Robotics & Machine Learning Daily News2024,Issue(Jun.4) :13-14.

Researchers from JiMei University Describe Findings in Machine Translation (Theo retical Perspectives and Factors Influencing Machine Translation Use In L2 Writi ng: a Scoping Review)

集美大学的研究人员描述了机器翻译的发现(理论观点和影响机器翻译使用的因素在第二届世界会议:范围综述)

Robotics & Machine Learning Daily News2024,Issue(Jun.4) :13-14.

Researchers from JiMei University Describe Findings in Machine Translation (Theo retical Perspectives and Factors Influencing Machine Translation Use In L2 Writi ng: a Scoping Review)

集美大学的研究人员描述了机器翻译的发现(理论观点和影响机器翻译使用的因素在第二届世界会议:范围综述)

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摘要

《机器人与机器学习每日新闻》的一名新闻记者兼新闻编辑,调查人员讨论机器翻译的新发现。根据来自中国人民共和国厦门的新闻,NewsRx记者的研究表明,"尽管第二语言(2)写作中的机器翻译越来越普遍,"本文综述了机器翻译在二语写作中的应用研究,旨在找出影响教师和学生使用机器翻译的主要模式和因素。我们的新闻记者从集美大学的研究中获得了一句话:“首先将支持机器翻译研究的理论观点综合起来,将机器翻译分为三种模式:语言过程、中介产物和跨语言过程。然后回顾了实证研究。”摘要:揭示了机器翻译如何塑造二语写作的主要因素是语言因素。最近的研究也考察了与人相关的因素,并将机器翻译的有效性作为教师和学生个体差异的条件。人际、教学、语言等方面的语境因素。在此基础上,提出了一个概念框架来阐明机器翻译过程中所识别的因素之间的相互关系,并提出了避免将机器翻译视为政治中立的参与者的观点。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators discuss new findings in Machine Translation. According to news originating from Xiamen, People’s Republi c of China, by NewsRx correspondents, research stated, “Despite the increasing p opularity of machine translation in second language (L2) writing, the theoretica l perspectives and complex factors shaping its use remain under synthesized. Thi s article reviews research on machine translation use in L2 writing to identify major models and factors that shape teachers’ and students’ employment of machin e translation.” Our news journalists obtained a quote from the research from JiMei University, “ Theoretical perspectives underpinning machine translation research are first syn thesized to categorize machine translation into three models: a linguistic proce ssor, a mediational artifact, and a translanguaging process. What then reviewed are empirical studies, revealing a predominant focus on linguistic factors in te rms of how machine translation shapes L2 writing. More recent research has also examined person-related factors and taken the effectiveness of machine translati on as conditioning upon individual differences of teachers and students. Context ual factors in interpersonal, instructional, and institutional settings and ideo logical factors are also identified. A conceptual framework is then developed to illuminate the interrelatedness of the identified factors during the process of using machine translation. The study argues for a need to avoid taking machine translation as a politically neutral participant in L2 writing.”

Key words

Xiamen/People’s Republic of China/Asia/Emerging Technologies/Machine Learning/Machine Translation/JiMei University

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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