首页|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)
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)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
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.”
XiamenPeople’s Republic of ChinaAsiaEmerging TechnologiesMachine LearningMachine TranslationJiMei University
NETL
NSTL
