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1 CRAPEL - Centre de Recherches et d-Applications Pédagogiques en Langues 2 ATILF - Analyse et Traitement Informatique de la Langue Française

Abstract : Data-driven learning DDL involves learners exploring corpora to discover language rather than -being taught-. This is claimed to have a number of advantages, and while empirical evidence to date is encouraging, it is less conclusive than might be hoped - partly, it is argued, as it tends to focus on short-term goals by testing knowledge and retention of selected language items covered. It may be, however, that the real advantages of DDL lie in longer-term benefits, cognitive-constructivist as well as purely linguistic; in addition to -incidental- learning and greater learner autonomy, these include language awareness and noticing ability, all of which are more difficult to assess. This paper reports on a medium-term experiment comparing noticing skills between experimental and control groups of lower-intermediate learners of English in an architecture school in France. The control groups were taught in the usual way, while the last 15 minutes of the experimental classes were given over to exploring the British National Corpus on line, with learners working in pairs on specific language points. Both experimental and control groups were tested after 12 weeks - not on the language points covered, but on their sensitivity to other language items in a previously unseen text. The time-frame of the present experiment is not enough to allow the full effects of DDL to be revealed, but does provide some indication that its main advantages go well beyond the short-term learning outcomes generally examined in current research. If further long-term work can confirm these findings, it might go some way towards helping DDL to reach a wider audience.

Keywords : data-driven learning DDL corpus-based language learning noticing

Autor: Alex Boulton -



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