Machine translation for language learning: A review of pedagogical integration and digital literacy in ESL contexts

Abstract

This systematic review investigates the integration of machine translation (MT) tools in English as a Second Language (ESL) education, focusing on pedagogical practices, learner perceptions, and digital literacy outcomes. Drawing from ten empirical studies published between 2020 and 2024, the review synthesizes findings across diverse educational contexts. The methodology follows PRISMA guidelines, involving a structured search across Google Scholar databases. From 200 initial records, 94 full-text articles were screened, and 10 studies were selected for thematic synthesis. Results are organized into four key themes: perceptions and attitudes, writing development, ethical concerns, and pedagogical integration. While many students report increased writing confidence and reduced anxiety when using MT, teachers express mixed views, ranging from cautious acceptance to concern about academic integrity and diminished language acquisition. Several studies emphasize the importance of guided MT use, including pre- and post-editing activities, as a means of promoting grammar awareness and critical language reflection. The review highlights MT’s potential to foster digital literacy and learner autonomy when integrated with instructional scaffolding. Conclusively, this study proposes a balanced, reflective approach to MT use in ESL classrooms and calls for pedagogical training and clear assessment policies. The findings offer insights for educators, curriculum designers, and researchers seeking to adapt language instruction in an AI-enhanced learning environment.