HCAIOct 11, 2024

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

arXiv:2410.08581v16 citationsh-index: 5
Originality Synthesis-oriented
AI Analysis

This addresses the problem of understanding AI feedback integration for translation students, but it is incremental as it builds on existing educational feedback research without introducing new methods or broad SOTA results.

This study tackled the understudied application of AI-generated feedback in translation education by investigating master's students' engagement with ChatGPT feedback during revision, revealing complex interrelations among cognitive, affective, and behavioral dimensions, with students showing considerable cognitive effort and moderate affective satisfaction.

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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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