Language corpora for L2 vocabulary learning: Data-driven learning across the curriculum
Date
2018-01-01
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Cengage
Volume
2018
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121
Ending Page
145
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Abstract
Empirical Instructed Second Language Acquisition research on L2 vocabulary
has shown that Data-Driven Learning (DDL), or teaching and learning languages
with the help of corpora (large, structured electronic collections of texts), is beneficial
for L2 vocabulary acquisition. Nevertheless, it is still far from becoming
a common pedagogical practice, not least because few pedagogical manuals and
user-friendly corpus tutorials have been published to date. This chapter describes
how DDL with an open-access German language corpus has been used across the
curriculum in a German Studies program at a North American university. I report
empirical results and present specific pedagogical suggestions and activities for
using a corpus to enhance L2 vocabulary knowledge at all proficiency levels and
show how DDL can help learners improve not only the breadth of their L2 vocabulary
knowledge (the number of words the basic meaning of which the learner
knows) but also the depth of this knowledge, including collocations, frequency,
and grammatical patterns. Although this chapter uses a German program as a
case study, its pedagogical suggestions can be applied to teaching any language for
which open-access electronic corpora are available.
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Vyatkina, N. (2018). Language corpora for L2 vocabulary learning: Data-driven learning across the curriculum. The American Association of University Supervisors, Coordinators and Directors of Foreign Languages Programs (AAUSC), 121-145. http://hdl.handle.net/102015/69785
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