Investigating the use of readability metrics to detect differences in written productions of learners: a corpus-based study

This paper deals with the use of readability metrics as indices of learmers' linguistic features in a written corpus of Spanish learners of English L2. Seventeen measures of readability are presented and computed for 200 samples of written argumentative essays extracted from the corpus NOCE (D...

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Autor principal:	Paula Lissón
Formato:	article
Lenguaje:	CA EN ES FR
Publicado:	Universitat Autònoma de Barcelona 2017
Materias:	readability learner corpora SVM written essays Special aspects of education LC8-6691 Language and Literature P
Acceso en línea:	https://doaj.org/article/611cc65aa7c24aeb86f29ffb61abe526
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spelling	oai:doaj.org-article:611cc65aa7c24aeb86f29ffb61abe5262021-11-25T13:20:19ZInvestigating the use of readability metrics to detect differences in written productions of learners: a corpus-based study10.5565/rev/jtl3.7522013-6196https://doaj.org/article/611cc65aa7c24aeb86f29ffb61abe5262017-12-01T00:00:00Zhttps://revistes.uab.cat/jtl3/article/view/752https://doaj.org/toc/2013-6196 This paper deals with the use of readability metrics as indices of learmers' linguistic features in a written corpus of Spanish learners of English L2. Seventeen measures of readability are presented and computed for 200 samples of written argumentative essays extracted from the corpus NOCE (Díaz-Negrillo, 2007). Support Vector Machines (SVM) are used in order to detect which are the metrics that perform better at detecting differences in learners’ productions belonging to students enrolled in the first or in the second year of an English major. Metrics based on sentence length, number of sentences, and number of polysyllabic words are reported to be the most accurate ones for the classification of learners' linguistic features. Paula LissónUniversitat Autònoma de Barcelonaarticlereadabilitylearner corporaSVMwritten essaysSpecial aspects of educationLC8-6691Language and LiteraturePCAENESFRBellaterra Journal of Teaching & Learning Language & Literature, Vol 10, Iss 4 (2017)
institution	DOAJ
collection	DOAJ
language	CA EN ES FR
topic	readability learner corpora SVM written essays Special aspects of education LC8-6691 Language and Literature P
spellingShingle	readability learner corpora SVM written essays Special aspects of education LC8-6691 Language and Literature P Paula Lissón Investigating the use of readability metrics to detect differences in written productions of learners: a corpus-based study
description	This paper deals with the use of readability metrics as indices of learmers' linguistic features in a written corpus of Spanish learners of English L2. Seventeen measures of readability are presented and computed for 200 samples of written argumentative essays extracted from the corpus NOCE (Díaz-Negrillo, 2007). Support Vector Machines (SVM) are used in order to detect which are the metrics that perform better at detecting differences in learners’ productions belonging to students enrolled in the first or in the second year of an English major. Metrics based on sentence length, number of sentences, and number of polysyllabic words are reported to be the most accurate ones for the classification of learners' linguistic features.
format	article
author	Paula Lissón
author_facet	Paula Lissón
author_sort	Paula Lissón
title	Investigating the use of readability metrics to detect differences in written productions of learners: a corpus-based study
title_short	Investigating the use of readability metrics to detect differences in written productions of learners: a corpus-based study
title_full	Investigating the use of readability metrics to detect differences in written productions of learners: a corpus-based study
title_fullStr	Investigating the use of readability metrics to detect differences in written productions of learners: a corpus-based study
title_full_unstemmed	Investigating the use of readability metrics to detect differences in written productions of learners: a corpus-based study
title_sort	investigating the use of readability metrics to detect differences in written productions of learners: a corpus-based study
publisher	Universitat Autònoma de Barcelona
publishDate	2017
url	https://doaj.org/article/611cc65aa7c24aeb86f29ffb61abe526
work_keys_str_mv	AT paulalisson investigatingtheuseofreadabilitymetricstodetectdifferencesinwrittenproductionsoflearnersacorpusbasedstudy
_version_	1718413438906007552

Investigating the use of readability metrics to detect differences in written productions of learners: a corpus-based study

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