Optimizing Machine Translation to Overcome Mechanical Engineering Vocational Education Students Difficulties in Academic Writing

S. Sulistyaningrum, Trisya Avianka
{"title":"Optimizing Machine Translation to Overcome Mechanical Engineering Vocational Education Students Difficulties in Academic Writing","authors":"S. Sulistyaningrum, Trisya Avianka","doi":"10.24903/sj.v6i2.714","DOIUrl":null,"url":null,"abstract":"Background: \nMachine translation has been proved to be a favourable style to execute. However, some research evidence difficulties indicates that its focus is on students' difficulties in academic writing, not on how to overcome them by using machine translation. As a result, this research aims to determine how machine translation might be optimized to help mechanical engineering vocational education students with academic writing difficulties. \nMethodology: \nThe data was collected from 27 second-semester mechanical engineering vocational education students currently enrolled in an English college course at one of the Universities in Jakarta. Questionnaires online were used to obtain the data, which was analyzed and interpreted descriptively. Questionnaire 1 is used to determine whether or not the subject utilized machine translation and, if so, what type of machine translation they used most frequently. Question 2 was split into two sections. PART A was modified from Xiao & Chen (2015), who described students' challenges with academic writing. It comprises 12 items that were delivered to 27 students via Google Form. Meanwhile, the findings of Lee (2020) have been adapted into PART B. \nFindings: \nThe result of this study revealed that 27 students of mechanical engineering vocational education in one of the Universities in Jakarta encountered several academic writing difficulties such as grammar (construct grammatically correct sentences, the use of appropriate tenses), expressions (discourse markers, part of speech), and vocabulary (proper vocabulary choices and finding synonyms). Grammar problems are the most challenging, followed by vocabulary and phrases. The optimization of machine translation was also discovered to be the most effective way of overcoming vocabulary issues followed by grammar and expression. \nConclusion: \nAcademic writing issues emerge in the classroom. According to the findings, the most difficulties students encountered fell into the grammar aspect. On the other hand, the students considered that machine translation would be the most helpful in overcoming their vocabulary challenges. Although machine translation helps deal with academic writing difficulties like developing vocabulary skills, increasing knowledge of grammar rules in context, and finding more authentic expression, teachers should also guide them in writing academically. \nKeywords: optimizing machine translation; academic writing difficulties; grammar; vocabulary; expressions.","PeriodicalId":250621,"journal":{"name":"Script Journal: Journal of Linguistics and English Teaching","volume":"86 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Script Journal: Journal of Linguistics and English Teaching","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.24903/sj.v6i2.714","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Background: Machine translation has been proved to be a favourable style to execute. However, some research evidence difficulties indicates that its focus is on students' difficulties in academic writing, not on how to overcome them by using machine translation. As a result, this research aims to determine how machine translation might be optimized to help mechanical engineering vocational education students with academic writing difficulties. Methodology: The data was collected from 27 second-semester mechanical engineering vocational education students currently enrolled in an English college course at one of the Universities in Jakarta. Questionnaires online were used to obtain the data, which was analyzed and interpreted descriptively. Questionnaire 1 is used to determine whether or not the subject utilized machine translation and, if so, what type of machine translation they used most frequently. Question 2 was split into two sections. PART A was modified from Xiao & Chen (2015), who described students' challenges with academic writing. It comprises 12 items that were delivered to 27 students via Google Form. Meanwhile, the findings of Lee (2020) have been adapted into PART B. Findings: The result of this study revealed that 27 students of mechanical engineering vocational education in one of the Universities in Jakarta encountered several academic writing difficulties such as grammar (construct grammatically correct sentences, the use of appropriate tenses), expressions (discourse markers, part of speech), and vocabulary (proper vocabulary choices and finding synonyms). Grammar problems are the most challenging, followed by vocabulary and phrases. The optimization of machine translation was also discovered to be the most effective way of overcoming vocabulary issues followed by grammar and expression. Conclusion: Academic writing issues emerge in the classroom. According to the findings, the most difficulties students encountered fell into the grammar aspect. On the other hand, the students considered that machine translation would be the most helpful in overcoming their vocabulary challenges. Although machine translation helps deal with academic writing difficulties like developing vocabulary skills, increasing knowledge of grammar rules in context, and finding more authentic expression, teachers should also guide them in writing academically. Keywords: optimizing machine translation; academic writing difficulties; grammar; vocabulary; expressions.
优化机器翻译,克服机械工程职业教育学生学术写作困难
背景:机器翻译已被证明是一种有利的翻译方式。然而,一些研究证据的困难表明,它关注的是学生在学术写作中的困难,而不是如何利用机器翻译来克服这些困难。因此,本研究旨在确定如何优化机器翻译,以帮助有学术写作困难的机械工程职业教育学生。方法:数据收集自目前在雅加达一所大学就读英语学院课程的27名机械工程职业教育第二学期学生。使用在线调查问卷获取数据,对数据进行描述性分析和解释。问卷1用于确定受试者是否使用机器翻译,如果使用,他们最常使用哪种类型的机器翻译。问题2分为两个部分。A部分改编自Xiao & Chen(2015),他们描述了学生在学术写作方面的挑战。它包括12个项目,通过谷歌表格发送给27名学生。同时,Lee(2020)的研究结果已被纳入第二部分。研究结果:本研究的结果显示,雅加达一所大学的27名机械工程职业教育学生遇到了一些学术写作困难,如语法(构建语法正确的句子,使用适当的时态),表达(话语标记,词性)和词汇(正确的词汇选择和查找同义词)。语法问题是最具挑战性的,其次是词汇和短语。机器翻译的优化是克服词汇问题的最有效方法,其次是语法和表达问题。结论:学术写作问题出现在课堂上。根据调查结果,学生遇到的最大困难是语法方面。另一方面,学生们认为机器翻译将是最有帮助的克服他们的词汇挑战。虽然机器翻译有助于解决学术写作的困难,如发展词汇技能,增加对上下文语法规则的了解,找到更真实的表达,但教师也应该指导他们进行学术写作。关键词:优化机器翻译;学术写作困难;语法;词汇表;表达式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信