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Automatically Augmenting Academic Text for Language Learning: PhD Abstract Corpora With the British Library

Automatically Augmenting Academic Text for Language Learning: PhD Abstract Corpora With the British Library
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Author(s): Shaoqun Wu (University of Waikato, New Zealand), Alannah Fitzgerald (Concordia University, Canada), Ian H. Witten (University of Waikato, New Zealand)and Alex Yu (Waikato Institute of Technology, New Zealand)
Copyright: 2018
Pages: 26
Source title: Handbook of Research on Integrating Technology Into Contemporary Language Learning and Teaching
Source Author(s)/Editor(s): Bin Zou (Xi’an Jiaotong-Liverpool University, China)and Michael Thomas (Liverpool John Moores University, UK)
DOI: 10.4018/978-1-5225-5140-9.ch025

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Abstract

This chapter describes the automated FLAX language system (flax.nzdl.org) that extracts salient linguistic features from academic text and presents them in an interface designed for L2 students who are learning academic writing. Typical lexico-grammatical features of any word or phrase, collocations, and lexical bundles are automatically identified and extracted in a corpus; learners can explore them by searching and browsing, and inspect them along with contextual information. This chapter uses a single running example, the PhD abstracts corpus of 9.8 million words derived from the open access Electronic Theses Online Service (EThOS) at the British Library, but the approach is fully automated and can be applied to any collection of English writing. Implications for reusing open access publications for non-commercial educational and research purposes are presented for discussion. Design considerations for developing teaching and learning applications that focus on the rhetorical and lexico-grammatical patterns found in the abstract genre are also discussed.

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