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Lee, Sangmin-Michelle – Computer Assisted Language Learning, 2023
With a significant number of students using machine translation (MT) for academic purposes in recent years, language teachers can no longer ignore it in their classrooms. Although an increasing number of studies have reported its pedagogical benefits, studies have also revealed that language teachers are still sceptical about using MT for various…
Descriptors: Instructional Effectiveness, Teaching Methods, Translation, Second Language Learning
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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)
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Han, Chao; Lu, Xiaolei – Computer Assisted Language Learning, 2023
The use of translation and interpreting (T&I) in the language learning classroom is commonplace, serving various pedagogical and assessment purposes. Previous utilization of T&I exercises is driven largely by their potential to enhance language learning, whereas the latest trend has begun to underscore T&I as a crucial skill to be…
Descriptors: Translation, Computational Linguistics, Correlation, Language Processing
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Tsai, Shu-Chiao – Computer Assisted Language Learning, 2022
This study investigates the effectiveness of using Google Translate as a translingual CALL tool in English as a Foreign Language (EFL) writing, keyed to the perceptions of both more highly proficient Chinese English major university students and less-proficient non-English majors. After watching a 5-minute passage from a movie, each cohort of…
Descriptors: Computer Assisted Instruction, Translation, Second Language Learning, Second Language Instruction
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Chung, Eun Seon; Ahn, Soojin – Computer Assisted Language Learning, 2022
Many studies that have investigated the educational value of online machine translation (MT) in second language (L2) writing generally report significant improvements after MT use, but no study as of yet has comprehensively analyzed the effectiveness of MT use in terms of various measures in syntactic complexity, accuracy, lexical complexity, and…
Descriptors: Translation, Computational Linguistics, English (Second Language), Second Language Learning
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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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Tsai, Shu-Chiao – Computer Assisted Language Learning, 2019
This study investigates the impact on extemporaneous English-language first drafts by using Google Translate (GT) in three different tasks assigned to Chinese sophomore, junior, and senior students of English as a Foreign Language (EFL) majoring in English. Students wrote first in Chinese (Step 1), then drafted corresponding texts in English (Step…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Computer Software
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Chen, Howard Hao-Jan; Wu, Jian-Cheng; Yang, Christine Ting-Yu; Pan, Iting – Computer Assisted Language Learning, 2016
The development of collocational knowledge is important for foreign language learners; unfortunately, learners often have difficulties producing proper collocations in the target language. Among the various ways of collocation learning, the DDL (data-driven learning) approach encourages the independent learning of collocations and allows learners…
Descriptors: Chinese, Phrase Structure, Second Language Learning, Computational Linguistics
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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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Garcia, Ignacio; Pena, Maria Isabel – Computer Assisted Language Learning, 2011
The few studies that deal with machine translation (MT) as a language learning tool focus on its use by advanced learners, never by beginners. Yet, freely available MT engines (i.e. Google Translate) and MT-related web initiatives (i.e. Gabble-on.com) position themselves to cater precisely to the needs of learners with a limited command of a…
Descriptors: Translation, Editing, Search Engines, Writing Skills
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Chen, Hao-Jan Howard – Computer Assisted Language Learning, 2011
The development of adequate collocational knowledge is important for foreign language learners; nonetheless, learners often have difficulties in producing proper collocations in the target language. Among the various ways of learning collocations, the DDL (data-driven learning) approach encourages independent learning of collocations and allows…
Descriptors: Independent Study, Foreign Countries, Second Language Learning, Phrase Structure
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Nino, Ana – Computer Assisted Language Learning, 2008
Generalised access to the Internet and globalisation has led to increased demand for translation services and a resurgence in the use of machine translation (MT) systems. MT post-editing or the correction of MT output to an acceptable standard is known to be one of the ways to face the huge demand on multilingual communication. Given that the use…
Descriptors: Advanced Students, Translation, Second Language Learning, Editing
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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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Berleant, Daniel; And Others – Computer Assisted Language Learning, 1997
Describes LEARN, a software system for computer assisted foreign language vocabulary acquisition. Notes that the system processes English unrestricted text by translating selected English words in it into foreign words before presenting the text to the student. Points out that the natural path for the system's future is to add more languages. (23…
Descriptors: Ambiguity, Computational Linguistics, Computer Assisted Instruction, Computer Software