{"title":"汉语学习者评价机器翻译的准确性","authors":"Li-Ching Chang","doi":"10.29140/jaltcall.v18n1.592","DOIUrl":null,"url":null,"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 post-editing 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. effect, making the transformation of education an unavoidable necessity, with ‘adaptive learning’ forming the basis of education reform.","PeriodicalId":37946,"journal":{"name":"JALT CALL Journal","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Chinese language learners evaluating machine translation accuracy\",\"authors\":\"Li-Ching Chang\",\"doi\":\"10.29140/jaltcall.v18n1.592\",\"DOIUrl\":null,\"url\":null,\"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 post-editing 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. effect, making the transformation of education an unavoidable necessity, with ‘adaptive learning’ forming the basis of education reform.\",\"PeriodicalId\":37946,\"journal\":{\"name\":\"JALT CALL Journal\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-04-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"JALT CALL Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.29140/jaltcall.v18n1.592\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Arts and Humanities\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"JALT CALL Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.29140/jaltcall.v18n1.592","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Arts and Humanities","Score":null,"Total":0}
Chinese language learners evaluating machine translation accuracy
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 post-editing 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. effect, making the transformation of education an unavoidable necessity, with ‘adaptive learning’ forming the basis of education reform.
期刊介绍:
The JALT CALL Journal is an international refereed journal committed to excellence in research in all areas within the field of Computer Assisted Language Learning.