Thirty years of data-driven learning: Taking stock and charting new directions - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Language Learning & Technology Année : 2021

Thirty years of data-driven learning: Taking stock and charting new directions

Résumé

The tools and techniques of corpus linguistics have many uses in language pedagogy, most directly with language teachers and learners searching and using corpora themselves. This is often associated with work by Tim Johns who used the term Data-Driven Learning (DDL) back in 1990. This paper examines the growing body of empirical research in DDL over three decades (1989-2019), with rigorous trawls uncovering 489 separate publications, including 117 in internationally ranked journals, all divided into five time periods. Following a brief overview of previous syntheses, the study introduces our collection, outlining the coding procedures and conversion into a corpus of over 2.5 million words. The main part of the analysis focuses on the concluding sections of the papers to see what recommendations and future avenues of research are proposed in each time period. We use manual coding and semi-automated corpus keyword analysis to explore whether those points are in fact addressed in later publications as an indication of the evolution of the field.
Fichier principal
Vignette du fichier
Boulton & Vyatkina 2021.pdf (1.09 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-04478640 , version 1 (26-02-2024)

Identifiants

  • HAL Id : hal-04478640 , version 1

Citer

Alex Boulton. Thirty years of data-driven learning: Taking stock and charting new directions. Language Learning & Technology, 2021. ⟨hal-04478640⟩
3 Consultations
0 Téléchargements

Partager

Gmail Facebook X LinkedIn More