Data‐Driven Learning: A Linguistically Authentic Complement to Coursebooks for Foreign Language Learners

ABSTRACT This study explores the potential of data‐driven learning (DDL) as a complement to traditional coursebooks for multilingual learners of French as a foreign language. Motivated by the need to address insufficiencies in coursebooks, such as oversimplified and misrepresented grammar rules, the study aims to examine how DDL facilitates the learning of French, focusing on adjective placement. To investigate this, the study employed a mixed‐methods experimental design incorporating corpus analyses to inform DDL materials, as well as pre‐, post‐, and delayed post‐tests, questionnaires, focus group interviews, and field recordings. Findings indicate that while DDL and traditional instruction yielded comparable short‐term outcomes, DDL enhanced long‐term retention, critical thinking, and learner autonomy. By exposing learners to authentic language data, DDL heightened awareness of linguistic gradience and variability, supporting its role as a valuable complement to coursebooks in foreign language education.