NotesFAQContact Us
Collection
Advanced
Search Tips
Audience
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Showing 1 to 15 of 16 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Siowai Lo – Computer Assisted Language Learning, 2025
Neural Machine Translation (NMT) has gained increasing popularity among EFL learners as a CALL tool to improve vocabulary, and many learners have reported its helpfulness for vocabulary learning. However, while there has been some evidence suggesting NMT's facilitative role in improving learners' writing on the lexical level, no study has examined…
Descriptors: Translation, Computational Linguistics, Vocabulary Development, English (Second Language)
Peer reviewed Peer reviewed
Direct linkDirect link
Peichin Chang; Pin-Ju Chen; Li-Ling Lai – Computer Assisted Language Learning, 2024
Machine Translation (MT) tools have advanced to a level of reliability such that it is now opportune to consider their place in language teaching and learning. Given their potential, the current study sought to engage EFL university sophomores in recursive editing afforded by Google Translate (GT) for one semester, and investigated (1) whether the…
Descriptors: Editing, Computer Software, Artificial Intelligence, Translation
Peer reviewed Peer reviewed
Direct linkDirect link
Sabrina Girletti; Marie-Aude Lefer – Interpreter and Translator Trainer, 2024
In recent years, machine translation post-editing (MTPE or PE for short) has been steadily gaining ground in the language industry. However, studies that examine translators' perceptions of, and attitudes towards, MTPE paint a somewhat negative picture, with PE pricing methods and rates being a major source of dissatisfaction. While the European…
Descriptors: Translation, Teaching Methods, Language Processing, Second Language Instruction
Peer reviewed Peer reviewed
Direct linkDirect link
Lee, Yoo-Jean – ELT Journal, 2021
This study investigates the application of machine translation (MT) in an EFL writing class and its impact on lower proficiency level writers. Theoretically grounded in the social nature of learning, the MT-based writing class is applied to students in four steps: planning, drafting with MT, revising MT output, and individual writing with MT. The…
Descriptors: Translation, Second Language Learning, Second Language Instruction, English (Second Language)
Peer reviewed Peer reviewed
Direct linkDirect link
Kun Dai; Ian Hardy; Yuxiao Jiang – Higher Education Research and Development, 2025
An increasing number of international students pursue doctoral studies in China, a non-traditional learning destination compared with English-dominated Western countries. Despite considerable research on the challenges doctoral students face when writing theses in English in Western countries, relatively few studies have explored comparable issues…
Descriptors: Foreign Countries, Doctoral Students, Doctoral Dissertations, Writing (Composition)
Peer reviewed Peer reviewed
Direct linkDirect link
Loboda, Krzysztof; Mastela, Olga – Interpreter and Translator Trainer, 2023
Mass adoption of neural machine translation (NMT) tools in the translation workflow has exerted a significant impact on the language services industry over the last decade. There are claims that with the advent of NMT, automated translation has reached human parity for translating news (see, e.g. Popel et al. 2020). Moreover, some machine…
Descriptors: Computer Software, Computational Linguistics, Polish, Folk Culture
Peer reviewed Peer reviewed
Direct linkDirect link
Dongkawang Shin; Yuah V. Chon – Language Learning & Technology, 2023
Considering noticeable improvements in the accuracy of Google Translate recently, the aim of this study was to examine second language (L2) learners' ability to use post-editing (PE) strategies when applying AI tools such as the neural machine translator (MT) to solve their lexical and grammatical problems during L2 writing. This study examined 57…
Descriptors: Second Language Learning, Second Language Instruction, Translation, Computer Software
Peer reviewed Peer reviewed
Direct linkDirect link
Öner Bulut, Senem; Alimen, Nilüfer – Interpreter and Translator Trainer, 2023
Motivated by the urgent need to investigate the possibilities for re-positioning the human translator and his/her educator in the machine translation (MT) age, this article explores the dynamics of the human-machine dance in the translation classroom. The article discusses the results of a collaborative learning experiment which was conducted in…
Descriptors: Translation, Teaching Methods, Self Efficacy, Second Languages
Peer reviewed Peer reviewed
Direct linkDirect link
Yang, Yanxia; Wang, Xiangling – Interactive Learning Environments, 2023
Machine translation post-editing (MTPE) has become a common practice in translation industry, which calls much attention in academia. However, little research has been carried out to investigate students' cognitive and motivational individual differences in MTPE. The purpose of the present study was to examine the predictive effects of…
Descriptors: Translation, Computational Linguistics, Second Languages, Language Usage
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Abdulaal, Mohammad Awad Al-Dawoody – Journal of Language and Linguistic Studies, 2022
This research study aims at drawing a comparison between some internet emerging applications used for machine translation (MT) and a human translation (HT) to two of Alphonse Daudet's short stories: "The Siege of Berlin" and "The Bad Zouave." The automatic translation has been carried out by four MT online applications (i.e.…
Descriptors: Translation, Literature, Syntax, Computational Linguistics
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Olkhovska, Alla; Frolova, Iryna – Advanced Education, 2020
This paper outlines the results of the experimental study aiming to explore the impact of using machine translation engines on the performance of translation students. Machine translation engines refer to the software developed to translate source texts into target languages in a fully automatic mode which can be classified according to the…
Descriptors: Translation, Computational Linguistics, English (Second Language), Second Language Learning
Al-Jarf, Reima – Online Submission, 2021
The College of Languages and Translation (COLT) prepares translators and interpreters. Some of the courses that the students take are language courses such as listening, speaking, reading, writing, vocabulary, grammar, and 4 types of interpreting courses (simultaneous, consecutive, liaison and sight). COLT has installed 4 multimedia language labs…
Descriptors: Language Laboratories, Second Language Learning, Second Language Instruction, Translation
Peer reviewed Peer reviewed
Direct linkDirect link
Rodríguez-Castro, Mónica – Interpreter and Translator Trainer, 2018
Increasing project complexity and a high level of specialization in the language industry have resulted in a demand for translation professionals with sophisticated technical skills. This has made computer-assisted translation (CAT) tools indispensable for translators in order to meet project requirements. With a rapidly changing industry…
Descriptors: Translation, Computational Linguistics, Outcomes of Education, Teaching Methods
Peer reviewed Peer reviewed
Direct linkDirect link
Moorkens, Joss – Interpreter and Translator Trainer, 2018
Machine translation is currently undergoing a paradigm shift from statistical to neural network models. Neural machine translation (NMT) is difficult to conceptualise for translation students, especially without context. This article describes a short in-class evaluation exercise to compare statistical and neural MT, including details of student…
Descriptors: Translation, Teaching Methods, Computational Linguistics, Quality Assurance
Peer reviewed Peer reviewed
Loffler-Laurian, Anne-Marie – Babel: International Journal of Translation, 1985
Machine translation has been criticized for its inability to provide language style, but for specialized or technical texts, of which there are increasing numbers, machine translation with its obligatory post-editing may be effective, and the "style" of these translations may be a reflection of the error patterns caught in post-editing. (MSE)
Descriptors: Comparative Analysis, Computer Software, Editing, Error Patterns
Previous Page | Next Page »
Pages: 1  |  2