Helping Language Learners Put Concordance Data in Context: Concordance Cards in The Prime Machine

Helping Language Learners Put Concordance Data in Context: Concordance Cards in The Prime Machine

Stephen Jeaco (Xi'an Jiaotong-Liverpool University, China)
DOI: 10.4018/978-1-5225-9618-9.ch004
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While corpus tools provide several different ways to display relationships between words within texts and across texts, the main format for viewing concordance data is Key Word in Context (KWIC). In Computer Aided Language Learning, concordance lines in KWIC format may be accessed inside a concordancer or within other software through links to corpus data. Language learners can and do gain useful insights from exploring concordance data in KWIC format, but some kinds of information may be harder to see, some patterning of use may not be so obvious, and reading of complete examples may not be very easy. The Prime Machine was developed for language learners and aims to make corpus data easier to access and interpret. This paper introduces the design of the Cards Tab, which provides an additional way of viewing concordance data. Results from three evaluations with language learners and teachers show positive attitudes towards this display.
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The tools of corpus linguistics have made it possible over the last few decades for researchers and lexicographers to access vast quantities of examples for specific search terms, and to discover and analyse patterns of language use. For more than 30 years, this usage-based approach to the analysis of language, drawing on corpora of increasing sizes, has had a huge impact on the way in which dictionaries are constructed (Hanks, 2012; Renouf, 2007). Corpora have also been used to explore the nature of language (Hanks, 2013; Hoey, 2005). Archives of transcripts and specially constructed corpora from child language research have been the basis for corpus work on first language acquisition within Usage Based Linguistics (Lieven, Behrens, Speares, & Tomasello, 2003; MacWhinney, 2000). Lists of words and multiword units have been used for the grading and selection of items in second language learning and teaching (Bauer & Nation, 1993; Coxhead, 2000; Durrant, 2009; Simpson-Vlach & Ellis, 2010). Corpora have been a basis for the analysis of lexical and grammatical differences across genres and registers (Biber & Conrad, 2009; Biber, Johansson, Leech, Conrad, & Finegan, 1999; Thompson, 2004), and in translation (Baker, 1993; Hu, 2016; Teubert, 2004). Corpora can also be used to compare patterns in literature or language as a whole or with those of a specific literary author (Fischer-Starcke, 2010; Mahlberg, 2013; Semino & Short, 2004). In the Chinese context, computerized corpus research has also covered a broad range of linguistic fields over the last few decades (Li & Smith, 2015). Work continues in a host of areas including exploring vocabulary for testing (Jin, Guo, Mak, & Wu, 2017) and discipline-specific teaching (M. Zhang, 2013), exploring China English (Xia, Xia, Zhang, & Nesi, 2016), exploring methods for extracting n-grams (Wei & Li, 2013), tracking changes in Chinese news media (W. Zhang, 2015), and building a system for opinion classification for Western news (Xiong, Xu, & Liang, 2014).

One of the central tools in corpus linguistics has been the concordance line, typically presented as Key Word in Context (KWIC), with each corpus example presented horizontally across the screen with a number of characters (letters) or words visible to the left and right. However, language teachers and language learners alike can find it hard, particularly at first, to understand how KWIC data can be used and interpreted. This paper presents the rationale and implementation of a complementary concordance line display format (Cards) which has been integrated into a new corpus tool (The Prime Machine) specifically designed with language teachers and language learners in mind. Feedback from teachers and students in three evaluations is reported, along with details of ongoing development and future plans.

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