Academic Writing with Corpora

A Resource Book for Data-Driven Learning

Tatyana Karpenko-Seccombe

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English

Routledge
20 December 2024

linguistics; ELT: English for technical & scientific purposes; History; Media studies; Press & journalism

Academic Writing with Corpora offers an accessible guide to using corpora in academic writing successfully and productively. Addressing the challenges faced by teachers of English for academic purposes when explaining to their students how to write 'naturally', this book places an emphasis on learning from expert and proficient writing.

Revised and updated throughout, this book:

• takes a highly practical approach, now with new tasks and the latest software features;

• fosters autonomous learning by demonstrating how to solve everyday difficulties in word choice and grammar;

• places a special emphasis on the use of corpora to explore rhetorical strategies;

• introduces the reader to five corpus tools (SkELL, Lextutor, COCA, MICUSP and AntConc);

• offers a new section on DIY corpora, including basic principles and a step-by-step guide to building a corpus, with an introduction to AntConc;

• now includes a ‘Further reading’ section for each chapter.

This resource book is for teachers looking to introduce data-driven learning into the classroom without spending excessive time on researching corpora and preparing tasks. It is also for second-language academic writers – university students and researchers – who are motivated to improve their writing and to learn from proficient and expert writing in their area.

By: Tatyana Karpenko-Seccombe
Imprint: Routledge
Country of Publication: United Kingdom
Edition: 2nd edition
Dimensions: Height: 234mm, Width: 156mm,
Weight: 420g
ISBN: 9781032731865
ISBN 10: 1032731869
Pages: 204
Publication Date: 20 December 2024
Audience: Professional and scholarly , College/higher education , Undergraduate , Primary
Format: Paperback
Publisher's Status: Active

Tatyana Karpenko-Seccombe is an independent scholar who for many years taught English for academic purposes at the University of Huddersfield, UK, using corpus methods.