Presentation Enhancing Translation Training Through AI and Peer Collaboration more

Sun, Jul 20, 12:15-12:40 Asia/Tokyo

While AI translation technologies offer efficiency and support in managing translation tasks, they also present challenges in preserving linguistic elements, cultural fidelity, and literary style. This study explores how peer review helps students analyze and post-edit AI translations by identifying issues, enhancing language sensitivity, and refining editing skills. Fourth-year university students in Taiwan will work with AI-generated translations, engaging in post-editing, peer review, and guided reflection. Through structured peer review, they will identify linguistic errors, cultural misinterpretations, and stylistic issues. Using Google Docs comments and Peer Review Parameters, they will assess AI quality, provide feedback, and refine translations. A final reflection will help them evaluate their editing strategies, AI effectiveness, and peer feedback experience. This study investigates whether peer collaboration enhances students’ ability to make informed judgments about AI translations, identify and correct AI errors, and develop critical evaluation skills. Using quantitative assessment and proofreading data, it assesses the pedagogical benefits of integrating AI-assisted translation with post-editing and peer review. Findings will offer insights into how peer review can help students critically assess AI translations, refine their editing skills, and balance AI efficiency with human judgment—particularly in literary translation, where cultural references and linguistic precision are essential.