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Language Corpora for L2 Vocabulary Learning: Data-Driven Learning Across the Curriculum
Vyatkina, Nina
Vyatkina, Nina
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Abstract
Empirical Instructed Second Language Acquisition (ISLA) 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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2018
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Cenage Learning
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Vyatkina, N. (2018). Language corpora for L2 vocabulary learning: Data-driven learning across the curriculum. In P. Ecke & S. Rott (Eds.), Understanding vocabulary learning and teaching: Implications for language program development (pp. 121-145). Boston, MA: Cengage Learning