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Chapter 8. Data-driven learning

Using #LancsBox in academic collocation learning
  • Tanjun Liu
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Beyond Concordance Lines
This chapter is in the book Beyond Concordance Lines

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.

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.

Chapters in this book

  1. Prelim pages i
  2. Table of contents vii
  3. Acknowledgements ix
  4. Introduction 1
  5. Chapter 1. Research in data-driven learning 9
  6. Chapter 2. Data-driven learning, theories of learning and second language acquisition 35
  7. Chapter 3. Looking back on 25 years of TaLC 57
  8. Chapter 4. L2 development of - ing clauses 75
  9. Chapter 5. Collocations in learner English 97
  10. Chapter 6. Profiling learners through pragmatically and error annotated corpora 121
  11. Chapter 7. Exploring the impact of data-driven learning in extensive reading 149
  12. Chapter 8. Data-driven learning 177
  13. Chapter 9. Scoledit 207
  14. Chapter 10. CEFR-J × 28 231
  15. Index 253
https://doi.org/10.1075/scl.102.08liu

Chapters in this book

  1. Prelim pages i
  2. Table of contents vii
  3. Acknowledgements ix
  4. Introduction 1
  5. Chapter 1. Research in data-driven learning 9
  6. Chapter 2. Data-driven learning, theories of learning and second language acquisition 35
  7. Chapter 3. Looking back on 25 years of TaLC 57
  8. Chapter 4. L2 development of - ing clauses 75
  9. Chapter 5. Collocations in learner English 97
  10. Chapter 6. Profiling learners through pragmatically and error annotated corpora 121
  11. Chapter 7. Exploring the impact of data-driven learning in extensive reading 149
  12. Chapter 8. Data-driven learning 177
  13. Chapter 9. Scoledit 207
  14. Chapter 10. CEFR-J × 28 231
  15. Index 253
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