DeepL Translator in EFL Writing: Correlating User Experience with Students’ Writing Achievement

Abstract

This study aims to find out the relationship between DeepL translator user experience and students' writing achievement at KH. A. Wahab Hasbullah University. This research is motivated by the increasing use of artificial intelligence-based translation tools at the academic level and the need to understand its influence on language learning, especially writing skills. This research uses a quantitative approach with a correlational research design. The data of this research was obtained through questionnaires and writing assignments from 33 respondents. The results of data analysis in this study using Pearson Product Moment show that there is a strong and significant correlation between the experience of using DeepL Translator and students' writing achievement, with a correlation value of r = 0.794 and sig. <0.001. The findings in this study show that students who gain positive experiences related to ease of use, accuracy, and from this positive experience also obtain higher writing scores. Nevertheless, researchers found negative effects such as over-reliance on automatic translation, as well as a lack of self-correction capabilities. It can be concluded that DeepL not only functions as a supporting translation tool, but DeepL can also make a positive contribution to students' writing achievement if used appropriately. Therefore, the use of DeepL needs to be critically integrated in learning activities to support the development of language awareness and writing independence.