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Computer-assisted detection of 90% of EFL student errors

Authors :
Calum Harvey-Scholes
Source :
Computer Assisted Language Learning. 31:144-156
Publication Year :
2017
Publisher :
Informa UK Limited, 2017.

Abstract

Software can facilitate English as a Foreign Language (EFL) students’ self-correction of their free-form writing by detecting errors; this article examines the proportion of errors which software can detect. A corpus of 13,644 words of written English was created, comprising 90 compositions written by Spanish-speaking students at levels A2-B2 (inclusive) of the Common European Framework. A total of 1,310 language errors were detected by the researcher. It was found that approximately 21% of these errors were spelling errors. A further 58% were characterised as either two-word phrases (45%), three-word phrases (9%), or four- and five-word phrases (4%) which are either absent from or rare in a large corpus of English which is known to be correct. The nature of software which can detect such words and phrases and bring them to students’ attention with a view to self-correction is briefly described. Of the remaining 21% of errors not detected by such software, most were found to be either errors of te...

Details

ISSN :
17443210 and 09588221
Volume :
31
Database :
OpenAIRE
Journal :
Computer Assisted Language Learning
Accession number :
edsair.doi...........293970ce4594453555bcf98e661d34c1
Full Text :
https://doi.org/10.1080/09588221.2017.1392322