Beyond Concordance Lines

Corpora in language education

ORCID logoPascual Pérez-Paredes | Universidad de Murcia
ORCID logoGeraldine Mark | Mary Immaculate College, University of Limerick
ISBN 9789027209894 | EUR 99.00 | USD 149.00
ISBN 9789027258496 | EUR 99.00 | USD 149.00
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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
Table of Contents
Cited by

Cited by 2 other publications

Gillings, Mathew, Gerlinde Mautner & Paul Baker
2023. Corpus-Assisted Discourse Studies, DOI logo
Ma, Qing, Ming Ming Chiu, Shanru Lin & Norman B. Mendoza
2023. Teachers’ perceived corpus literacy and their intention to integrate corpora into classroom teaching: A survey study. ReCALL 35:1  pp. 19 ff. DOI logo

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Main BIC Subject

CFX: Computational linguistics

Main BISAC Subject

LAN009000: LANGUAGE ARTS & DISCIPLINES / Linguistics / General
ONIX Metadata
ONIX 2.1
ONIX 3.0
U.S. Library of Congress Control Number:  2021037716 | Marc record