2016
DOI: 10.1515/iral-2016-0121
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Effect of corrective feedback for learning verb second

Abstract: This paper presents a detailed study on the role of corrective feedback (CF) in the development of second language (L2) oral proficiency. Learners practiced speaking with a computer-assisted language learning (CALL) system that employs automatic speech recognition (ASR) technology to provide CF. The system tracks learner behaviour by logging the system-user interactions. Two language learning conditions are compared. In the CF condition learners received immediate, automatic CF on the grammaticality of their s… Show more

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Cited by 3 publications
(4 citation statements)
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“…While in the CF condition the higher number of spoken attempts and of grammatically correct utterances (OKs) had a beneficial effect in addition to the CF messages that alerted learners to errors, the absence of an additional effect of CF is remarkable. In a previous study with a similar setup the CF condition outperformed the NOCF condition (Penning de Vries et al, 2016). A crucial difference with that study is that those participants were high educated.…”
Section: Discussionmentioning
confidence: 85%
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“…While in the CF condition the higher number of spoken attempts and of grammatically correct utterances (OKs) had a beneficial effect in addition to the CF messages that alerted learners to errors, the absence of an additional effect of CF is remarkable. In a previous study with a similar setup the CF condition outperformed the NOCF condition (Penning de Vries et al, 2016). A crucial difference with that study is that those participants were high educated.…”
Section: Discussionmentioning
confidence: 85%
“…In meaning-based conversation, a V2 error will not result in communication problems. Our earlier study with high-educated participants working with GREET found that the CF condition was rated more positively (Penning de Vries et al, 2016). The current study showed a similar trend among HE learners.…”
Section: Discussionmentioning
confidence: 97%
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“…With the recent rapid advancements in machine learning and artificial intelligence, the field of technology‐assisted language learning has seen an increased focus on speech‐to‐text recognition and automated corrective feedback techniques (Aluthman, 2016; de Vries et al, 2016; Fichten et al, 2000; Konur, 2007; Kukulska‐Hulme et al, 2004). Speech‐to‐text recognition refers to a tool that can accurately transcribe speech input into text, which is then displayed on a whiteboard or computer screen for students (Ryba et al, 2006; Wald & Bain, 2008).…”
Section: Introductionmentioning
confidence: 99%