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Showing 1 to 15 of 26 results Save | Export
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Byrd, Antonio – Composition Studies, 2023
The concept 'literacy crisis' has framed ChatGPT's popularity, its rapid evolution, and its seemingly sophisticated language and knowledge performance. The concept helps scholars and teachers easily enter conversations about artificial intelligence (AI) text generation technologies and how they transform the notions of authorship, research, labor,…
Descriptors: Artificial Intelligence, Technological Advancement, Computational Linguistics, Computer Software
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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
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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)
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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
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Tourmen, Claire; Hoffmann, Daniel – L2 Journal, 2022
Despite attempts to discourage the use of machine translation (MT), we have observed that students continue to rely on it. Are teachers powerless? We believe not! Consistent with a range of solutions proposed in previous publications, we hypothesized that a "hands-on" approach would be effective in helping students raise awareness of the…
Descriptors: Pilot Projects, Teaching Methods, Consciousness Raising, French
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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
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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
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Zhang, Hong; Torres-Hostench, Olga – Language Learning & Technology, 2022
The main purpose of this study is to evaluate the effectiveness of Machine Translation Post-Editing (MTPE) training for FL students. Our hypothesis was that with specific MTPE training, students will able to detect and correct machine translation mistakes in their FL. Training materials were developed to detect six typical mistakes from Machine…
Descriptors: Computational Linguistics, Translation, Second Language Learning, Second Language Instruction
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Xu, Jun – L2 Journal, 2022
While the use of machine translation (MT) in the classroom has been explored from various perspectives, the relationship between language proficiency and MT use regarding learners' behaviors and beliefs remains unclear in the research literature. This study focused on four Japanese learners with various language proficiencies from a fourth-year…
Descriptors: Translation, Japanese, Language Proficiency, Second Language Learning
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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
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Mirzaeian, Vahid R. – The EUROCALL Review, 2021
Although the field of machine translation has witnessed huge improvements in recent years, its potentials have not been fully exploited in other interdisciplinary areas such as foreign language teaching. The aim of this paper, therefore, is to report an experiment in which this technology was employed to teach a foreign language to a group of…
Descriptors: Translation, Computational Linguistics, Error Correction, Phrase Structure
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Klekovkina, Vera; Denié-Higney, Laurence – L2 Journal, 2022
Machine translation (MT) provides a seemingly accelerated alternative way to communicate in the target language (L2). A convenient service to the public, MT renders a potential disservice to language learners. In this pedagogically focused article, we show concrete and detailed examples of how language instructors can turn MT and other electronic…
Descriptors: Translation, Computational Linguistics, Interdisciplinary Approach, Writing Instruction
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Mughaz, Dror; Cohen, Michael; Mejahez, Sagit; Ades, Tal; Bouhnik, Dan – Interdisciplinary Journal of e-Skills and Lifelong Learning, 2020
Aim/Purpose: Using Artificial Intelligence with Deep Learning (DL) techniques, which mimic the action of the brain, to improve a student's grammar learning process. Finding the subject of a sentence using DL, and learning, by way of this computer field, to analyze human learning processes and mistakes. In addition, showing Artificial Intelligence…
Descriptors: Artificial Intelligence, Teaching Methods, Brain Hemisphere Functions, Grammar
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Nitzke, Jean; Tardel, Anke; Hansen-Schirra, Silvia – Interpreter and Translator Trainer, 2019
This paper presents the ERASMUS+ "DigiLing" project, which aims to teach and improve linguists' and translators' skills and knowledge of digitalisation to prepare them for today's job market. Against this background, it discusses the development of digital competencies and distinguishes them from traditional domain-specific and general…
Descriptors: Translation, Blended Learning, Technological Literacy, Skill Development
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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
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