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1
AI augmented approach to identify shared ideas from large format public consultation
Weng, Min-Hsien; Wu, Shaoqun; Dyer, Mark. - : MDPI AG, 2021
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Urban Narrative: Computational Linguistic Interpretation of Large Format Public Participation for Urban Infrastructure
In: Urban Planning ; 5 ; 4 ; 20-32 ; The City of Digital Social Innovators (2020)
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3
Bundle-driven move analysis: Sentence initial lexical bundles in PhD abstracts
Wu, Shaoqun; Li, Liang; Franken, Margaret. - : Elsevier, 2020
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4
Urban narrative: Computational linguistic interpretation of large format public participation for urban infrastructure
Dyer, Mark; Weng, Min-Hsien; Wu, Shaoqun. - : Cogitatio, 2020
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5
Making use of and adapting MOOCs text resources for language learning
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6
Automating vocabulary tests and enriching online courses for language learners
König, Jemma Lynette. - : The University of Waikato, 2019
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7
Automatically augmenting academic text for language learning: PhD abstract corpora with the British Library
Yu, Alex; Witten, Ian; Fitzgerald, Alannah. - : IGI Global, 2018
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8
Sentence initial bundles: A comparative study between Chinese master’s L2 theses and published writing
Wu, Shaoqun; Li, Liang; Franken, Margaret. - : Asian EFL Journal Press, 2018
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9
Chinese postgraduates' explanation of the sources of sentence initial bundles in their thesis writing
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10
Evaluating the efficacy of the digital commons for scaling data-driven learning
Marin, Maria Jose; Witten, Ian; Fitzgerald, Alannah. - : Routledge, Taylor & Francis., 2017
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11
Sentence initial bundles in L2 thesis writing: A comparative study of Chinese L2 and New Zealand L1 postgraduates’ writing
Li, Liang. - : University of Waikato, 2017
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12
Learning collocations with FLAX apps
In: MLearn 2016 (2016)
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13
FLAX: Flexible and open corpus-based language collections development
Fitzgerald, Alannah; Wu, Shaoqun; Marin, Maria Jose. - : Research-publishing.net, 2015
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14
Using Wikipedia for language learning
In: CITRENZ 2015 (2015)
Abstract: Differentiating between words like look, see and watch, injury and wound, or broad and wide presents great challenges to language learners because it is the collocates of these words that reveal their different shades of meaning, rather than their dictionary definitions. This paper describes a system called FlaxCLS that overcomes the restrictions and limitations of the existing tools used for collocation learning. FlaxCLS automatically extracts useful syntactic-based word from three millions Wikipedia article and provides a simple interface through which learners seek collocations of any words, or search for combinations of multiple words. The system also retrieves semantically related words and collocations of the query term by consulting Wikipedia. FlaxCLS has been used as language support for many Masters and PhD students in a New Zealand university. Anecdotal evidence suggests that the interface it provides is easy to use and students have found it helpful in improving their written English.
Keyword: collocations; Computer-assisted Language Learning; concordancers; Data-driven Learning; Machine learning; Wikipedia
URL: https://hdl.handle.net/10289/9686
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15
FLAX: Flexible and open corpus-based language collections development
Fitzgerald, Alannah; Wu, Shaoqun; Marín, María José. - : Research-publishing.net, 2015
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16
Investigating an open methodology for designing domain-specific language collections
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17
Second Language Learning in the Context of MOOCs
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18
Investigating an open methodology for designing domain-specific language collections
In: 2014 EUROCALL (2014)
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19
Second language learning in the context of MOOCs
In: CSEDU 2014 (2014)
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20
Supporting collocation learning with a digital library
In: Computer assisted language learning. - Colchester [u.a.] : Taylor & Francis 23 (2010) 1, 87-110
OLC Linguistik
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