Students’ self-determination in using machine translation and generative AI tools for English for academic purposes
Year: 2025
Type: article
Abstract: The rise of machine translation (MT) and generative artificial intelligence (GAI) offers both opportunities and challenges for English for Academic Purposes (EAP) instruction. While MT/GAI can enhance students’ learning beyond the classroom, overreliance may impede the development of critical research and writing skills. Despite studies on MT/GAI in self-regulated learning, students’ motivations for its use and the influence of instructional context and discipline remain underexplored. This study applies Self-Determination Theory (SDT) (Deci & Ryan, 2004) to investigate how autonomy, competence, and relatedness shape MT/GAI use in academic writing. Employing a mixed-methods approach, the study compares EAP students in an English as a Second Language (ESL) context in Australia and an English as a Foreign Language (EFL) context in Vietnam. An online survey, validated through confirmatory factor analysis, collected 416 responses, supplemented by interviews with 17 students. Findings indicate a complex relationship between MT/GAI use and students’ motivational needs. Students reported moderate autonomy, competence, and relatedness, but mixed-effects regression revealed Australian students experienced lower relatedness than Vietnamese students. Disciplinary differences also influenced MT/GAI use. Interviews highlighted variations in EAP instructional approaches and peer-teacher dynamics. We discuss the need for tailored pedagogical strategies fostering collaboration among institutions, teachers, and students.
Institutions: The University of Queensland, Ton Duc Thang University
Language: English
Subfield: Language and Linguistics
Field: Arts and Humanities
Domain: Social Sciences
SDG: Quality education
Open Access status: hybrid
Estimated APC paid: $3,730
OpenAlex ID: W7081927774