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Investigating student engagement with AI-driven feedback in translation revision : a mixed-methods study

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Title: Investigating student engagement with AI-driven feedback in translation revision : a mixed-methods study
Authors: Xu, S, Su, Y, Liu, K
Contributors: Department of Chinese and Bilingual Studies
Publisher Information: Springer New York LLC
Publication Year: 2025
Collection: Hong Kong Polytechnic University: PolyU Institutional Repository (PolyU IR)
Subject Terms: AI-generated feedback, ChatGPT, Revision process, Student engagement, Translation education
Description: 202509 bcch ; Version of Record ; Self-funded ; Published ; Springer Nature (2025) ; TA
Document Type: article in journal/newspaper
Language: English
Relation: https://hdl.handle.net/10397/114868; 16969; 16995; 30; 12; OA_TA
DOI: 10.1007/s10639-025-13457-0
Availability: https://hdl.handle.net/10397/114868
https://doi.org/10.1007/s10639-025-13457-0
Rights: © The Author(s) 2025 ; Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. ; The following publication Xu, S., Su, Y. & Liu, K. Investigating student engagement with AI-driven feedback in translation revision: A mixed-methods study. Educ Inf Technol 30, 16969–16995 (2025) is available at https://doi.org/10.1007/s10639-025-13457-0.
Accession Number: edsbas.50D02C8F
Database: BASE
Description
Abstract:202509 bcch ; Version of Record ; Self-funded ; Published ; Springer Nature (2025) ; TA
DOI:10.1007/s10639-025-13457-0