Multiple Affordances of Language Corpora for Data-driven Learning
Editors
| University of Warsaw
| ATILF-CNRS / University of Lorraine
In recent years, corpora have found their way into language instruction, albeit often indirectly, through their role in syllabus and course design and in the production of teaching materials and other resources. An alternative and more innovative use is for teachers and students alike to explore corpus data directly as part of the learning process. This volume addresses this latter application of corpora by providing research insights firmly based in the classroom context and reporting on several state-of-the-art projects around the world where learners have direct access to corpus resources and tools and utilize them to improve their control of the language systems and skills or their professional expertise as translators. Its aim is to present recent advances in data-driven learning, addressing issues involving different types of corpora, for different learner profiles, in different ways for different purposes, and using a variety of different research methodologies and perspectives.
[Studies in Corpus Linguistics, 69] 2015. vii, 312 pp.
Publishing status: Available
© John Benjamins
Table of Contents
1–14
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15–36
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37–62
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Part I. Corpora for language learning
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63–84
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85–108
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109–128
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Part II. Corpora for skills development
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129–154
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155–176
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177–198
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Part III. Corpora for translation training
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199–224
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225–244
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245–266
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267–296
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Notes on contributors
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297–300
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Publically-available corpus tools and resources discussed in the book
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301–304
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Subject Index
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305–310
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Author Index
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311–316
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“Overall, this volume makes a strong contribution to the growing body of research on Data-Driven Learning (DDL)...it could be said that each article, while fililng one gap in the DDL literarure, simultaneously opens another avenue of exploration in the application of DDL to a wider range of language learning contexts. In sum, this volume serves as a substantial step in identifying all the affordances DDL can have for the learners we hope to serve.”
James Garner, Georgia State University, in International Journal of Corpus Linguistics 20(4): 560-569
“The volume can be considered as an essential resource for those already well-versed in DDL [Data Driven Learning]. Perhaps more importantly, however, the volume acts as an accessible guide for educational administrators, teachers and students who are thinking about incorporating a data-driven approach to teaching and learning, and who need the know-how, practical applications and most of all, encouragement to start experimenting with DDL and language corpora more generally.”
Peter R Crosthwaite, University of Hong Kong, on Linguist List 27.1078 (March 2016)
Cited by
Cited by 12 other publications
No author info given
Boulton, Alex & Pascual Pérez-Paredes
Callies, Marcus & Tugba Simsek
Crosthwaite, Peter, Lillian L.C. Wong & Joyce Cheung
Liou, Hsien-Chin & Tzu-Wei Yang
Tyler, Andrea E. & Lourdes Ortega
Wu, Shaoqun, Alannah Fitzgerald, Ian H. Witten & Alex Yu
Wu, Shaoqun, Alannah Fitzgerald, Alex Yu & Ian Witten
Wu, Shaoqun, Liang Li, Ian Witten & Alex Yu
Wu, Shaoqun, Liang Li, Ian H. Witten & Alex Yu
Wu, Shaoqun, Liang Li, Ian H. Witten & Alex Yu
Yunus, Kamariah
This list is based on CrossRef data as of 03 april 2021. Please note that it may not be complete. Sources presented here have been supplied by the respective publishers. Any errors therein should be reported to them.
Subjects
BIC Subject: CJ – Language teaching & learning (other than ELT)
BISAC Subject: FOR000000 – FOREIGN LANGUAGE STUDY / General