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Narrow reading, vocabulary load and collocations in context: Exploring lexical repetition in concordances from a pedagogical perspective

Published online by Cambridge University Press:  15 June 2020

Oliver James Ballance Open the ORCID record for Oliver James Ballance [Opens in a new window]
Oliver James Ballance*
Affiliation:
Victoria University of Wellington, New Zealand ([email protected])
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Abstract

Narrow reading has the potential to reduce vocabulary load and to provide rich opportunities for developing collocation knowledge, but these benefits rely on narrow reading increasing lexical repetition within a text. Hence, interest in narrow reading has been limited by the relatively small lexical effect of narrowing reading by topic (Nation, 2013). Nevertheless, research in data-driven learning and teaching and language corpora has reported positively on learners using concordances in a manner comparable to narrow reading. However, the potential for concordances to provide an increased lexical-repetition effect has not been assessed. This study bridges this gap by exploring the degree of lexical repetition available in concordances and identifies corpus composition as a key predictor of lexical repetition. The study uses standardised type-token ratio (sTTR) to analyse concordances extracted from corpora at three different levels of homogeneity/heterogeneity. The results show large, reliable variations in lexical repetition resulting from variation in corpus homogeneity/heterogeneity, and so identifies concordance-based narrow reading as a possible means of overcoming the limitations of traditional narrow reading by topic. The results are discussed with reference to pedagogical implications for language learners, teachers, and researchers.

Keywords

corpus linguisticsdata-driven learningdepth of vocabulary knowledgenarrow readingtype-token ratiovocabulary load
Type
Regular papers
Information
ReCALL , Volume 33 , Issue 1 , January 2021 , pp. 4 - 17
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Copyright
© European Association for Computer Assisted Language Learning 2020

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