I am an Assistant Professor of French and English Language Teaching at Universidad Central del Ecuador, in Quito.
Currently finishing my PhD at KU Leuven (ITEC, an imec research group) and UCLouvain (CENTAL team) in Belgium, I work on dialogue-based CALL, more precisely on task-oriented dialogue systems (chatbots) for language learning, at the intersection of computer-assisted language learning (CALL) and natural language processing (NLP). My research focuses on the instructional design and the evaluation of the effectiveness of dialogue-based CALL systems for L2 proficiency development, in particular L2 fluency.
I am a PhD candidate in Linguistics thanks to a SENESCYT scholarship (Ecuador). Previously, I worked as a research assistant at UCLouvain on reflexive writing in general education.
PhD in Linguistics, ongoing
Agrégation in Romance Languages, 2007
MA in Romance Languages, 2007
BA in Romance Languages, 2004
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.