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Harvey-Scholes, Calum – Computer Assisted Language Learning, 2018
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…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Error Correction
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Floyd, Simeon; Manrique, Elizabeth; Rossi, Giovanni; Torreira, Francisco – Discourse Processes: A multidisciplinary journal, 2016
This article expands the study of other-initiated repair in conversation--when one party signals a problem with producing or perceiving another's turn at talk--into the domain of visual bodily behavior. It presents one primary cross-linguistic finding about the timing of visual bodily behavior in repair sequences: if the party who initiates repair…
Descriptors: Interpersonal Communication, Error Correction, Sign Language, American Indian Languages
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Crosthwaite, Peter – Computer Assisted Language Learning, 2017
An increasing number of studies have looked at the value of corpus-based data-driven learning (DDL) for second language (L2) written error correction, with generally positive results. However, a potential conundrum for language teachers involved in the process is how to provide feedback on students' written production for DDL. The study looks at…
Descriptors: Feedback (Response), Error Correction, Morphology (Languages), Syntax
El-Banna, Adel I.; Naeem, Marwa A. – Online Submission, 2016
This research work aimed at making use of Machine Translation to help students avoid some syntactic, semantic and pragmatic common errors in translation from English into Arabic. Participants were a hundred and five freshmen who studied the "Translation Common Errors Remedial Program" prepared by the researchers. A testing kit that…
Descriptors: Computational Linguistics, Translation, Statistical Analysis, Syntax
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Forti, Luciana – Research-publishing.net, 2017
This paper looks at how corpus data was used to design an Italian as an L2 language learning programme and how it was evaluated by students. The study focuses on the acquisition of Italian verb-noun collocations by Chinese native students attending a ten month long Italian language course before enrolling at an Italian university. It describes how…
Descriptors: Italian, Phrase Structure, Second Language Learning, Questionnaires
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Chukharev-Hudilainen, Evgeny; Saricaoglu, Aysel – Computer Assisted Language Learning, 2016
Expressing causal relations plays a central role in academic writing. While it is important that writing instructors assess and provide feedback on learners' causal discourse, it could be a very time-consuming task. In this respect, automated writing evaluation (AWE) tools may be helpful. However, to date, there have been no AWE tools capable of…
Descriptors: Discourse Analysis, Feedback (Response), Undergraduate Students, Accuracy
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Alshaar, Awatif Abu; AbuSeileek, Ali Farhan – JALT CALL Journal, 2013
This study aims to investigate the effect of using concordances and word processors on EFL graduates' performance in academic writing. To achieve this aim, the subjects were asked to use linguistics corpora and word processors to correct their grammatical and spelling mistakes in their written papers in a course that lasted for sixteen weeks. The…
Descriptors: Computational Linguistics, English (Second Language), Second Language Learning, Semi Structured Interviews
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Thouësny, Sylvie – Research-publishing.net, 2011
In contrast to standardised assessment, dynamic assessment (DA) simultaneously combines teaching and assessment activities. The key difference between standardised and dynamic approaches lies in the fact that, in the latter, an expert is allowed to provide assistance to a novice during the assessment process. Mediation, whether in the form of…
Descriptors: French, Second Language Learning, Second Language Instruction, Computational Linguistics