Ethical principles for generative AI in research paper writing for EFL graduate students in China

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Published

2025-09-30

Issue: 2025
Section: Proceedings Papers

Authors

DOI: https://doi.org/10.29140/97817637116240-25

Abstract

With DeepSeek and ChatGPT taking the lead in AI technology breakthroughs and applications, AI-assisted writing Apps have demonstrated marvelous efficiency and potential in academic writing for EFL graduate students, sparking concerns over academic misconduct, lack of originality, and privacy risks, and posing severe challenges to academic ethics in universities. Unfortunately, it still remains a universally unsettled debate regarding the accessibility, usability, and inclusivity of AI-assisted writing tools, leading to disparate positions of hesitation, rejection, and inclusion. This paper examines the pros and cons of AI-assisted academic writing and proposes three principles: originality, transparency, and accountability, to guide graduate schools in establishing guidelines for the use of AI in academic paper writing for EFL graduate students in China. It is recommended that the AI-assisted academic writing guidelines focus on AI assistance rather than overindulgence, AI use disclosure and disclaimer, and AI misuse prevention and punishment. The guidelines aim to proactively address the academic ethical challenges brought by AI technological innovation and fill the regulatory gap in AI-assisted academic paper writing for EFL graduate students in China. Our work represents an AI-assisted and CALL-motivated transition from our prior practices and its positive impacts on equity in language education, contributing to the promotion of institutional efforts in providing equitable AI access for EFL graduate students in a more inclusive language learning environment.


Keywords: AI policy, research paper writing, EFL graduate students

Suggested Citation:

Zeng, J., & Zhang, X. (2025). Ethical principles for generative AI in research paper writing for EFL graduate students in China. Proceedings of the International CALL Research Conference, 2025, 191–196. https://doi.org/10.29140/97817637116240-25