The role of corpus linguistics in developing innovation in data-driven language learning

Abstract

Data Driven (language) Learning (DDL) is characterized by the use of language data in the language learning classroomso that students can analyse language and identify patterns of use. DDL fits well with contemporary learning paradigmsand with the so-called 21st C learning or lifelong learning, which implies a new attitude on the part of students andteachers. In this new scenario, students need to take responsibility over their own learning and become active learners,and not mere recipients of information. Teachers turn themselves into guides and facilitators of the learning process. Inmaking students work as researchers, DDL is therefore a representative example of learner-centred teaching. Moreover,this approach fosters inductive learning, as the process of analyzing data, formulating hypotheses and derivingconclusions is at the heart of this approach. However, classroom applications of traditional corpus linguistics haverelied on heavy linguistic research paradigms, which according to different authors has problematized the use of thismethodology.In the context of our proposal, the data-driven culture that we want to foster is based on a totally new approach to theway in which language data are treated by researchers/teachers and learners. The use of a new data model whichfavours a more rapid transformation into information which is meaningful to learners is at the hub of our approach toinnovation. Two European projects, SACODEYL and Corpora for Content Language Integrated Learning are examplesof innovation in the field of lifelong learning