Learners and users – Who do we want corpus data from?
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Anna Mauranen
Abstract
Learner corpora and lingua franca corpora differ in important ways in social and interactional aspects. Yet in the cognitive domain of language processing they have much in common, as reflected in lexicogrammatical and phraseological features. They can therefore be seen as complementary takes on second language research. We can expect advanced second/foreign language learners to show similar linguistic features to lingua franca speakers, and supporting evidence is accumulating. This paper suggests that although some features in an English as a lingua franca (ELF) corpus can be explained on cognitive principles similar to those likely to operate in learners, such as economy of effort, others cannot. For instance the common use of not quite native-like phraseological units requires a use-based rather than learning-based explanation. On the whole, the major differences between learner and ELF corpora make it necessary to keep them separate. At the same time, both can contribute results of considerable mutual interest.
Abstract
Learner corpora and lingua franca corpora differ in important ways in social and interactional aspects. Yet in the cognitive domain of language processing they have much in common, as reflected in lexicogrammatical and phraseological features. They can therefore be seen as complementary takes on second language research. We can expect advanced second/foreign language learners to show similar linguistic features to lingua franca speakers, and supporting evidence is accumulating. This paper suggests that although some features in an English as a lingua franca (ELF) corpus can be explained on cognitive principles similar to those likely to operate in learners, such as economy of effort, others cannot. For instance the common use of not quite native-like phraseological units requires a use-based rather than learning-based explanation. On the whole, the major differences between learner and ELF corpora make it necessary to keep them separate. At the same time, both can contribute results of considerable mutual interest.
Chapters in this book
- Prelim pages i
- Table of contents v
- Acknowledgements ix
- List of contributors xi
- Preface xiii
- Putting corpora to good uses 1
- Frequency, corpora and language learning 7
- Learner corpora and contrastive interlanguage analysis 33
- The use of small corpora for tracing the development of academic literacies 63
- Revisiting apprentice texts 85
- Automatic error tagging of spelling mistakes in learner corpora 109
- Data mining with learner corpora 127
- Learners and users – Who do we want corpus data from? 155
- Learner knowledge of phrasal verbs 173
- Corpora and the new Englishes 209
- Towards a new generation of corpus-derived lexical resources for language learning 237
- Automating the creation of dictionaries 257
- addendumSelect list of publications by Sylviane Granger 283
- Subject index 289
- Name index 293
Chapters in this book
- Prelim pages i
- Table of contents v
- Acknowledgements ix
- List of contributors xi
- Preface xiii
- Putting corpora to good uses 1
- Frequency, corpora and language learning 7
- Learner corpora and contrastive interlanguage analysis 33
- The use of small corpora for tracing the development of academic literacies 63
- Revisiting apprentice texts 85
- Automatic error tagging of spelling mistakes in learner corpora 109
- Data mining with learner corpora 127
- Learners and users – Who do we want corpus data from? 155
- Learner knowledge of phrasal verbs 173
- Corpora and the new Englishes 209
- Towards a new generation of corpus-derived lexical resources for language learning 237
- Automating the creation of dictionaries 257
- addendumSelect list of publications by Sylviane Granger 283
- Subject index 289
- Name index 293
