Learner corpus research: a critical appraisal and roadmap for contributing (more) to SLA research agendas
(2024) Corpus Linguistics and Linguistic Theory — Vol. 20, n° 3, p. 567-590 (2024)
Files
CLLT_learner_corpora_rev_FINAL.docx
Open Access - Microsoft Word XML
- 145.61 KB
Details
- Authors
- Abstract
- Over the past decade, learner corpora have gained recognition as valuable data sources in Second Language Acquisition (SLA) research. This development can be attributed to significant progress in Learner Corpus Research (LCR). However, there is still substantial work to be done. This article highlights key issues essential for sustaining the relevance of learner corpora in SLA. More particularly, I focus on the need for more diverse types of learner corpora, stress the importance of detailed metadata, and advocate for multifactorial study designs. I then revisit ongoing debates regarding the role of the native speaker in LCR and propose a practical solution to address this thorny issue. Finally, I also readdress the need for improvement in the quantitative methods and statistics, arguing that the importance of robust quantitative analysis cannot be over-stated. In conclusion, I envision an ambitious learner corpus compilation project that adheres to the FAIR principles, with the goal of further elevating study quality in LCR.
- Affiliations
Citations
Paquot, M. (2024). Learner corpus research: a critical appraisal and roadmap for contributing (more) to SLA research agendas. Corpus Linguistics and Linguistic Theory, 20(3), 567-590. https://doi.org/10.1515/cllt-2024-0014 (Original work published 2024)