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Qing-Ke Fu; Di Zou; Haoran Xie; Gary Cheng – Computer Assisted Language Learning, 2024
Automated writing evaluation (AWE) plays an important role in writing pedagogy and has received considerable research attention recently; however, few reviews have been conducted to systematically analyze the recent publications arising from the many studies in this area. The present review aims to provide a comprehensive analysis of the…
Descriptors: Journal Articles, Automation, Writing Evaluation, Feedback (Response)
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Sarré, Cédric; Grosbois, Muriel; Brudermann, Cédric – Computer Assisted Language Learning, 2021
Corrective feedback (CF) can be provided to learners in different ways (explicit or implicit, focused or unfocused) and is the subject of major controversies in second language acquisition research. As no clear consensus has been reached so far about the most effective approach to CF with a view to fostering accuracy in second language (L2)…
Descriptors: Blended Learning, Comparative Analysis, Second Language Learning, Second Language Instruction
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Chung, Eun Seon; Ahn, Soojin – Computer Assisted Language Learning, 2022
Many studies that have investigated the educational value of online machine translation (MT) in second language (L2) writing generally report significant improvements after MT use, but no study as of yet has comprehensively analyzed the effectiveness of MT use in terms of various measures in syntactic complexity, accuracy, lexical complexity, and…
Descriptors: Translation, Computational Linguistics, English (Second Language), Second Language Learning
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Guo, Qian; Feng, Ruiling; Hua, Yuanfang – Computer Assisted Language Learning, 2022
AWCF can facilitate academic writing development, especially for novice writers of English as a foreign language (EFL). Existing AWCF studies mainly focus on teacher and learner perceptions; fewer have investigated the error-correction effect of AWCF and factors related to the effect. Especially lacking is research on how successfully students can…
Descriptors: Error Correction, Feedback (Response), English (Second Language), Second Language Learning
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Ranalli, Jim – Computer Assisted Language Learning, 2018
Automated written corrective feedback (AWCF) has qualities that distinguish it from teacher-provided WCF and potentially undermine claims about its value for L2 student writers, including disparities in the amounts of useful information it provides across error types and the fact that inaccuracies in error-flagging must be anticipated. It remains…
Descriptors: Error Correction, Feedback (Response), Computer Assisted Instruction, Second Language Learning
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Jiang, Wei; Eslami, Zohreh R. – Computer Assisted Language Learning, 2022
Although the effectiveness of computer-mediated collaborative writing (CMCW) is confirmed by many recent studies, only a few have investigated whether linguistic knowledge and writing skills learned through collaboration can be internalized and transferred to individual writing. This study uses a pre-and post-test design to investigate the impact…
Descriptors: Collaborative Writing, English (Second Language), Second Language Learning, Second Language Instruction
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Ebadi, Saman; Rahimi, Masoud – Computer Assisted Language Learning, 2019
Drawing on Vygotskian sociocultural theory of mind and social constructivism, and adopting a sequential exploratory mixed-methods approach, this study explored the impact of online dynamic assessment (DA) on EFL learners' academic writing skills through one-on-one individual and online synchronous DA sessions over Google Docs. It also investigated…
Descriptors: English (Second Language), Language Tests, Second Language Learning, Sociocultural Patterns
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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