Beyond Concordance Lines
Corpora in language education
Editors
In over 30 years of data-driven learning (DDL) research, there has been a growing sophistication in the ways we collect, analyse, and put corpus data to use. This volume takes a three-fold perspective on DDL. It first looks at DDL and its role in informing language learning theory and how it might shed light on the language development process; secondly it addresses how DDL can help us characterise learner language and inform teaching accordingly, and thirdly it showcases practical applications for the use of DDL in classrooms. The contributors to this volume examine a variety of instructional settings and languages across the world. They reflect on theoretical, methodological and classroom implications using both novel and established language learning theories, natural language processing (NLP), longitudinal research designs, and a variety of language learning targets. The present volume is an invitation from some of the leading researchers in DDL to reflect on the research avenues that will define the field in the coming years.
[Studies in Corpus Linguistics, 102] 2021. ix, 255 pp.
Publishing status: Available
© John Benjamins
Table of Contents
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Acknowledgements | pp. ix–1
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IntroductionPascual Pérez-Paredes and Geraldine Mark | pp. 1–8
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Chapter 1. Research in data-driven learningAlex Boulton | pp. 9–34
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Chapter 2. Data-driven learning, theories of learning and second language acquisition: In search of intersectionsAnne O’Keeffe | pp. 35–56
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Chapter 3. Looking back on 25 years of TaLC: In conversation with Profs Mike McCarthy and Tony McEneryMichael McCarthy, Tony McEnery, Geraldine Mark and Pascual Pérez-Paredes | pp. 57–74
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Chapter 4. L2 development of -ing clauses: A longitudinal study of Norwegian learnersHildegunn Dirdal | pp. 75–96
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Chapter 5. Collocations in learner English: A true-longitudinal perspectiveRolf Kreyer | pp. 97–120
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Chapter 6. Profiling learners through pragmatically and error annotated corporaMartin Weisser | pp. 121–148
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Chapter 7. Exploring the impact of data-driven learning in extensive readingGregory Hadley and Hiromi Hadley | pp. 149–176
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Chapter 8. Data-driven learning: Using #LancsBox in academic collocation learningTanjun Liu | pp. 177–206
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Chapter 9. Scoledit : A tool to analyse learner writing and better understand the challenges of language educationClaire Wolfarth, Claude Ponton and Catherine Brissaud | pp. 207–230
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Chapter 10. CEFR-J × 28: Corpus-based multilingual pedagogical resources and e-learning systems for 28 languagesYukio Tono | pp. 231–252
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Index | pp. 253–255
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Subjects
Main BIC Subject
CFX: Computational linguistics
Main BISAC Subject
LAN009000: LANGUAGE ARTS & DISCIPLINES / Linguistics / General