Chapter in:Beyond Concordance Lines: Corpora in language education
Edited by Pascual Pérez-Paredes and Geraldine Mark
[Studies in Corpus Linguistics 102] 2021
► pp. 36–55
Data-driven learning, theories of learning and second language acquisition
In search of intersections
This chapter focuses on the need to address both theories of learning and theories of language acquisition in data-driven learning (DDL) research. While it recognises that there has been so much worthwhile research work on DDL which has shed so much light on the value of DDL, it is still not a mainstream methodology. The chapter argues that by understanding better the variations in pedagogical underpinnings and ontologies, DDL research can better pinpoint what works within specified variables. Additionally, the paper argues strongly for engagement with ongoing research in second language acquisition (SLA), especially from a usage-based perspective because there are so many resonances for DDL in terms of the centrality of the role of frequently experienced syntactic regularities in learning.
Keywords: data-driven learning, second language acquisition, usage-based theory