Language Resources and Evaluation

, Volume 48, Issue 1, pp 1–3 | Cite as

Introduction to the special issue on Resources and Tools for Language Learners

  • Serge Sharoff
  • Stefania Spina
  • Sofie Johansson Kokkinakis
SI: Resources for language learning

This special issue of Language Resources and Evaluation is devoted to Resources and Tools for Language Learners.

The use of language resources in the teaching and learning of a foreign language goes back to the middle of the last century: the General Service List published by Michael West in 1953is one of the first examples of the usefulness of corpus information for language learning. In subsequent decades, corpora and corpus evidence became increasingly exploited for teaching and learning of foreign languages, including annotated frequency lists, corpus-based reference works such as dictionaries, concordances, and grammars, and tools for mining corpora (e.g., procedures for the extraction and analysis of collocations) for linguistic data that can be used in the classroom, CALL programs, and, in more recent years, web-based environments. As a result, a strong link has been forged “between the two previously disparate fields of corpus linguistics and foreign/second language research”...


Foreign Language Natural Language Processing Language Learner Language Resource Parallel Corpus 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Aston, G. (1997). Enriching the learning environment: Corpora in ELT. In A. Wichmann, S. Fligelstone, T. McEnery, & G. Knowles (Eds.), Teaching and language corpora (pp. 51–64). London: Longman.Google Scholar
  2. Borin, L. (2002). What have you done for me lately? The fickle alignment of NLP and CALL. In Proceedings of NLP in CALL. Jyväskylä, Finland.Google Scholar
  3. Brown, J. C., Frishkoff, G. A., & Eskenazi, M. (2005). Automatic question generation for vocabulary assessment. In Proceedings of Human Language Technology and Empirical Methods in Natural Language Processing (pp. 819–826), Vancouver, Canada.Google Scholar
  4. Burstein, J. (2003). The e-rater scoring engine: Automated essay scoring with natural language processing. In M. Shermis, & J. Burstein (Eds.), Automated essay scoring: A cross-disciplinary perspective, (pp. 113–121). Routledge.Google Scholar
  5. Granger, S. (2002). A Bird’s-eye view of learner corpus research. In S. Granger, J. Hung, & S. Petch-Tyson (Eds.), Computer learner corpora, second language acquisition and foreign language teaching (pp. 3–33). Amsterdam: John Benjamins.CrossRefGoogle Scholar
  6. Kilgarriff, A., Husák, M., McAdam, K., Rundell, M., & Rychlý, P. (2008). GDEX: Automatically finding good dictionary examples in a corpus. In Proceedings of Euralex.Google Scholar
  7. Leech, G. (1997). Teaching and language corpora: A convergence. In A. Wichmann, S. Fligelstone, T. McEnery, & G. Knowles (Eds.), Teaching and language corpora (pp. 1–23). London: Longman.Google Scholar
  8. Römer, U. (2008). Corpora and language teaching. In A. Lüdeling & K. Merja (Eds.), Corpus linguistics. An international handbook (Vol. 1, pp. 112–130). Berlin: Mouton de Gruyter.Google Scholar
  9. Schwarm, S. E., & Ostendorf, M. (2005). Reading level assessment using support vector machines and statistical language models. In Proceedings of ACL. Ann Arbor, MI.Google Scholar
  10. West, M. (1953). A general service list of English words. London: Longman.Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Serge Sharoff
    • 1
  • Stefania Spina
    • 2
  • Sofie Johansson Kokkinakis
    • 3
  1. 1.Centre for Translation StudiesUniversity of LeedsLeedsUK
  2. 2.Dipartimento di scienze umane e socialiUniversità per Stranieri di PerugiaPerugiaItaly
  3. 3.Department of SwedishUniversity of GothenburgGöteborgSweden

Personalised recommendations