Multiple affordances of language corpora for data-driven learning
by Boulton, Alex Lenko-Szymanska, Agnieszka
Data-driven learning typically involves the use of dedicated concordancers to explore linguistic corpora, which may require significant training if the technology is not to be an obstacle for teacher and learner alike. One possibility is to begin not with corpus or concordancer, but to find parallels with what 'ordinary' users already do. This paper compares the web to a corpus, regular search engines to concordancers, and the techniques used in web searches to data-driven learning. It also exa…
Read More ↓Title Statements
- Full title :Multiple affordances of language corpora for data-driven learning / edited by Agnieszka Lenko-Szymanska, University of Warsaw ; Alex Boulton, ATILF-CNRS / University of Lorraine.
Summary
Data-driven learning typically involves the use of dedicated concordancers to explore linguistic corpora, which may require significant training if the technology is not to be an obstacle for teacher and learner alike. One possibility is to begin not with corpus or concordancer, but to find parallels with what 'ordinary' users already do. This paper compares the web to a corpus, regular search engines to concordancers, and the techniques used in web searches to data-driven learning. It also examines previous studies which exploit web searches in ways not incompatible with a DDL approach.
Read More ↓Edition Statements
- Publication Date:2015
Publication Statements
- Publisher(s):John Benjamins Publishing Company
- Place of Publication:Amsterdam, The Netherlands
- Language:eng
- Publication Date:2015
The Physical Object
- Description:1 online resource (1 recurso electrónico.).
Edition Identifiers
- ISBN:9789027268716, 9027268711
- oclc:on1127487826
- Dewey Decimal:420/.285
Table of Contents
Table of contents; Multiple Affordances of Language Corpora for Data-driven Learning; Editorial page; Title page; LCC data; Table of contents; Editors' acknowledgements; Introduction; References; Data-driven learning and language learning theories; 1. Introduction; 2. Language learning theories and learning style; 3. The noticing hypothesis and DDL; 4. Constructivist learning and DDL; 5. Vygotskyan sociocultural theories and DDL; 6. Learning styles and DDL; 7. Conclusion; Acknowledgements; References; Teaching and language corpora; 1. Introduction; 2. Beginnings; 3. What's happened?
3.1 1975-1985: From manual to computer analysis3.2 1986-1990; 3.3 1991-2000; 3.4 2001-2014; 4. Corpus applications in language teaching: The current situation; 5. Who's using language corpora in 2012: Findings from a survey; 5.1 Respondents; 5.2 Who is using corpora in language teaching, and in what contexts?; 5.3 What tools and resources are they using?; 5.4 Favourite resources; 6. What are the benefits?; 7. Conclusion and future directions?; References; Part I. Corpora for language learning; Learning phraseology from speech corpora; 1. Why spoken phraseology matters.
2. Constructing a speech corpus…
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