A Study on Teaching Path Design for Developing College Students’ Post-Editing Competence Based on Technology Trust

As artificial intelligence reshapes translation workflows, post-editing competence has become essential for translation graduates. Yet how technology trust influences its development remains underexplored. This study investigates the optimization of teaching pathways for cultivating college students’ post-editing competence based on technology trust. The study therefore explains a three-stage teaching pathway. It contributes a complete method for integrating technology trust into post-editing instruction, offering practical implications for AI-enhanced translation education.