Analysing corpus-based criterial conjunctions for automatic proficiency classification

Authors

DOI:

https://doi.org/10.18172/jes.3090

Keywords:

Cohesion, language assessment, corpus linguistics, L2 English learning texts, linguistic profiling, Coh-Metrix.

Abstract

The linguistic profiling of L2 learning texts can be taken as a model for automatic proficiency assessment of new texts. But proficiency levels are distinguished by many different linguistic features among which the use of cohesive devices can be a criterial element for level distinctions, either in the number of conjunctions used (quantitative) and/or in the type and variety of them (qualitative). We have carried such an analysis with a subgroup of the CLEC (CEFR-levelled English Corpus) using Coh-Metrix, a tool for computing computational cohesion and coherence metrics for written and spoken texts, but our results suggest that automatic proficiency level assessment needs a deeper examination of conjunctions that should rely on the analysis of conjunction-types use and conjunction varieties, with an analysis of lexical choice. A variable based on familiarity ranks could help to predict cohesive levels proficiencyoriented.

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Author Biographies

Ángeles Zarco-Tejada, University of Cádiz

Department of French and English Philology.

Institute of Applied Linguistics (ILA).

Senior Lecturer

 

Carmen Noya Gallardo, University of Cádiz

Department of French and English Philology.

Senior Lecturer

Mª Carmen Merino Ferradá, University of Cádiz

Department of French and English Philology.

Institute of Applied Linguistics (ILA).

Full-time Lecturer

Isabel Calderón López, University of Cádiz

Department of French and English Philology.

Full-time Lecturer

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Published

16-12-2016

How to Cite

Zarco-Tejada, Ángeles, Noya Gallardo, C., Merino Ferradá, M. C., & Calderón López, I. (2016). Analysing corpus-based criterial conjunctions for automatic proficiency classification. Journal of English Studies, 14, 215–237. https://doi.org/10.18172/jes.3090

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