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AI augmented approach to identify shared ideas from large format public consultation
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Urban Narrative: Computational Linguistic Interpretation of Large Format Public Participation for Urban Infrastructure
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In: Urban Planning ; 5 ; 4 ; 20-32 ; The City of Digital Social Innovators (2020)
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Bundle-driven move analysis: Sentence initial lexical bundles in PhD abstracts
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Urban narrative: Computational linguistic interpretation of large format public participation for urban infrastructure
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Making use of and adapting MOOCs text resources for language learning
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Abstract:
Massive Open Online Courses are becoming popular educational vehicles through which universities reach out to non-traditional audiences. Many enrollees hail from other countries and cultures, and struggle to cope with the English language in which these courses are invariably offered. Moreover, most such learners have a strong desire and motivation to extend their knowledge of academic English, particularly in the specific area addressed by the course. Online courses provide a compelling opportunity for domain-specific language learning, a growing trend in language teaching and learning. Typical MOOCs supply a large corpus of interesting linguistic material relevant to a particular area, including supplementary images (slides), audio and video. Such corpus provides an excellent context to study domain-specific lexico-grammatical features of any word or phrase, a challenging aspect of English productive use even for quite advanced learners. We contend that this corpus can be automatically analysed, enriched, and transformed into a resource that learners can browse and query in order to extend their ability to understand the language used, and help them express themselves more fluently and eloquently in that domain. To illustrate this idea, an existing online corpus-based language learning tool (FLAX) is applied to a Coursera MOOC entitled English Common Law offered by University of London. We will illustrate how this resource has been augmented for language learning, and then review how learners can use it to explore language usage. This article uses a single running example, a Coursera MOOC course, but the approach is fully automated and can be applied to any collection of English writing.
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Keyword:
computer science; corpus-based language learning; data-driven learning; English for academic purposes; MOOCs
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URL: https://hdl.handle.net/10289/13201
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Automating vocabulary tests and enriching online courses for language learners
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Automatically augmenting academic text for language learning: PhD abstract corpora with the British Library
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Sentence initial bundles: A comparative study between Chinese master’s L2 theses and published writing
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Chinese postgraduates' explanation of the sources of sentence initial bundles in their thesis writing
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Evaluating the efficacy of the digital commons for scaling data-driven learning
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Sentence initial bundles in L2 thesis writing: A comparative study of Chinese L2 and New Zealand L1 postgraduates’ writing
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Learning collocations with FLAX apps
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In: MLearn 2016 (2016)
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FLAX: Flexible and open corpus-based language collections development
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Using Wikipedia for language learning
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In: CITRENZ 2015 (2015)
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FLAX: Flexible and open corpus-based language collections development
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Investigating an open methodology for designing domain-specific language collections
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Investigating an open methodology for designing domain-specific language collections
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In: 2014 EUROCALL (2014)
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Second language learning in the context of MOOCs
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In: CSEDU 2014 (2014)
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