Corpus Analysis and the Achievement of Learner Autonomy in Interaction

Abstract

Differentiating between corpus work for & in the classroom, it is observed that the challenge of corpus work in the classroom is that it makes accessible to students & teachers a new, previously unavailable, analytic methodology & that the idea of exploring corpora on the basis of this methodology may prompt a series of interesting learning activities in which students & teachers can be engaged. Thus, corpus work in the classroom offers an opportunity to: (1) look at features of language in use, (2) understand that there are regularities in language use that are not solely of a logical, rationalistic nature, & (3) empower students/teachers by allowing them to contribute to the description of language features with their own original observation. Focusing on (3), this study reports on students working with corpora as hands-on analysts & elaborates further Tim Johns's (1991 & 1994) Data-Driven Learning (DDL) approach, as well as discusses its consequences for the achievement of learner autonomy in language learning. After summarizing the principal features of the DDL methodology, it is demonstrated that the principles on which it is based are also present in discussions about the development of language learning autonomy & learners' responsibility for their own learning. Two reports by students working on features of text & discourse with self-built corpora are presented to demonstrate the significance of their discoveries for learner autonomy & the development of autonomous language learning. Z. Dubiel