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Yining Zhang; Binbin Zheng; Yuan Tian – Computer Assisted Language Learning, 2024
The use of text chat in synchronous computer-mediated communication (SCMC) could help remedy the widely reported lack of active involvement in online language learning. However, the nuances and complexities of learners' text-chat actions warrant further examination. This exploratory study used observational data collected from 40 students in a…
Descriptors: Synchronous Communication, Foreign Countries, Research Universities, English Language Learners
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Chen, Hao-Jan Howard; Lai, Shu-Li; Lee, Ken-Yi; Yang, Christine Ting-Yu – Computer Assisted Language Learning, 2023
Knowledge of collocations is essential for English academic writing. However, there are few academic collocation referencing tools available and there is a pressing need to develop more. In this paper, we will introduce the ACOP (Academic Collocations and Phrases Search Engine), a newly developed corpus-based tool to search large academic corpora.…
Descriptors: Academic Language, English for Academic Purposes, Phrase Structure, Computational Linguistics
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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
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Yeh, Hui-Chin – Computer Assisted Language Learning, 2015
Few studies have investigated how metacognitive processes foster the application of genre knowledge to students' academic writing. This is largely due to its internal and unobservable characteristics. To bridge this gap, an online writing system based on metacognition, involving the stages of planning, monitoring, evaluating, and revising, was…
Descriptors: Metacognition, Statistical Analysis, Academic Discourse, Sampling