Multi‐Word Expressions in Second Language Writing: A Large‐Scale Longitudinal Learner Corpus Study

© 2019 Language Learning Research Club, University of Michigan In the present study, we sought to advance the field of learner corpus research by tracking the development of phrasal vocabulary in essays produced at two different points in time. To this aim, we employed a large pool of second language (L2) learners (N = 175) from three proficiency levels—beginner, elementary, and intermediate—and focused on an underrepresented L2 (Italian). Employing mixed-effects models, a flexible and powerful tool for corpus data analysis, we analyzed learner combinations in terms of five different measures: phrase frequency, mutual information, lexical gravity, delta Pforward, and delta Pbackward. Our findings suggest a complex picture, in which higher proficiency and greater exposure to the L2 do not result in more idiomatic and targetlike output, and may, in fact, result in greater reliance on low frequency combinations whose constituent words are non-associated or mutually attracted.

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Multi-Word Expressions in Second Language Writing: A Large-Scale Longitudinal Learner Corpus Study

10.26686/wgtn.13670590.v1 ◽

2021 ◽

Author(s):

Anna Siyanova ◽

S Spina

Keyword(s):

Second Language ◽

Language Learning ◽

Large Scale ◽

Second Language Writing ◽

Low Frequency ◽

University Of Michigan ◽

Corpus Study ◽

Learner Corpus ◽

Language Writing ◽

Complex Picture

© 2019 Language Learning Research Club, University of Michigan In the present study, we sought to advance the field of learner corpus research by tracking the development of phrasal vocabulary in essays produced at two different points in time. To this aim, we employed a large pool of second language (L2) learners (N = 175) from three proficiency levels—beginner, elementary, and intermediate—and focused on an underrepresented L2 (Italian). Employing mixed-effects models, a flexible and powerful tool for corpus data analysis, we analyzed learner combinations in terms of five different measures: phrase frequency, mutual information, lexical gravity, delta Pforward, and delta Pbackward. Our findings suggest a complex picture, in which higher proficiency and greater exposure to the L2 do not result in more idiomatic and targetlike output, and may, in fact, result in greater reliance on low frequency combinations whose constituent words are non-associated or mutually attracted.

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The Development of Second Language Writing Complexity in Groups and Individuals: A Longitudinal Learner Corpus Study

Modern Language Journal ◽

10.1111/j.1540-4781.2012.01401.x ◽

2012 ◽

Vol 96 (4) ◽

pp. 576-598 ◽

Cited By ~ 40

Author(s):

NINA VYATKINA

Keyword(s):

Second Language ◽

Second Language Writing ◽

Corpus Study ◽

Learner Corpus ◽

Writing Complexity ◽

Language Writing

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Differences Across Levels in the Language of Agency and Ability in Rating Scales for Large-Scale Second Language Writing Assessments

Studia Anglica Posnaniensia ◽

10.1515/stap-2017-0006 ◽

2017 ◽

Vol 52 (2) ◽

pp. 147-172

Author(s):

Salena Sampson Anderson

Keyword(s):

Second Language ◽

Writing Assessment ◽

Large Scale ◽

Second Language Writing ◽

Rating Scales ◽

Reliability And Validity ◽

College Level ◽

Writing Assessments ◽

The Public ◽

Language Writing

Abstract While large-scale language and writing assessments benefit from a wealth of literature on the reliability and validity of specific tests and rating procedures, there is comparatively less literature that explores the specific language of second language writing rubrics. This paper provides an analysis of the language of performance descriptors for the public versions of the TOEFL and IELTS writing assessment rubrics, with a focus on linguistic agency encoded by agentive verbs and language of ability encoded by modal verbs can and cannot. While the IELTS rubrics feature more agentive verbs than the TOEFL rubrics, both pairs of rubrics feature uneven syntax across the band or score descriptors with either more agentive verbs for the highest scores, more nominalization for the lowest scores, or language of ability exclusively in the lowest scores. These patterns mirror similar patterns in the language of college-level classroom-based writing rubrics, but they differ from patterns seen in performance descriptors for some large-scale admissions tests. It is argued that the lack of syntactic congruity across performance descriptors in the IELTS and TOEFL rubrics may reflect a bias in how actual student performances at different levels are characterized.

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Explaining the orthography–phonology interface in written corpora: an Optimality–Theoretic approach

Corpora ◽

10.3366/cor.2017.0116 ◽

2017 ◽

Vol 12 (2) ◽

pp. 181-205

Author(s):

Yasemin Yildiz

Keyword(s):

Second Language ◽

Optimality Theory ◽

Second Language Writing ◽

Descriptive Analysis ◽

Theoretic Approach ◽

Writing Systems ◽

Spelling Errors ◽

Learner Corpus ◽

Learner Corpora ◽

Language Writing

This paper has two goals. The first goal is to contribute to the literature of Second Language Writing Systems (L2WS) by focussing on the British University in Dubai (BUiD) and the Arab Learner Corpus (BALC). The second is to demonstrate the close orthography–phonology interface in L2WS and critically address the issue of reform in a script. Unlike previous studies, which provide a holistic and descriptive analysis of all possible spelling errors of Arab learners of English (e.g., Haggan, 1991 ; and Randall and Groom, 2009 ), this study is different in two ways. First, BALC will be interpreted within a markedness framework and a constraint-based theory known as Optimality Theory. Second, particular emphasis will be given to the erroneous spelling forms which appear in lexical items exclusively with complex onset and coda clusters at the phonological level. The motive for this study is to look beyond spelling errors and bridge linguistic theory with learner corpora. The sub-corpora will be identified and categorised by using the Wmatrix3 program ( Rayson, 2003 , 2005 ). The fulfilment of the above goals will provide new insights for researchers and teachers who are working closely in the areas of L2WS and learner corpora.

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