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How to use oral multimodal corpora and data-driven learning to teach French Talk-in-Interaction

How to use oral multimodal corpora and data-driven learning to teach French Talk-in-Interaction AbstractThis paper presents one aspect of our ongoing research in the context of a doctoral thesis. We focus on the use of multimodal oral corpora to develop the interactional skills of learners of French as a foreign language (André 2018, Ravazzolo and Etienne 2019). To do so, we compiled a list of interactional difficulties through a survey of 20 researchers and French as a Foreign Language teachers. After that, we created a learner corpus to check whether the difficulties brought up in the survey were present in learners’ productions, and to narrow down our results. To better analyze this corpus, we conducted self-confrontations so that we could have input directly from the learners. The objective was to identify interactional difficulties that could be the object of data-driven learning (Johns 1991) sessions with intermediate-level learners of French as a Foreign Language. The paper is part of the AILA Europe special issue. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png European Journal of Applied Linguistics de Gruyter

How to use oral multimodal corpora and data-driven learning to teach French Talk-in-Interaction

Cousinard, Clara
European Journal of Applied Linguistics , Volume 10 (2): 12 – Sep 1, 2022
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Publisher
de Gruyter
Copyright
© 2022 Walter de Gruyter GmbH, Berlin/Boston
ISSN
2192-953X
eISSN
2192-953X
DOI
10.1515/eujal-2022-0032
Publisher site
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Abstract

AbstractThis paper presents one aspect of our ongoing research in the context of a doctoral thesis. We focus on the use of multimodal oral corpora to develop the interactional skills of learners of French as a foreign language (André 2018, Ravazzolo and Etienne 2019). To do so, we compiled a list of interactional difficulties through a survey of 20 researchers and French as a Foreign Language teachers. After that, we created a learner corpus to check whether the difficulties brought up in the survey were present in learners’ productions, and to narrow down our results. To better analyze this corpus, we conducted self-confrontations so that we could have input directly from the learners. The objective was to identify interactional difficulties that could be the object of data-driven learning (Johns 1991) sessions with intermediate-level learners of French as a Foreign Language. The paper is part of the AILA Europe special issue.

Journal

European Journal of Applied Linguistics – de Gruyter

Published: Sep 1, 2022

Keywords: oral multimodal corpora; data-driven learning; French talk-in-interaction; FLEURON; corpus

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