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Chinese Language Learners Evaluating Machine Translation Accuracy

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Title: Chinese Language Learners Evaluating Machine Translation Accuracy
Language: English
Authors: Chang, Li-Ching (ORCID 0000-0002-9044-5411)
Source: JALT CALL Journal. 2022 18(1):110-136.
Availability: JALT CALL SIG. 1-6-1 Nishiwaseda Shinjuku-ku, Tokyo, 169-8050, Japan. e-mail: journal!jaltcall.org; Web site: http://journal.jaltcall.org
Peer Reviewed: Y
Page Count: 27
Publication Date: 2022
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Chinese, Second Language Learning, Second Language Instruction, Translation, Computational Linguistics, English (Second Language), Accuracy, Decision Making, Teaching Methods, Learning Processes, Instructional Effectiveness, Intervention, Group Discussion, Student Attitudes, Information Sources, Dictionaries, Language Usage, Phrase Structure, Definitions, Search Engines, Computer Software, Educational Resources, Undergraduate Students, Foreign Countries
Geographic Terms: Taiwan
ISSN: 1832-4215
Abstract: With increasingly rapid advances in machine translation (MT) technology, such as Google Translate, MT has become an indispensable learning resource for second or additional language learners. Many studies indicate that MT or postediting of MT (PEMT) can be an effective tool for L2 learning and teaching. Nevertheless, little research illustrates how language learners judge or evaluate the accuracy of MT output. The judgement of MT accuracy is essential because MT is not yet error-free. Therefore, the aim of this research is to explore how L2 learners attempt to judge the accuracy of MT output when using MT or PEMT. This study was undertaken through a teaching intervention in an online English-Chinese translation course. Student participants included L2 learners of Chinese studying at a university in Taiwan. Findings from observations of screen recordings and focus group discussions reveal that students use different MT tools and additional online-based resources as complementary strategies to better judge MT accuracy. These include: 1) using more than one MT tool to cross-check MT output; 2) using dictionaries to check word meaning and word usage by looking at example sentences; 3) using search engines to check word definitions, translations, and collocations.
Abstractor: As Provided
Entry Date: 2022
Accession Number: EJ1341954
Database: ERIC
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  Data: JALT CALL SIG. 1-6-1 Nishiwaseda Shinjuku-ku, Tokyo, 169-8050, Japan. e-mail: journal!jaltcall.org; Web site: http://journal.jaltcall.org
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  Data: With increasingly rapid advances in machine translation (MT) technology, such as Google Translate, MT has become an indispensable learning resource for second or additional language learners. Many studies indicate that MT or postediting of MT (PEMT) can be an effective tool for L2 learning and teaching. Nevertheless, little research illustrates how language learners judge or evaluate the accuracy of MT output. The judgement of MT accuracy is essential because MT is not yet error-free. Therefore, the aim of this research is to explore how L2 learners attempt to judge the accuracy of MT output when using MT or PEMT. This study was undertaken through a teaching intervention in an online English-Chinese translation course. Student participants included L2 learners of Chinese studying at a university in Taiwan. Findings from observations of screen recordings and focus group discussions reveal that students use different MT tools and additional online-based resources as complementary strategies to better judge MT accuracy. These include: 1) using more than one MT tool to cross-check MT output; 2) using dictionaries to check word meaning and word usage by looking at example sentences; 3) using search engines to check word definitions, translations, and collocations.
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        PageCount: 27
        StartPage: 110
    Subjects:
      – SubjectFull: Chinese
        Type: general
      – SubjectFull: Second Language Learning
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      – SubjectFull: Second Language Instruction
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      – SubjectFull: Translation
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      – SubjectFull: Computational Linguistics
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      – SubjectFull: English (Second Language)
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      – SubjectFull: Accuracy
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      – SubjectFull: Teaching Methods
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