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Strategic Use of Machine Translation: A Case Study of Japanese EFL University Students

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Title: Strategic Use of Machine Translation: A Case Study of Japanese EFL University Students
Language: English
Authors: Mariko Yuasa (ORCID 0000-0003-0563-4072), Osamu Takeuchi
Source: AILA Review. 2024 37(2):215-240.
Availability: John Benjamins Publishing Company. Klaprozenweg 105 Postbus 36224, NL-1020 ME Amsterdam, Netherlands. Tel: +31-20-6304747; Fax: +31-20-6739773; e-mail: subscription@benjamins.nl; Web site: https://www.benjamins.com
Peer Reviewed: Y
Page Count: 26
Publication Date: 2024
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Computational Linguistics, Translation, English (Second Language), Second Language Learning, Foreign Countries, Artificial Intelligence, Writing (Composition), Language Proficiency, Learning Strategies, Learner Engagement, Electronic Learning, COVID-19, Pandemics, Private Colleges, College Freshmen, Social Sciences, Teaching Methods, Student Behavior
Geographic Terms: Japan
DOI: 10.1075/aila.24020.yua
ISSN: 1461-0213
1570-5595
Abstract: The development of generative artificial intelligence (AI) and its associated tools has revolutionised the learning and use of foreign languages (L2). One such tool is machine translation (MT), which has become increasingly popular among university students worldwide, spurring research on MT use in L2 writing. However, previous research has primarily focused on the writing products of intermediate or advanced L2 learners, neglecting the writing process with MT of students with limited L2 proficiency. Therefore, this case study aimed to qualitatively explore how the Common European Framework of Reference for Languages (CEFR) A2 university students employ strategies for L2 writing with MT and how their strategies change after strategy instruction. Seven participants completed writing tasks on a PC before, immediately after, and four weeks after three one-hour out-of-class instruction sessions based on the Strategic Content Learning (SCL) approach. Their writing process was screen-recorded, followed by stimulated recall interviews to elicit their strategies, which were coded and categorised using a framework by O'Malley and Chamot (1990). The results showed an increase in students' elaborate use of strategies after instruction. In particular, strategy clusters were observed for all participants, demonstrating their cognitive engagement in the writing process. Furthermore, first-language (L1)-related strategies were used more frequently post-instruction, indicating learners' efforts to create translation-friendly L1 input for MT. The findings suggest that teaching MT-use strategies is crucial to fostering learners' active engagement in the L2 writing process in a technology-enhanced learning environment.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1459280
Database: ERIC
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  Data: Strategic Use of Machine Translation: A Case Study of Japanese EFL University Students
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  Data: <searchLink fieldCode="AR" term="%22Mariko+Yuasa%22">Mariko Yuasa</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-0563-4072">0000-0003-0563-4072</externalLink>)<br /><searchLink fieldCode="AR" term="%22Osamu+Takeuchi%22">Osamu Takeuchi</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22AILA+Review%22"><i>AILA Review</i></searchLink>. 2024 37(2):215-240.
