Indonesian EFL Students’ Perceptions of DeepL Machine Translation Tool: Utilization, Advantages, and Disadvantages

The integration of artificial intelligence (AI) technologies, such as machine translation tools, has gained traction in language education, offering potential benefits while raising concerns. This mixed-methods study investigates the perceptions and experiences of Indonesian students learning English as a Foreign Language (EFL) regarding the use of DeepL Machine Translation. With advancements in AI and increasing reliance on translation tools, understanding users' perspectives is crucial for effective integration. The research aims to explore EFL students' perceptions of DeepL's utilization, advantages, and disadvantages through a convergent mixed-methods design. Data were collected from 293 participants across various educational levels through a closed-ended questionnaire and open-ended responses. Quantitative analysis revealed a high level of agreement towards DeepL's utilization, particularly for translating written works. Perceived advantages included translation accuracy, time-saving capabilities, and potential for language skill improvement. However, concerns regarding over-reliance and dependency were also expressed. Qualitative insights corroborated the quantitative findings, highlighting DeepL's strengths in context matching, word choice suggestions, and user-friendly features. These findings contribute to the discourse on AI integration in language education, emphasizing the importance of understanding user perceptions and developing balanced implementation strategies. The study concludes with recommendations for educators and curriculum designers to leverage machine translation tools effectively while mitigating potential drawbacks, fostering independent language learning and responsible technology use.