Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 2 |
Since 2016 (last 10 years) | 4 |
Since 2006 (last 20 years) | 5 |
Descriptor
Source
Computer Assisted Language… | 5 |
Author
Brudermann, Cédric | 1 |
Chang, J. S. | 1 |
Chen, M.-H. | 1 |
Chukharev-Hudilainen, Evgeny | 1 |
Grosbois, Muriel | 1 |
Huang, S.-T. | 1 |
Liou, H.-C. | 1 |
Ranalli, Jim | 1 |
Saricaoglu, Aysel | 1 |
Sarré, Cédric | 1 |
Schenker, Theresa | 1 |
More ▼ |
Publication Type
Journal Articles | 5 |
Reports - Research | 5 |
Tests/Questionnaires | 1 |
Education Level
Higher Education | 5 |
Postsecondary Education | 5 |
Audience
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
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
Schenker, Theresa – Computer Assisted Language Learning, 2021
The present study investigated the effects of group set-up in a semester-long telecollaborative discussion forum project in second-semester German. In order to explore whether group set-up affects learning in discussion forums, small groups of non-native speakers (NNS) of German were partnered either with native speakers (NS), other NNS with the…
Descriptors: Group Discussion, Computer Mediated Communication, Teaching Methods, Native Speakers
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
Chen, M.-H.; Huang, S.-T.; Chang, J. S.; Liou, H.-C. – Computer Assisted Language Learning, 2015
Paraphrasing, or restating information using different words, is critical to successful writing. However, EFL learners have difficulty in making paraphrases to meet their writing demands, and there has been little research on developing automatic reference tools to assist these learners' paraphrasing skills for better writing quality. In this…
Descriptors: English (Second Language), Second Language Learning, Computational Linguistics, Dictionaries
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