Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 2 |
| Since 2017 (last 10 years) | 4 |
| Since 2007 (last 20 years) | 6 |
Descriptor
Source
| Language Learning & Technology | 2 |
| International Journal of… | 1 |
| Modern Language Journal | 1 |
| Online Learning | 1 |
| Research-publishing.net | 1 |
Author
| Aubrey, Scott | 1 |
| Berglund, Therese Örnberg | 1 |
| Earnshaw, Yvonne | 1 |
| Frumuselu, Anca Daniela | 1 |
| Godwin-Jones, Robert | 1 |
| Gutiérrez-Colón, Mar | 1 |
| Ranalli, Jim | 1 |
| Shintani, Natsuko | 1 |
| Soria, Sara | 1 |
| Yamashita, Taichi | 1 |
Publication Type
| Journal Articles | 5 |
| Reports - Research | 5 |
| Reports - Evaluative | 1 |
| Speeches/Meeting Papers | 1 |
Audience
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Direct linkGodwin-Jones, Robert – Language Learning & Technology, 2022
In recent years, advances in artificial intelligence (AI) have led to significantly improved, or in some cases, completely new digital tools for writing. Systems for writing assessment and assistance based on automated writing evaluation (AWE) have been available for some time. That is the case for machine translation as well. More recent are…
Descriptors: Writing Instruction, Artificial Intelligence, Feedback (Response), Writing Evaluation
Ranalli, Jim; Yamashita, Taichi – Language Learning & Technology, 2022
To the extent automated written corrective feedback (AWCF) tools such as Grammarly are based on sophisticated error-correction technologies, such as machine-learning techniques, they have the potential to find and correct more common L2 error types than simpler spelling and grammar checkers such as the one included in Microsoft Word (technically…
Descriptors: Error Correction, Feedback (Response), Computer Software, Second Language Learning
Download full textSoria, Sara; Gutiérrez-Colón, Mar; Frumuselu, Anca Daniela – International Journal of Instruction, 2020
Mobile assisted language learning (MALL) has developed and gained importance over the years in foreign language learning settings. However, mobile phones are still perceived as distracting devices in most of the schools. Within the field of second and foreign language learning, one of the most difficult things for school teachers is to give…
Descriptors: Computer Software, Telecommunications, Handheld Devices, Second Language Learning
Earnshaw, Yvonne – Online Learning, 2017
In face-to-face conversations, speaker transitions (or hand-offs) are typically seamless. In computer-mediated communication settings, speaker hand-offs can be a bit more challenging. This paper presents the results of a study of audio communication problems that occur in an online synchronous course, and how, and by whom, those problems are…
Descriptors: Graduate Students, Discourse Analysis, Computer Mediated Communication, Computer Software
Shintani, Natsuko; Aubrey, Scott – Modern Language Journal, 2016
This study extends research on written corrective feedback (CF) by investigating how timing of CF affects grammar acquisition. Specifically, it examined the relative effects of synchronous and asynchronous CF on the accurate use of the hypothetical conditional structure. Participants were 68 intermediate-level students of English at a university…
Descriptors: Error Correction, Feedback (Response), English (Second Language), Second Language Learning
Berglund, Therese Örnberg – Research-publishing.net, 2012
This paper discusses the concept of "noticing" (Schmidt, 1990; cf. Smith, 2010) in relation to text-based second language interaction (instant messaging). Data has been collected at an upper secondary school, where students of English as a foreign language interact with the researcher, providing feedback on language and content. In…
Descriptors: Error Correction, Second Language Learning, Synchronous Communication, Secondary School Students
