Proposing a framework for ethical use of AI in academic writing based on a conceptual review

Implications for quality education

Bibliographic Data

ID21631313
AuthorsMansour Amini (0000-0003-2149-4604, Universiti Sains Malaysia), Kam-Fong Lee (0000-0002-5572-8627, SEGi University), Wang Yiqiu (0009-0004-1603-7489, Zhejiang Chinese Medical University), Wang Yi-qiu (Zhejiang Chinese Medical University, corresponding author), Latha Ravindran (0000-0002-5830-2437, SEGi University)
Year2026
Volume34
Issue3
Pages1394-1418
Publication date2026-03-16
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueInteractive Learning Environments (JOURNAL)
Journal identifiersISSN: 1049-4820 • E-ISSN: 1744-5191
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/10494820.2025.2523382
OpenAlexW4412014521
LanguageEN
Citations received4
References cited72

Aligned with the United Nations Sustainable Development Goal 4 (Quality Education), this paper addresses the ethical use of Artificial Intelligence in academic writing. While AI tools offer unprecedented opportunities for personalized learning and efficiency, their unregulated use raises significant ethical challenges. Through a systematic conceptual review, this study synthesizes existing ethical frameworks and identifies gaps in practical guidance. It proposes a novel, student-centered framework grounded on four pillars: (1) Validation and Source Verification, ensuring AI-generated content accuracy; (2) Transparency and Acknowledgment, promoting honesty by disclosing AI assistance; (3) Context-Dependent Similarity Index, adopting flexible thresholds for AI content usage depending on the academic context; and (4) Direct Source Linking, encouraging proper citation practices with accessible references. The study advocates for embedding this framework into educational policies and AI literacy curricula to empower students to harness AI responsibly, thereby safeguarding educational quality and fostering a culture of transparency and ethical scholarship

Conceptual framework · Engineering ethics · Epistemology · Knowledge management · Mathematics education · Pedagogy · Social science · Sociology · Artificial Intelligence in Healthcare and Education · Computer Science · Ethics and Social Impacts of AI · Explainable Artificial Intelligence (XAI · Psychology

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