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From input to output: the potential of parallel corpora for CALL

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Abstract

The aim of this paper is to illustrate the potential of a parallel corpus in the context of (computer-assisted) language learning. In order to do so, we propose to answer two main questions (1) what corpus (data) to use and (2) how to use the corpus (data). We provide an answer to the what-question by describing the importance and particularities of compiling and processing a corpus for pedagogical purposes. In order to answer the how-question, we first investigate the central concepts of the interactionist theory of second language acquisition: comprehensible input, input enhancement, comprehensible output and output enhancement. By means of two case studies, we illustrate how the abovementioned concepts can be realized in concrete corpus-based language learning activities. We propose a design for a receptive and productive language task and describe how a parallel corpus can be at the basis of powerful language learning activities. The Dutch Parallel Corpus, a ten-million word sentence aligned and annotated parallel corpus, is used to develop these language tasks.

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Notes

  1. Other linguistic research domains such as descriptive linguistics, contrastive linguistics, and translation studies, and more application-oriented research areas such as machine translation and natural language processing research (NLP) have all illustrated the benefits of using corpora in their domain.

  2. Sinclair (2004: 9) states that the changes brought forth by corpora “were likely to have a profound effect on the teaching and learning of languages, because the new descriptions would represent language in a different way”.

  3. In a more general context, Rundell and Stock (1992) also referred to “The corpus revolution”.

  5. For a corpus typology, we refer to the overview of Fuster and Clavel (2010).

  6. As pointed out by Gilquin and Granger (2010: 362): “(i)t is probably fair to say that most DDL activities involve concordances of some sort”. Frequency lists may also be used in this context.

  7. E.g. KWIC (Key-Word-In-Context). The context is usually expressed in a number of words situated left and right from the keyword.

  8. While extensive research has been published on the use of learner corpora in language pedagogy, it is not our aim to provide a detailed overview of the importance of learner corpora. For more information on the use of learner corpora we refer to for instance Granger (2002, 2009).

  9. As Frankenberg-García (2005: 197) stated in her paper on monolingual and parallel concordances, “the two types of concordances have non-conflicting, complementary roles to play” (e.g. parallel concordances might be more interesting to optimize comprehension whereas monolingual concordances may be useful to provide grammatical evidence) and it is important to judge which type of concordance matches the particular learning context.

  10. For more information on the corpus and its availability, see http://www.inl.nl/tst-centrale/nl/producten/corpora/dutch-parallel-corpus-niet-commercieel/6-65, visited 21 March 2013.

  11. For more information, we refer to http://www.tei-c.org/Guidelines/P5/, visited 21 March 2013.

  12. In his 1999 book “Interaction and the second language learner”, Ellis argued that there are two main types of interaction: interpersonal and intrapersonal interaction. Chapelle (2003) stated that interpersonal interaction does not only take place between people but also between learner and computer.

  13. We could also refer to a learner-corpus interaction in the context of Data Driven Learning (e.g. Fuster and Clavel 2010).

  14. Chapelle’s conceptualization (1998, 2003, 2005a, 2005b) is largely based on the one made by Sharwood Smith (1993)). In his 1993 article, he referred to the notion as a manipulation of “aspects of the input” but no “further assumptions about the consequences of that input on the learner” could be made.

  15. Because words in the French-Dutch part of the DPC corpus are not aligned below sentence level, the isolated translation of the French word “la percée” cannot be given.

  16. Translation into English: “daily cleansing, wash your face, the upper part of the body and your hands; brush your teeth”.

  17. The aim of the DPC project was to create a multifunctional corpus, which is also suited for translation studies, machine translation, descriptive linguistics, etc.

  18. For a complete overview, see van Baardewijk-Rességuier and van Willigen-Sinemus (1989).

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Acknowledgments

The DPC project has been carried out within the STEVIN programme, which is funded by the Dutch and Flemish Governments. The DPC was created by a Flemish consortium (KU Leuven Kulak and the Faculty of Translation Studies of Ghent University College): Piet Desmet, Willy Vandeweghe, Hans Paulussen, Lieve Macken, Maribel Montero Perez, Orphée De Clercq, Lidia Rura, Julia Trushkina, and Antoine Besnehard.

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Authors and Affiliations

  1. ITEC-iMinds, KU Leuven Kulak, Etienne Sabbelaan 53, 8500, Kortrijk, Belgium

    Maribel Montero Perez, Hans Paulussen & Piet Desmet

  2. LT3, University College Ghent, Groot-Brittanniëlaan 45, Ghent, Belgium

    Lieve Macken

  3. Departement of Applied Mathematical and Computer Science, Ghent University, Krijgslaan 281 (S9), 9000, Ghent, Belgium

    Lieve Macken

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Montero Perez, M., Paulussen, H., Macken, L. et al. From input to output: the potential of parallel corpora for CALL. Lang Resources & Evaluation 48, 165–189 (2014). https://doi.org/10.1007/s10579-013-9241-4

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