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Showing 1 to 15 of 16 results Save | Export
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Godwin-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
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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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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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Lee, Sangmin-Michelle; Briggs, Neil – ReCALL, 2021
In recent years, marked gains in the accuracy of machine translation (MT) outputs have greatly increased its viability as a tool to support the efforts of English as a foreign language (EFL) students to write in English. This study examines error corrections made by 58 Korean university students by comparing their original L2 texts to that of MT…
Descriptors: Translation, Computational Linguistics, Second Language Learning, Second Language Instruction
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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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Chompurach, Wichuta – English Language Teaching, 2021
The present study aims to investigate how Thai EFL university students use Google Translate (GT) in English writing, how they post-edit (PE) its outputs, and how they view GT use in English writing. The participants were 15 third-year non-English major students from three universities in Thailand. The data collection tools were an interview and…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Instructional Effectiveness
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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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Lee, Sangmin-Michelle – Computer Assisted Language Learning, 2020
Although it remains controversial, machine translation (MT) has gained popularity both inside and outside of the classroom. Despite the growing number of students using MT, little is known about its use as a pedagogical tool in the EFL classroom. The present study investigated the role of MT as a CALL tool in EFL writing. Most studies on MT as a…
Descriptors: Translation, Computational Linguistics, English (Second Language), Second Language Learning
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Valijärvi, Riitta-Liisa; Tarsoly, Eszter – Practitioner Research in Higher Education, 2019
We propose ways of incorporating Google Translate into the teaching of Finnish and Hungarian in a higher education setting at different skill levels. The task types tested in our study were: analytical tasks (dictionary-like exercise, word-building, part-of-word identification), discovery method tasks (elicitation, problem solving), and awareness…
Descriptors: Translation, Computer Software, Finno Ugric Languages, Hungarian
El-Banna, Adel I.; Naeem, Marwa A. – Online Submission, 2016
This research work aimed at making use of Machine Translation to help students avoid some syntactic, semantic and pragmatic common errors in translation from English into Arabic. Participants were a hundred and five freshmen who studied the "Translation Common Errors Remedial Program" prepared by the researchers. A testing kit that…
Descriptors: Computational Linguistics, Translation, Statistical Analysis, Syntax
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Carrió Pastor, María Luisa; Mestre-Mestre, Eva María – International Journal of English Studies, 2014
Nowadays, scientific writers are required not only a thorough knowledge of their subject field, but also a sound command of English as a lingua franca. In this paper, the lexical errors produced in scientific texts written in English by non-native researchers are identified to propose a classification of the categories they contain. This study…
Descriptors: Second Language Learning, English (Second Language), Guidelines, Error Patterns
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Gao, Zhao-Ming – Computer Assisted Language Learning, 2011
Previous studies on self-correction using corpora involve monolingual concordances and intervention from instructors such as marking of errors, the use of modified concordances, and other simplifications of the task. Can L2 learners independently refine their previous outputs by simply using a parallel concordancer without any hints about their…
Descriptors: Translation, Pretests Posttests, Guidelines, English (Second Language)
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Cui, Ying, Ed.; Zhao, Wei, Ed. – IGI Global, 2015
As an area of research that continues to develop, the study of linguistics worldwide presents the opportunity for the improvement of cross-cultural communication through education and research. Language educators are charged with the task of instructing students to effectively communicate across cultures in a multi-lingual world. The…
Descriptors: Guides, Second Languages, Translation, Teaching Methods
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Jafarpour, Ali Akbar; Sharifi, Abolghasem – Teaching English with Technology, 2012
Collocations are one of the most important elements in language proficiency but the effect of error correction feedback of collocations has not been thoroughly examined. Some researchers report the usefulness and importance of error correction (Hyland, 1990; Bartram & Walton, 1991; Ferris, 1999; Chandler, 2003), while others showed that error…
Descriptors: Error Correction, Feedback (Response), Phrase Structure, Language Proficiency
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Chang, Yu-Chia; Chang, Jason S.; Chen, Hao-Jan; Liou, Hsien-Chin – Computer Assisted Language Learning, 2008
Previous work in the literature reveals that EFL learners were deficient in collocations that are a hallmark of near native fluency in learner's writing. Among different types of collocations, the verb-noun (V-N) one was found to be particularly difficult to master, and learners' first language was also found to heavily influence their collocation…
Descriptors: Sentence Structure, Verbs, Nouns, Foreign Countries
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