Multiple Affordances of Language Corpora for Data-driven Learning

Name: Multiple Affordances of Language Corpora for Data-driven Learning
Brand: John Benjamins Publishing Company
Price: 123.99 EUR
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Agnieszka Lenko-Szymanska Alex Boulton(Herausgeber*in)

John Benjamins Publishing Company

1. Auflage

Erschienen am 15. Mai 2015

VII, 300 Seiten

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Inhalt

Intro
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 analysis
3.2 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 for acquiring spoken phraseology
3. Analysing a speech corpus: Some examples
3.1 Starting from a list
3.2 Starting from a listening experience
3.3 One thing leads to another
4. Implications: The role of the learner
References
Stealing a march on collocation
1. Introduction and overview
2. The Sketch Engine
3. A constrained definition of collocation and its affordances
4. Collocation Plus (C+)
5. Observing and using Topic Trails in full text
6. Conclusion
References
Appendix 1: Text examples cited
Appendix 2: Corpora cited
A corpus and grammatical browsing system for remedial EFL learners
1. Appropriate level, needs-driven corpora for the EFL classroom
2. Developing the Grammatical Pattern Profiling System (GPPS)
2.1 Using LWP-GRC as a model for the GPPS
2.2 GPPS functionality
2.3 Selection of grammatical categories
2.4 Creation of search expressions and patterns
3. Developing the Sentence Corpus of Remedial English (SCoRE)
3.1 Defining target population proficiency levels
3.2 Sourcing potential corpus data
3.3 Defining sentence length
3.4 Defining the number of sentences
3.5 Using the source corpus as a model for SCoRE
3.6 Translation
4. Pedagogical applications: Using SCoRE and the GPPS
5. Limitations of SCoRE and the GPPS
6. Conclusion
Acknowledgements
References
Part II. Corpora for skills development
Same task, different corpus
1. Introduction
2. Background to the course
2.1 Course programme
2.2 Course procedure
3. Data
3.1 Participants
3.2 Corpus and worksheet data
4. Corpus tools in the 'same task, different corpus' approach
4.1 The Concordance tool
4.2 The Word List tool
4.3 The Collocates tool
4.4 The Concordance Plot tool
5. Evaluation of the course
6. Conclusions and pedagogical implications
Acknowledgements
References
Appendix 1.
Textual cohesion patterns for developing reading skills
1. Reading skills
2. Connectors
2.1 Classifications of connectors
2.2 Collecting textual connectors and developing their classification scheme
3. Corpus design for teaching reading in a foreign language
3.1 Online news as material for teaching reading
3.2 Corpus annotation and representation
4. Corpus collection method and representation format
5. Application
5.1 Exercises for developing reading skills
5.2 Exercises with emphasis on the text function and text organisation
5.3 Exercises for developing ability to assess and evaluate a text, distinguish facts from opinions and understand the writer's intention
6. Conclusions and future work
References
Exploiting keywords in a DDL approach to the comprehension of news texts by lower-level students
1. Introduction
2. News, keywords, and DDL
3. Methodology
3.1 Instruments
3.2 Activities
3.3 Logs and questionnaires
4. Results
4.1 Activities
4.2 Test scores
4.3 Participants' feedback
5. Discussion
6. Conclusions
References
Part III. Corpora for translation training
Webquests in translator training
1. Introduction
2. Corpora as a pedagogic resource in translator training
3. Webquests
3.1 Student-student interaction: Collaborative aspects
3.2 Student-teacher interaction: Feedback and evaluation
4. Introducing translation students to corpus work through webquests: A pilot study
4.1 Webquest 1: What's in a prefix? The interaction of meaning and pronunciation
4.1.1 Exploring meaning, equivalence and use
4.1.2 Paying attention to intonation and stress
4.1.3 Translating, comparing and debating
4.2 Webquest 2: Modal particles - Understanding and re-creating pragmatic value
4.2.1 Grasping pragmatic value in the source language
4.2.2 Expressing pragmatic value in the target language
4.2.3 Assessing results (student translations vs. published translations)
5. Outcomes and prospects
6. Conclusions
Acknowledgements
References
Enhancing translator trainees' awareness of source text interference through use of comparable corpora
1. Introduction
2. Interference in translation
3. The use of corpora in translator education
4. Aims and method
5. Results and discussion
6. Concluding remarks
Acknowledgements
References
Using a multimedia corpus of subtitles in translation training
1. Introduction
2. Electronic corpora at the crossroads of translator training and professional practice
3. A multimedia corpus for hands-on training in subtitling
3.1 The Veiga multimedia corpus of subtitles
3.2 Corpus segmentation and annotation
3.3 The corpus search system
4. Corpus-driven tasks in the audiovisual translator training environment
4.1 Task 1: Formal features
4.2 Task 2: Omissions
4.3 Task 3: Additions
4.4 Task 4: Reductions of disfluency
4.5 Subsequent tasks
5. Conclusions
References
Appendix 1: Multimedia display of search results
Applying data-driven learning to the web
1. Introduction
2. Data-driven learning in theory and practice
3. Web as corpus
4. Google as concordancer
5. Searching the web
6. Previous studies
7. Conclusion
References
Notes on contributors
Publically-available corpus tools and resources discussed in the book
Subject Index
Author Index

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