24.4385, Calls: Language Acquisition, Text/Corpus Linguistics/Poland

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LINGUIST List: Vol-24-4385. Mon Nov 04 2013. ISSN: 1069 - 4875.

Subject: 24.4385, Calls: Language Acquisition, Text/Corpus Linguistics/Poland

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Date: Mon, 04 Nov 2013 15:02:40
From: Cristóbal Lozano [interlanguageannotation at gmail.com]
Subject: Interlanguage Annotation

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Full Title: Interlanguage Annotation 
Short Title: ILA 

Date: 11-Sep-2014 - 14-Sep-2014
Location: Poznań, Poland 
Contact Person: Cristóbal Lozano
Meeting Email: interlanguageannotation at gmail.com

Linguistic Field(s): Language Acquisition; Text/Corpus Linguistics 

Call Deadline: 20-Nov-2013 

Meeting Description:

Interlanguage Annotation (ILA): From Sla Research to Learner Corpus Research

Much of the annotation undertaken in learner corpora to date has been error annotation and has had a pedagogical orientation. This thematic session focuses, however, on a type of learner corpus annotation which does not describe errors but learners' interlanguage, that has recently been referred to as 'InterLanguage Annotation (ILA)' (Díaz-Negrillo & Lozano 2013), and which is defined in the terms described below.

Grounded on common annotation practices in LCR, as well as SLA hypothesis-driven rich annotation schemes used in corpus-based L2 studies (e.g., Gudmestad et al. 2013, Lozano 2009, inter alia), ILA is a type of annotation that is designed to test specific features of learners' interlanguage and, therefore, that can serve to answer questions formulated in SLA research. It is a type of tagging that (i) is purpose-oriented, (ii) is fine-grained, (iii) describes learners' interlanguage by covering both learners' errors and also their correct uses, and that (iv) is theory-motivated. 

This type of annotation can help answer SLA theoretical questions in more sophisticated ways than previous error annotation research because it is designed to investigate a specific interlanguage phenomenon (purpose-oriented), and to answer specific research questions/hypotheses (theory-motivated) about what cannot be acquired and also what is actually acquired (learners' interlanguage). This is done so by taking into account previous L2 findings before constructing the tagging scheme and by categorising subtle linguistic properties in the annotation scheme (fine-grained).

References:

Díaz-Negrillo, A. & Lozano, C. (2013). Using learner corpus tools in SLA research: the morpheme order studies revisited', Paper presented at Corpus Linguistics 2013, University of Lancaster (UK).
Lozano, C. (2009). Selective deficits at the syntax-discourse interface: Evidence from the CEDEL2 corpus. In: Snape, N., Leung, Y.I., & Sharwood-Smith, M. (eds). Representational Deficits in SLA. Amsterdam: John Benjamins.
Gudmestad, A., House, Leanna, and Geeslin, Kimberly L. (2013). What a bayesian analysis can do for SLA: New tools for the sociolinguistic study of subject expression in L2 Spanish. Language Learning 63(3): 371-399.

Call for Papers:

We invite submissions of papers covering the following:

- Purpose-oriented annotation schemes/tagsets for the analysis of SLA research questions. 
- Architectures used for fine-grained learner corpus annotation.
- SLA studies based on finely-grained annotated learner corpora. 

Keywords: Learner corpora, SLA research, interlanguage grammars, fine-grained annotation schemes, purpose-oriented annotation, theory-motivated annotation, annotation architectures, hypothesis-testing corpus approaches.

Submission Guidelines: 

Abstracts should be of max. 300 words (excluding references), and they should clearly specify the research questions, the method and the expected results. Please, send your abstract in an attached modifiable file to the following address: interlanguageannotation at gmail.com.

Please note that if the workshop is selected for SLE2014 Conference, 500-word abstracts will have to be submitted to the conference scientific committee by 15 January 2014.

Submission deadline: 20 November 2013
Notification of acceptance: 30 November 2013

Workshop Organizer:

Cristóbal Lozano







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