THE INTEGRATION OF GOOGLE TRANSLATE AS A MACHINE TRANSLATION AID IN EFL STUDENTS’ THESIS COMPOSITION

Abstract

This study aims to examine the integration of Google Translate as a machine translation tool in the EFL students’ thesis writing process. Framed within the explanatory sequential mixed methods, the study utilized a survey and an open-ended interview. Using a purposive sampling technique, this study included fifty EFL students in North Bali, Indonesia, in the survey and five students voluntarily in the interview session. Measured using the Gregory Formula, content validity results from the two raters showed that the survey and interview guide were valid (.1) and reliable (α=.809). The survey data were analyzed using Ideal Mean Score analysis and the interview transcripts data were analyzed using Interactive Model analysis. Results reveal that Google Translate benefited the students in the thesis writing process. The interactive model analysis resulted in main themes of the strengths, comprising sub-themes of functions and features of Google Translate and weaknesses, involving sub-themes of contextuality, grammar accuracy, and academic integrity issues. It can be concluded that the use of Google Translate can be helpful in assisting students’ thesis writing with several considerations.