DOI logo
https://doi.org/10.1075/scl.102.08liu
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