Chapter 1. Research in data-driven learning
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Alex Boulton
Abstract
Data-driven learning (DDL) typically involves language learners consulting corpus data, either directly or via prepared materials, to answer questions about language. The approach has been mooted since the beginning of the modern era of corpus linguistics and has come to be associated with work by Tim Johns who coined the term in print in 1990. Since then, hundreds of studies have attempted to evaluate some aspect of DDL, giving rise to several reviews and syntheses. This paper introduces DDL and discusses the syntheses to date, before analysing a rigorous collection of 351 studies published up to and including 2018. While previous syntheses have evaluated the field, the objective here is to provide an overview of how researchers see DDL across the board, to identify more clearly what DDL actually looks like today, how it has evolved from its early beginnings in the 1980s, and to suggest avenues for future research in underexplored areas.
Abstract
Data-driven learning (DDL) typically involves language learners consulting corpus data, either directly or via prepared materials, to answer questions about language. The approach has been mooted since the beginning of the modern era of corpus linguistics and has come to be associated with work by Tim Johns who coined the term in print in 1990. Since then, hundreds of studies have attempted to evaluate some aspect of DDL, giving rise to several reviews and syntheses. This paper introduces DDL and discusses the syntheses to date, before analysing a rigorous collection of 351 studies published up to and including 2018. While previous syntheses have evaluated the field, the objective here is to provide an overview of how researchers see DDL across the board, to identify more clearly what DDL actually looks like today, how it has evolved from its early beginnings in the 1980s, and to suggest avenues for future research in underexplored areas.
Chapters in this book
- Prelim pages i
- Table of contents vii
- Acknowledgements ix
- Introduction 1
- Chapter 1. Research in data-driven learning 9
- Chapter 2. Data-driven learning, theories of learning and second language acquisition 35
- Chapter 3. Looking back on 25 years of TaLC 57
- Chapter 4. L2 development of - ing clauses 75
- Chapter 5. Collocations in learner English 97
- Chapter 6. Profiling learners through pragmatically and error annotated corpora 121
- Chapter 7. Exploring the impact of data-driven learning in extensive reading 149
- Chapter 8. Data-driven learning 177
- Chapter 9. Scoledit 207
- Chapter 10. CEFR-J × 28 231
- Index 253
Chapters in this book
- Prelim pages i
- Table of contents vii
- Acknowledgements ix
- Introduction 1
- Chapter 1. Research in data-driven learning 9
- Chapter 2. Data-driven learning, theories of learning and second language acquisition 35
- Chapter 3. Looking back on 25 years of TaLC 57
- Chapter 4. L2 development of - ing clauses 75
- Chapter 5. Collocations in learner English 97
- Chapter 6. Profiling learners through pragmatically and error annotated corpora 121
- Chapter 7. Exploring the impact of data-driven learning in extensive reading 149
- Chapter 8. Data-driven learning 177
- Chapter 9. Scoledit 207
- Chapter 10. CEFR-J × 28 231
- Index 253
