I am an Assistant Professor of French Language Teaching at the University of Louvain (UCLouvain), in Louvain-la-Neuve, Belgium. I am affiliated with the Institute for the Analysis of Change in Contemporary and Historical Societies (IACCHOS) and the Centre de recherche interdisciplinaire sur les pratiques enseignantes et les disciplines scolaires (Cripedis).
I study conversational AI for language learning, or dialogue-based CALL, more precisely task-oriented dialogue systems (chatbots) for language learning, at the intersection of Task-based language teaching (TBLT), computer-assisted language learning (CALL) and natural language processing (NLP). My research focuses on the instructional design and the evaluation of the effectiveness of conversational AI for L2 proficiency development, particularly L2 vocabulary and fluency.
PhD in Linguistics, 2022
KU Leuven
Agrégation in Romance Languages, 2007
Université de Louvain
MA in Romance Languages, 2007
Université de Louvain
BA in Romance Languages, 2004
Université Saint-Louis
A meta-analysis of effectiveness studies on dialogue-based CALL, based on 17 studies and $k = 100$ individual effect sizes. We use Morris and DeShon’s (2002) formulas to compute comparable effect sizes across designs, and analyse them through a multilevel random-effects model. Results confirm that dialogue-based CALL practice has a significant medium effect size on L2 proficiency development ($d = 0.59$). Extensive moderator analyses on several learning outcomes of different types and features of dialogue-based CALL (type of interaction, modality, agent embodiment, etc.) confirm the effectiveness of form-focused and goal-oriented systems, system-guided interactions, corrective feedback provision, and gamification features. Significant effects for lower proficiency learners, and on vocabulary, morphosyntax, holistic proficiency and accuracy are established.
Dialogue systems allow a user to interact, orally or in writing, with an automated interlocutor, whether it is referred to as a chatbot, a robot, a conversational agent or an intelligent personal assistant. We discuss the different typologies of dialogue-based computer-assisted language learning (CALL), the natural language processing (NLP) technology operating those systems, and the issues of their instructional design. We review the scientific findings on the cognitive, behavioral, and emotional effects of dialogue systems. Finally, we provide recommendations for the use of dialogue-based CALL in foreign language learning and teaching, as well as for the development of new conversational applications.
This article presents the results of a systematic review of the literature on dialogue-based CALL. Applications allowing a learner to have a conversation in a foreign language with a computer have been studied under different traditions (intelligent tutoring systems, dialogue systems, conversational agents, chatbots…). We attempt to offer a structured overview of these efforts into a conceptual framework, including an operational definition of dialogue-based CALL and a typology of systems (4 types: narrative, form-focused, goal-oriented and reactive systems) and types of dialogue, with their corresponding interactional, instructional and technological traits. We summarize the main results from empirical studies on such systems, and discuss the impact of dialogue-based CALL on motivation and L2 development.
Doctoral research project at KU Leuven, funded by a SENESCYT scholarship (Ecuador)
FNRS-FRFC research project from 2008 to 2010 at UCLouvain