Learning to interact from conversational narratives

Abstract

Abstract This article explores two under-researched types of corpora for use in data-driven learning (DDL): L2 corpora (i.e. in a second or foreign language) and multimodal corpora. It first outlines the development of FLEURON, a dedicated DDL platform designed to support interactional competence in French as a Foreign Language (FFL), based on multimodal corpora of both native and L2 speakers. It then presents an ecological study of how 19 international FFL learners interacted with the platform in a DDL approach at the University of Lorraine. The analysis highlights how L2 corpora in particular can help learners to improve their awareness of complex phenomena related to conversational narratives by engaging their meta-cognitive strategies during their time abroad. The study thus reveals the potential for integrating an L2 component among the range of resources available for teaching and learning spoken interaction.