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

IF 0.8 Q3 LINGUISTICS European Journal of Applied Linguistics Pub Date : 2022-09-01 DOI:10.1515/eujal-2022-0032
Clara Cousinard
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Abstract

Abstract This 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.
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如何使用口语多模态语料库和数据驱动学习来教授法语对话式互动
本文介绍了我们正在进行的博士论文研究的一个方面。我们专注于使用多模态口语语料库来培养法语作为外语学习者的互动技能(andr 2018, Ravazzolo和Etienne 2019)。为此,我们通过对20名研究人员和法语作为外语教师的调查,编制了一份互动困难清单。之后,我们创建了一个学习者语料库,以检查调查中提出的困难是否存在于学习者的作品中,并缩小我们的结果。为了更好地分析这个语料库,我们进行了自我对抗,这样我们就可以直接从学习者那里得到输入。目的是确定可能成为数据驱动学习(Johns 1991)课程对象的交互困难,该课程以法语为外语的中级水平学习者为对象。这篇论文是AILA欧洲特刊的一部分。
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