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Multiple Affordances of Language Corpora for Data-driven Learning
Edited by Agnieszka Leńko-Szymańska and Alex Boulton
[Studies in Corpus Linguistics 69] 2015
► pp. 15–36

Data-driven learning and language learning theories

Whither the twain shall meet

| formerly of the Centre for Language Education Hong Kong University of Science and Technology

This chapter discusses various language learning theories underpinning data-driven learning, namely the noticing hypothesis, constructivist learning and Vygotskyan sociocultural theories. A variety of pedagogic initiatives are used to illustrate the relationship between data-driven learning and language learning theories. The paper also reports on experimental studies which examine students’ performance in relation to these three language learning theories as well as learning style preferences. The general consensus from these experimental studies is that while data-driven learning shows promise, additional larger-scale studies of a longitudinal nature are needed to give a more in-depth picture of its beneficial effects.

Keywords: constructivist learning, deductive approach, inductive approach, learning styles, noticing hypothesis, scaffolding, sociocultural theories
Published online: 13 May 2015
DOI logo
https://doi.org/10.1075/scl.69.02flo
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