Applying a data-driven approach to language learning: the new talk of the Arqus series “7 Months, 7 Universities”

Arqus

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06/Jul/2022

The series of guest lectures “Seven months, seven universities” launches its 14th episode with the presentation: “Encouraging students’ exploration of language through data-driven learning”. The talk will be given by Katherine Ackerley, Associate Professor at the University of Padua, on 13th July at 11:00 CEST and it will be broadcast live on the Arqus YouTube channel.

The benefits of corpora in language education are widely recognised, yet data-driven approaches are still not well-established in the classroom. In the data-driven approach to language learning, teachers “simply provide the evidence needed to answer the learner’s questions, and rely on the learner’s intelligence to find answers” (Johns 1991: 2), a “learner-as-researcher” approach that can often result in serendipitous learning (Bernardini 2000).

This talk will illustrate how corpora have been used in university classes for Italian students of English. It will be seen how, through hands-on exploration of corpora, students can be encouraged to go beyond the vocabulary and phrases learned at school to become explorers of the language, capable of finding linguistic evidence that can lead to more adventurous, proficient language use.

Katherine Ackerley is Associate Professor of English language at the Department of Linguistic and Literary Studies, University of Padua, where she teaches the degree course in Language, Literature, and Cultural Communication. Her research interests include applied corpus linguistics, online language learning, and English-medium instruction.

This is the fourteenth episode of a series of guest lectures (“Seven months, seven universities”) to be offered in the framework of the Action Line 4 of Arqus, Multilingual and Multicultural University (sub-line 4.8). These lectures focus on specific topics related to language and culture and target mainly graduate and post-graduate students as well as early-stage researchers interested in those topics. 

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