In:Beyond Concordance Lines: Corpora in language education
Edited by Pascual Pérez-Paredes and Geraldine Mark
[Studies in Corpus Linguistics 102] 2021
► pp. 231–252
Chapter 10CEFR-J × 28
Corpus-based multilingual pedagogical resources and e-learning systems for 28 languages
Published online: 22 December 2021
https://doi.org/10.1075/scl.102.10ton
https://doi.org/10.1075/scl.102.10ton
Abstract
This chapter discusses the development of multilingual pedagogical resources that make use of functional descriptors such as vocabulary and grammar items aligned to the CEFR levels in English. CEFR-J × 28 is a project that sets out to create multilingual pedagogical resources for 28 languages based upon the resources developed for the CEFR-J, a localised version of the CEFR for English language teaching in Japan. The chapter discusses the original CEFR-J project and its accompanying resources such as word/phrase lists, grammar and text profiles. It describes how to convert English resources into multiple languages using machine translation and multilingual corpora. A discussion of the advantages of this approach as well as future work is provided. The chapter discusses a series of e-learning tools developed to support learners’ vocabulary and grammar learning as well as a web-based learner corpus collection tool for multilingual spoken and written production.
Article outline
- Introduction
- The CEFR-J project
- Survey of standards and learning objectives (2004–2007)
- The construction of the CEFR-J (2008–2011)
- Reference level descriptions for the CEFR-J (2012–2015)
- CEFR-J wordlist
- CEFR-J can-do descriptor database
- CEFR-J grammar profile
- CEFR-J text profile
- Applying the CEFR-J resources to multilingual education
- Designing a workbench for multilingual pedagogical resource construction
- Semi-automated construction of the CEFR-J × 28 wordlists
- Creating can-do phrase lists for the CEFR-J × 28
- Developing CEFR-J × 28 e-learning tools
- The CEFR-J × 28 flash card vocab builder
- The CEFR-J × 28 can-do sentence builder
- The can-do task-based spoken/written corpus collection tool
- Conclusions and implications for future research
Note References
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