Digital Translation and Algorithmic Mediation in English Language Education: Paths and Contradictions in the “My Dream Job” Project in a Brazilian Public School

Abstract

This study analyzes a pedagogical practice conducted with eighth-grade students at a Brazilian public school, in which they created multimodal posts about future professions using the Padlet platform. The study aims to understand how machine translation tools and image-search algorithms reconfigure student authorship and representations of work, gender, and race. Authorship is understood as both situated, since it is connected to students’ social, affective, territorial, and school experiences, and mediated, since it is shaped by the linguistic and visual choices made available by digital technologies. The analysis focuses on two main dimensions: the recurrent use of machine translation tools to comprehend prompts and produce texts in English, and the selection of images through search mechanisms integrated into the platform. The data, comprising field notes, students’ digital productions, and participant observation, indicate that digital technologies expand access to texts, images, and linguistic resources, while also fostering a form of “total translation” that reduces reflective engagement with English and renders algorithms less visible as mediators in meaning-making. The findings show that translators and search engines do not operate as neutral tools, since they influence discursive choices and representations of profession, race, and gender. The study therefore argues that these technologies should be incorporated as objects of critical analysis so that multimodal projects such as My Dream Job can contribute to the development of critical readers and authors in English language education, particularly in Brazilian public school contexts.