Data-driven learning: Using #LancsBox in academic collocation learning

Tanjun Liu*

*Corresponding author for this work

Research output: Chapter in Book or Report/Conference proceedingChapterpeer-review

3 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationBeyond Concordance Lines. Corpora in language education
EditorsPascual Perez-Paredes, Geraldine Mark
PublisherJohn Benjamins Publishing Company
Pages177-206
Number of pages30
ISBN (Electronic)9789027258496
DOIs
Publication statusPublished - 2021

Publication series

NameStudies in Corpus Linguistics
Volume102
ISSN (Print)1388-0373

Keywords

  • #LancsBox
  • Collocation graphs
  • Collocations
  • Data-driven learning

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