Sustainability and Influence of Machine Translation: Perceptions and Attitudes of Translation Instructors and Learners in Hong Kong

Kanglong Liu, Ho Ling Kwok, Jianwen Liu and Andrew K.F. Cheung
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Kanglong Liu: Department of Chinese and Bilingual Studies, The Hong Kong Polytechnic University, Hong Kong, China
Ho Ling Kwok: Department of Chinese and Bilingual Studies, The Hong Kong Polytechnic University, Hong Kong, China
Jianwen Liu: Department of English Language and Literature, Hong Kong Shue Yan University, Hong Kong, China
Andrew K.F. Cheung: Department of Chinese and Bilingual Studies, The Hong Kong Polytechnic University, Hong Kong, China

Sustainability, 2022, vol. 14, issue 11, 1-29

Abstract: In this era of globalisation, translation technologies have become more popular in daily communication, the education sector, and the translation industry. It is observed that there is a prevalent use of machine translation (MT) among translation learners. The proper use versus abuse of MT can be a critical issue regarding its role in and impact on translation teaching. This exploratory study aims at investigating learners’ and instructors’ knowledge of MT, experience in MT use, perceived MT quality, ethics of MT use, and the perceived relationship between MT and translation training, in order to figure out the usefulness of MT in translation competence acquisition and the necessity of MT training. To this end, we conducted surveys and semi-structured interviews and found that the influence of MT in translation competence acquisition is determined by the properties of MT and learners’ quality. MT is particularly helpful in gaining lexical knowledge and knowledge to ensure translation efficiency, but not in bicultural knowledge. However, such usefulness builds on learners’ language proficiency, analytic ability, and learning motivation. In light of the findings, issues including the sustainability of MT from ethical and linguistic perspectives, and the potential and proper use of MT to inform translator training, are discussed.

Keywords: machine translation; translation competence; translation competence acquisition (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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