Article published in:
Multiple Affordances of Language Corpora for Data-driven LearningEdited by Agnieszka Leńko-Szymańska and Alex Boulton
[Studies in Corpus Linguistics 69] 2015
► pp. 267–296
Applying data-driven learning to the web
Alex Boulton | ATILF, CNRS & University of Lorraine
Data-driven learning typically involves the use of dedicated concordancers to explore linguistic corpora, which may require significant training if the technology is not to be an obstacle for teacher and learner alike. One possibility is to begin not with corpus or concordancer, but to find parallels with what ‘ordinary’ users already do. This paper compares the web to a corpus, regular search engines to concordancers, and the techniques used in web searches to data-driven learning. It also examines previous studies which exploit web searches in ways not incompatible with a DDL approach.
Keywords: data-driven learning, DDL, Google, Internet, search engines, web as corpus
Published online: 13 May 2015
https://doi.org/10.1075/scl.69.13bou
https://doi.org/10.1075/scl.69.13bou
Cited by
Cited by 2 other publications
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