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How learner corpus-research can inform language learning and teaching
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Less is more? The impact of written corrective feedback on corpus-assisted L2 error resolution
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Abstract:
The past decade has seen a sharp increase in research into L2 learners’ direct use of language corpora (typically known as ‘data-driven learning’, DDL) for error resolution in L2 writing. However, a crucial yet underexplored variable in this process is whether and how the form of written corrective feedback (WCF) provided on L2 writing facilitates effective corpus consultation for L2 error resolution. Focusing on L2 writers at the post-graduate level and using a short private online course for DDL training, we determine the impact of four WCF conditions (varying in their degree of directness) on students’ use of corpora for lexical and grammatical error resolution, and the appropriacy of error revisions made with/without corpora for these error types. The results suggest that ‘less (WCF) is more’ if learners are to make successful error revisions via corpus consultation, with more direct WCF conditions often resulting in students revising errors without consulting a corpus. However, less direct WCF conditions sometimes resulted in inappropriate revisions, as learners required additional information as to the nature and location of the specific error. Differences were also found in the effectiveness of corpus consultation for grammatical and lexical error types, with WCF a confounding factor. These results suggest that if corpora are to be used for L2 error resolution, teachers need to carefully consider whether their WCF allows for meaningful engagement with corpora to occur, and whether corpus consultation is suitable or desirable for resolving all error types.
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Keyword:
1203 Language and Linguistics; 3304 Education; 3310 Linguistics and Language; Data-driven learning; L2 error resolution; L2 writing; Written corrective feedback
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URL: https://espace.library.uq.edu.au/view/UQ:30df823
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Using Semantic Vector Space Models to investigate lexical replacement – a corpus based study of ongoing changes in intensifier systems
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How learner corpus research can inform language learning and teaching: an analysis of adjective amplification among L1 and L2 English speakers
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Swearing in Irish English: a corpus-based quantitative analysis of the sociolinguistics of swearing
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The sociolinguistics of emotional language - emotive use in Irish English
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Swearing in Irish English - a corpus-based quantitative analysis of the sociolinguistics of swearing
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Using semantic vector space models to investigate lexical replacement - a corpus based study of ongoing changes in intensifier systems
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The discourse marker LIKE : a corpus-based analysis of selected varieties of English ; Der Diskursmarker LIKE : eine korpusbasierte Untersuchung ausgewählter Varietäten des Englischen
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Studying the linguistic ecology of Singapore: a comparison of college and university students
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In: World Englishes : Special Issue: English in multilingual singapore. - 33, 3 (2014) , 340-362, ISSN: 1467-971X (2014)
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Studying the linguistic ecology of Singapore: a comparison of college and university students
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The discourse marker LIKE: a corpus-based analysis of selected varieties of English
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