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  Data: John Benjamins Publishing Company. Klaprozenweg 105 Postbus 36224, NL-1020 ME Amsterdam, Netherlands. Tel: +31-20-6304747; Fax: +31-20-6739773; e-mail: subscription@benjamins.nl; Web site: https://www.benjamins.com
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  Data: 26
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  Data: 2024
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  Data: Journal Articles<br />Reports - Research
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  Data: <searchLink fieldCode="EL" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="EL" term="%22Postsecondary+Education%22">Postsecondary Education</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Computational+Linguistics%22">Computational Linguistics</searchLink><br /><searchLink fieldCode="DE" term="%22Translation%22">Translation</searchLink><br /><searchLink fieldCode="DE" term="%22English+%28Second+Language%29%22">English (Second Language)</searchLink><br /><searchLink fieldCode="DE" term="%22Second+Language+Learning%22">Second Language Learning</searchLink><br /><searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+Intelligence%22">Artificial Intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Writing+%28Composition%29%22">Writing (Composition)</searchLink><br /><searchLink fieldCode="DE" term="%22Language+Proficiency%22">Language Proficiency</searchLink><br /><searchLink fieldCode="DE" term="%22Learning+Strategies%22">Learning Strategies</searchLink><br /><searchLink fieldCode="DE" term="%22Learner+Engagement%22">Learner Engagement</searchLink><br /><searchLink fieldCode="DE" term="%22Electronic+Learning%22">Electronic Learning</searchLink><br /><searchLink fieldCode="DE" term="%22COVID-19%22">COVID-19</searchLink><br /><searchLink fieldCode="DE" term="%22Pandemics%22">Pandemics</searchLink><br /><searchLink fieldCode="DE" term="%22Private+Colleges%22">Private Colleges</searchLink><br /><searchLink fieldCode="DE" term="%22College+Freshmen%22">College Freshmen</searchLink><br /><searchLink fieldCode="DE" term="%22Social+Sciences%22">Social Sciences</searchLink><br /><searchLink fieldCode="DE" term="%22Teaching+Methods%22">Teaching Methods</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Behavior%22">Student Behavior</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Japan%22">Japan</searchLink>
– Name: DOI
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  Data: 10.1075/aila.24020.yua
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 1461-0213<br />1570-5595
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The development of generative artificial intelligence (AI) and its associated tools has revolutionised the learning and use of foreign languages (L2). One such tool is machine translation (MT), which has become increasingly popular among university students worldwide, spurring research on MT use in L2 writing. However, previous research has primarily focused on the writing products of intermediate or advanced L2 learners, neglecting the writing process with MT of students with limited L2 proficiency. Therefore, this case study aimed to qualitatively explore how the Common European Framework of Reference for Languages (CEFR) A2 university students employ strategies for L2 writing with MT and how their strategies change after strategy instruction. Seven participants completed writing tasks on a PC before, immediately after, and four weeks after three one-hour out-of-class instruction sessions based on the Strategic Content Learning (SCL) approach. Their writing process was screen-recorded, followed by stimulated recall interviews to elicit their strategies, which were coded and categorised using a framework by O'Malley and Chamot (1990). The results showed an increase in students' elaborate use of strategies after instruction. In particular, strategy clusters were observed for all participants, demonstrating their cognitive engagement in the writing process. Furthermore, first-language (L1)-related strategies were used more frequently post-instruction, indicating learners' efforts to create translation-friendly L1 input for MT. The findings suggest that teaching MT-use strategies is crucial to fostering learners' active engagement in the L2 writing process in a technology-enhanced learning environment.
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  Data: 2025
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  Data: EJ1459280
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        Value: 10.1075/aila.24020.yua
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      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 26
        StartPage: 215
    Subjects:
      – SubjectFull: Computational Linguistics
        Type: general
      – SubjectFull: Translation
        Type: general
      – SubjectFull: English (Second Language)
        Type: general
      – SubjectFull: Second Language Learning
        Type: general
      – SubjectFull: Foreign Countries
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      – SubjectFull: Artificial Intelligence
        Type: general
      – SubjectFull: Writing (Composition)
        Type: general
      – SubjectFull: Language Proficiency
        Type: general
      – SubjectFull: Learning Strategies
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      – SubjectFull: Learner Engagement
        Type: general
      – SubjectFull: Electronic Learning
        Type: general
      – SubjectFull: COVID-19
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      – SubjectFull: Pandemics
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      – SubjectFull: Private Colleges
        Type: general
      – SubjectFull: College Freshmen
        Type: general
      – SubjectFull: Social Sciences
        Type: general
      – SubjectFull: Teaching Methods
        Type: general
      – SubjectFull: Student Behavior
        Type: general
      – SubjectFull: Japan
        Type: general
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      – TitleFull: Strategic Use of Machine Translation: A Case Study of Japanese EFL University Students
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            NameFull: Osamu Takeuchi
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              Y: 2024
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              Value: 1570-5595
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