MA of L2 learner English

Corpus Linguistics 2015, University of Lancaster, 21-24 July

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Yu Yuan:
“Exploring the variation in world Learner Englishes: A multidimensional analysis of L2 written corpora”

109 features included in the analysis

RQ:

Can Biber’s model be extended?

How do features co-occur in learner English?

 

Data

ICLE 1.0 (Granger, 2002)

SWEECL 2.0 (Wen & Wang, 2008)

 

Tools

MA tagger Nini (2014) Manual here. Software (Windows) here.

Stanford Corenlp

R

Pythin scripts

 

Method

Kaisser’s criteria + Scree test for Factor Analysis

 

Results

10 dimensions stand out

Dimensions are largely epistemological, rhetorical and syntactical.

 

Native & learner language in interviews

This talk discusses some of our findings in

Pérez-Paredes, P., & Sánchez Tornel, M. (2015). A multidimensional analysis of learner language during story reconstruction in interviews. In M. Callies & S. Götz (Eds.), Learner Corpora in Language Testing and Assessment. Amsterdam: John Benjamins.

 

Learner Corpora in Language Testing and Assessment

Edited by Marcus Callies and Sandra Götz
University of Bremen / Justus Liebig University, Giessen
ISBN 9789027203786 
The aim of this volume is to highlight the benefits and potential of using learner corpora for the testing and assessment of L2 proficiency in both speaking and writing, reflecting the growing importance of learner corpora in applied linguistics and second language acquisition research. Identifying several desiderata for future research and practice, the volume presents a selection of original studies, covering a variety of different languages. It features studies that present very thoroughly compiled new corpus resources which are tailor-made and ready for analysis in LTA, new tools for the automatic assessment of proficiency levels, and new methods of (self-)assessment with the help of learner corpora. Other studies suggest innovative research methodologies of how proficiency can be operationalized through learner corpus data. The volume is of particular interest to researchers in (applied) corpus linguistics, learner corpus research, language testing and assessment, as well as for materials developers and language teachers.
Learner corpora in language testing and assessment: Prospects and challenges
Marcus Callies and Sandra Götz
1 – 10
New corpus resources, tools and methods. The Marburg Corpus of Intermediate Learner English (MILE)
Rolf Kreyer
13 – 34
Avalingua : Natural language processing for automatic error detection
Pablo Gamallo Otero, Marcos Garcia, Iria del Río and Isaac González López
35 – 58
Data commentary in science writing: Using a small, specialized corpus for formative self-assessment practices
Lene Nordrum and Andreas Eriksson
59 – 84
First steps in assigning proficiency to texts in a learner corpus of computer-mediated communication
Tim Marchand and Sumie Akutsu
85 – 112
Data-driven approaches to the assessment of proficiency
The English Vocabulary Profile as a benchmark for assigning levels to learner corpus data
Agnieszka Lenko-Szymanska
115 – 140
A multidimensional analysis of learner language during story reconstruction in interviews
Pascual Pérez-Paredes and María Sánchez-Tornel
141 – 162
Article use and criterial features in Spanish EFL writing: A pilot study from CEFR A2 to B2 levels
María Belén Díez-Bedmar
163 – 190
Tense and aspect errors in spoken learner English: Implications for language testing and assessment
Sandra Götz
191 – 216

LINDSEI: the Turkish component

LINDSEI-TR: A New Spoken Corpus of Advanced Learners of English
By Abdurrahman Kilimci

Cukurova University, Faculty of Education, English Language Teaching Department, Balcalı, Adana, Turkey

Abstract

The aim of the present study is to describe the LINDSEI-TR, the Turkish component of the LINDSEI (the Louvain International Database of Spoken English), which was initiated to compile a corpus of spoken data produced by learners from varied mother tongues (Gilquin et al., 2010). In this respect, the main objective of the study is to present the aim, development, and the design criteria of the corpus along with its quantitative and qualitative characteristics. The corpus is considered to be of value to researchers in terms of delineating the features of learners’ spoken interlanguage and designing teaching materials to improve second language teaching and learning.

Keywords: Corpus linguistics, spoken corpus, interlanguage, second language teaching and learning

#corpusMOOC Corpus Linguistics: Method, Analysis, Interpretation starts Sept 29

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