Applications of corpus-based linguistics to second language instruction: Lexical grammar and data-driven learning
Date
2008-01-01
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Heinle Cengage Learning
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2008
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128
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150
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Abstract
Although the use of corpora and concordancing as a research method to discover patterns of language use in real-world language data is somewhat familiar to applied linguists (e.g., Di Vito, 1997; Celce-Murcia & Larsen-Freeman, 1998), the potential pedagogical uses of these tools appear to be unfamiliar to practitioners
in second language education in the United States, especially in comparison
to their European counterparts and to ESL specialists. This chapter
describes some of the potential uses of these technologies in second language
education and their relevance to language program directors and classroom teachers. In addition to describing potential uses of corpora and concordancing (also referred to as data-driven learning), it argues for a greater emphasis on vocabulary acquisition and a better integration of lexical and grammatical aspects
of language instruction, following certain insights from the field of corpus
linguistics. Of special interest is the notion of the centrality of lexical
phrases in speech production, as articulated in Sinclair’s lexical grammar and later brought to bear on second language instruction in Lewis’s lexical approach. In addition, language program directors should be aware of the ability of corpus-based analyses to describe more accurately native-speaker usage and, therefore, to contribute to the formulation of appropriate pedagogical norms
for grammatical instruction.With respect to classroom instruction, the chapter
illustrates through sample activities (in English and French) how online corpora and concordancers can be used to provide student-centered consciousness- raising activities based on authentic language. An appendix suggests appropriate online concordancers for French, German, and Spanish.
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Kerr, B.J. (2008). Applications of corpus-based linguistics to second language instruction: Lexical grammar and data-driven learning. The American Association of University Supervisors, Coordinators and Directors of Foreign Languages Programs (AAUSC), 128-150. http://hdl.handle.net/102015/69661
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