Dialogue-based CALL: a multilevel meta-analysis

Autor: Bibauw, Serge, Van den Noortgate, Wim, François, Thomas, Desmet, Piet
Přispěvatelé: UCL - SSH/ILC/PLIN - Pôle de recherche en linguistique, UCL - SSH/TALN - Centre de traitement automatique du langage
Jazyk: angličtina
Rok vydání: 2018
Popis: Dialogue-based CALL systems allow a learner to practice meaningfully an L2 with an automated agent, through an oral (spoken dialogue systems) or written interface (chatbots) (Bibauw, François, & Desmet, 2015). In order to obtain a better comprehension of their effects on L2 proficiency development, we conducted a multilevel meta-analysis on all the experimental studies measuring an impact of such systems on language learning outcomes (40 publications). Effect sizes for each variable and group under observation were systematically computed (k=96). By combining all studies into a multilevel linear model, we observed a significant medium effect of dialogue-based CALL on general L2 proficiency development (d=.61). By integrating moderator variables into our statistical model, we are able to provide insights on the relative effectiveness of certain technological and instructional characteristics (spoken vs. written, task-oriented vs. open-ended, form-focused vs. meaning-focused) on different learning outcomes (writing vs. speaking vs. comprehension skills, complexity, accuracy and fluency measures…) and different samples of populations (L2 proficiency, age, context…), as well as to model the effect of treatment duration (number of sessions and time on task) and spacing on these outcomes, to better inform future system and research design.
Databáze: OpenAIRE