# Integrating AI for Enhanced Feedback in Translation Revision- A Mixed-Methods Investigation of Student Engagement

arXiv: https://arxiv.org/abs/2410.08581 · HTML: https://mlsanity.com/paper/2410.08581/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 62 references that are in the map.
- First posted on arXiv 11 Oct 2024.

## Builds on (most cited first, 1 of 1)

- [Exploring the effectiveness of ChatGPT-based feedback compared with teacher feedback and self-feedback: Evidence from Chinese to English translation](https://mlsanity.com/paper/2309.01645/) (2023)

## Built on by (most cited first, 1 of 1)

- [Who Should Grade My Work? Student Perspectives on Transparent AI-Assisted Writing Assessment in Higher Education](https://mlsanity.com/paper/2609.05346/) (2026)

## Abstract (arXiv)

Despite the well-established importance of feedback in education, the application of Artificial Intelligence (AI)-generated feedback, particularly from language models like ChatGPT, remains understudied in translation education. This study investigates the engagement of master's students in translation with ChatGPT-generated feedback during their revision process. A mixed-methods approach, combining a translation-and-revision experiment with quantitative and qualitative analyses, was employed to examine the feedback, translations pre-and post-revision, the revision process, and student reflections. The results reveal complex interrelations among cognitive, affective, and behavioural dimensions influencing students' engagement with AI feedback and their subsequent revisions. Specifically, the findings indicate that students invested considerable cognitive effort in the revision process, despite finding the feedback comprehensible. Additionally, they exhibited moderate affective satisfaction with the feedback model. Behaviourally, their actions were largely influenced by cognitive and affective factors, although some inconsistencies were observed. This research provides novel insights into the potential applications of AI-generated feedback in translation teachingand opens avenues for further investigation into the integration of AI tools in language teaching settings.