Machine Translation in Language Acquisition: A Study on EFL Students' Perceptions and Practices in Saudi Arabia and South Korea

• Published in: Journal of computer assisted learning 2023-12, Vol.39 (6), p.1988-2003
• Main Authors: Almusharraf, Asma, Bailey, Daniel
• Format: Article
• Language: English
• Subjects: Accuracy; College Students; Colleges & universities; Comparative Education; Computational Linguistics; Content analysis; Correlation analysis; Cross Cultural Studies; English (Second Language); English as a second language; English as a second language instruction; English language; Foreign Countries; Foreign language learning; Foreign languages; Korean language; Language Acquisition; Language Proficiency; Language Skills; Machine translation; Perceptions; Pronunciation; Recording; Revision (Written Composition); Second Language Learning; Second language writing; Second Languages; Skills; Speech; Student Attitudes; Students; Technology Uses in Education; Translation; Translation methods and strategies; Voice communication; Writing Instruction
• ISSN: 0266-4909; 1365-2729
• DOI: 10.1111/jcal.12857

Background: Language learners are taking advantage of the increased accuracy afforded by machine translation (MT) tools like Google Translate. There is a growing debate as to whether these tools support or hinder English as a foreign language (EFL) education. Some EFL students are drawn to MT tools to save time and energy when communicating, but how this use relates to second language acquisition needs to be clarified. Objective: This study investigated the perceptions and practices of MT tools among university EFL students in Saudi Arabia and South Korea. Methods: The study surveyed Saudi (n = 310) and South Korean (n = 160) university students to explore the use of MT tools in EFL learning. It used mean scores, correlation analysis, and structural equation modelling to understand the perceived benefits and limitations of MT tools and their influence on the use of translation websites. The findings were triangulated using content analysis of open-ended items. Results and Conclusion: Findings indicate students showed a high level of acceptance and utilization of MT tools. English avoidance behaviour (B = 0.43), benefits (B = 0.32), and foreign language proficiency (B = -0.19) predicted 61% of actual use of MT tools like Google Translate. Further, students frequently used MT tools despite the reported concerns about accuracy mistakes. Saudi students listed a more comprehensive array of why they use MT tools than Korean students, while Saudis and Koreans frequently used MT tools for individual word and sentence translations. Implications: Students should edit MT output when writing and are encouraged to use the voice recording and other functions of MT tools to learn language skills. Instructors must prevent overuse and dependency on MT tools, especially among low-proficiency students who want to avoid using English.