Induction from self-selected concordances and self-correction

Todd, Richard Watson

doi:10.1016/s0346-251x(00)00047-6

Cited by 71 publications

(50 citation statements)

References 9 publications

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“…A concordancer is software which extracts instances of a specific search word or search phrase from a corpus and presents these instances in their immediate linguistic context. The output is referred to as a concordance and can be used by language learners to learn about specific grammatical and lexical patterns in the L2 in a form of data-driven learning (Cobb, 1997;Gaskell & Cobb, 2004;Johns, 1994;Kaur & Hegelheimer, 2005;Milton, 2006;Shei, 2008aShei, , 2008bSun, 2003;Todd, 2001). According to Kaur and Hegelheimer (2005, p. 290), this type of data-driven learning can "help [students] become autonomous learners and also provide them the opportunity to act as researchers".…”

Section: Corpus-based Language Learningmentioning

confidence: 99%

“…Kaur & Hegelheimer, 2005;O'Sullivan & Chambers, 2006), but several other studies have examined the learning of lexico-grammar (e.g. Lee & Swales, 2006;Todd, 2001), and increasingly also grammar (Gaskell & Cobb, 2004;Liu & Jiang, 2009;Yoon & Hirvela, 2004). O'Sullivan and Chambers found that learners of L2 French could correct 19 of 25 preposition errors, and 22 of 28 word choice errors after instruction in corpus techniques.…”

Section: Corpus-based Language Learningmentioning

confidence: 99%

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Internet tools for language learning: University students taking control of their writing

Conroy¹

2010

AJET

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Many excellent corpus-based language learning resources (e.g., concordancers) have been freely available on the Internet for some time. Google assisted language learning (GALL) is also gaining increasing acceptance. These tools are a potential resource for English as an additional language (EAL) university students who want to independently improve their academic writing. However, many Australian universities have been remarkably slow to integrate these tools into English language support operations. In this study, Australian EAL university students were trained in Internet-based tools and techniques for language learning and subsequently surveyed on their attitudes and behaviour. Students' competence in using the tools and techniques to correct errors in their writing was also measured. The results revealed that students are enthusiastic and reasonably competent users of Internet-based tools and techniques for independent language learning. It is argued that Internet-based corpus tools and techniques are undervalued by Australian universities, but could be promoted and used to support EAL university student writers.

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Section: Corpus-based Language Learningmentioning

confidence: 99%

Section: Corpus-based Language Learningmentioning

confidence: 99%

Internet tools for language learning: University students taking control of their writing

Conroy¹

2010

AJET

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“…The findings of relevant studies revealed that consulting with corpus tools improved collocation and lexico-grammatical patterns of non-native students in their writing (Todd, 2001;Yoon & Hirvela, 2004;O'Sullivan & Chambers, 2006;Gilmore, 2009). However, little research has tracked the process of interaction with corpus consultation during scholarly writing to investigate the participant's cognitive processes and whether the corpus consultation has a possible effect on students' writing.…”

Section: Introductionmentioning

confidence: 99%

Online Corpus Tools in Scholarly Writing: A Case of EFL Postgraduate Student

Kotamjani¹,

Razavi²,

Hussin³

2017

ELT

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Some studies have reported the positive outcome of using concordancers and dictionaries in (ESL) context. This study aims to examine how an EFL writer consulted with concordancers and dictionaries along with Google and Google Scholar when engaging in academic writing at university level. The researcher investigated a non-English-major postgraduate student corpus consultation over five months. The researcher provided a toolkit including corpus tools; concordancers, collocation dictionaries, thesaurus, Google, in combination with traditional reference resources such as monolingual and bilingual online dictionaries. The participant received a three-session training to consult with different resources while writing research paper. Real-time data, stimulated recall interview, participants' writing and query logs served as the main sources of data. Results showed that the participant was aware of the applicability of each corpus tool. He could successfully solve 604 linguistic problems, and promoted his linguistic awareness. It is implied that corpus tools have the potential to assist EFL writers in proofreading and editing the surface levels of their writing.

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“…A number of researchers have proposed a small corpus for language learners given that the learning goals are those that smaller and specialized corpora might better serve (Bloch, 2009;Chambers, 2005;Flowerdew, 2004Flowerdew, , 2005Flowerdew, , 2009Kennedy & Miceli, 2001;Todd, 2001). Flowerdew (2005) demonstrated that small corpora serve pedagogical purposes better because the teachers can draw on examples closer to the students' needs.…”

Section: Tool Designmentioning

confidence: 99%

Using a stance corpus to learn about effective authorial stance-taking: a textlinguistic approach

Chang¹

2012

ReCALL

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Presenting a persuasive authorial stance is a major challenge for second language (L2) writers in writing academic research. Failure to present an effective authorial stance often results in poor evaluation, which compromises a writer's research potential. This study proposes a ''textlinguistic'' approach to advanced academic writing to complement a typical corpus approach that is oriented toward exploring lexico-grammatical patterns at the sentence level. A web-based stance corpus was developed which allowed the users to study both the linguistic realizations of stance at clause/sentence level and how stance meanings are made at the rhetorical move level. The assumptions the study tested included: (1) whether a textlinguistic approach assists L2 writers to polish their research argument particularly as a result of improved stance deployment, and (2) whether the web-based corpus tool affords a constructivist environment which prompts the learners to infer linguistic patterns to attain deeper understanding. Seven L2 doctoral students in the social sciences were recruited. The results indicate a positive relationship between writing performance and more accurate use of stance. However, the application of higher order cognitive skills (e.g., inferring and verifying) was infrequent in the corpus environment. Instead, the writers used more lower-level cognitive skills (e.g., making sense and exploring) to learn. The participants accessed the integrated ''context examples'' most frequently to guide their learning, followed by rhetorical ''move examples'' and clause-based ''stance examples''. This suggests that the learning of stance is critically contingent on the surrounding contexts. Overall, the study reveals that effective authorial stance-taking plays a critical role in effective academic argument. To better assist L2 academic writers, incorporating more (con)textual examples in computer corpora tools is recommended.

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Induction from self-selected concordances and self-correction

Cited by 71 publications

References 9 publications

Internet tools for language learning: University students taking control of their writing

Internet tools for language learning: University students taking control of their writing

Online Corpus Tools in Scholarly Writing: A Case of EFL Postgraduate Student

Using a stance corpus to learn about effective authorial stance-taking: a textlinguistic approach

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