From feedback engagement to literacy development: how translation students learn from multi-sourced feedback in LMS for professional growth

Research on student engagement with diverse sources of feedback (e.g., teacher, peer, and automated systems) in language education has expanded significantly over the past two decades, particularly in second language (L2) writing. This growth has accelerated with the recent emergence of generative AI (GenAI) tools, which represent a transformative shift in automated feedback delivery. However, in other L2 teaching and learning contexts, particularly like translation settings, students' engagement with feedback and the following development of feedback literacy in feedback activities is still severely under-studied. To fill this gap and embrace the emerging digitally-enabled teaching trend in translation classrooms, this case study examined the automated, peer and teacher feedback that three translation-majored undergraduates have received for their translation assignments in the Learning Management System (LMS). Drawing upon these data along with semi-structured interviews, stimulated recalls, classroom observations and other documents, this study also explored these students' engagement with the multi-sourced translation feedback in the LMS and its implications for developing feedback literacy and professional competence in translation education. The findings suggest that for effective feedback engagement and the development of both feedback literacy and professional competencies, facilitating conditions, well-designed feedback practices and scaffolding activities compatible with learner factors are all indispensable.