REFRAMING AI-ASSISTED PLAGIARISM IN HIGHER EDUCATION: A SEMI-SYSTEMATIC REVIEW OF PEDAGOGICAL, DISCIPLINARY, AND INSTITUTIONAL PERSPECTIVES


Authors

(1) * Mira Tania   (Universitas Bengkulu)  
        Indonesia
(2)  Cindy Amalia Mughni   (Student in Universitas Indonesia)
(*) Corresponding Author

Abstract


The rapid adoption of artificial intelligence (AI) based writing tools in higher education has intensified concerns regarding academic integrity, particularly AI-assisted plagiarism, commonly termed AI-giarism. Despite growing scholarly attention, existing research on AI-giarism remains fragmented, conceptually ambiguous, and methodologically limited, revealing a clear gap in integrative and theory-informed synthesis. Current studies predominantly rely on perception-based, cross-sectional designs and focus narrowly on student attitudes, with limited attention to disciplinary variation, pedagogical practice, and institutional policy alignment. Addressing this gap, this study presents a semi-systematic literature review of nine peer-reviewed and Scopus-indexed studies published between 2020 and 2025. The novelty of this review lies in its integrative analysis of conceptual definitions, methodological trends, disciplinary contexts, and institutional perspectives, positioning AI-giarism as a pedagogical and governance-related challenge rather than a purely technological or compliance issue. The findings inform a structured agenda for future research emphasising conceptual clarification, validated measurement, longitudinal inquiry, and policy-aligned ethical frameworks in higher education.





Full Text: PDF



References


Alsharefeen, R. (2025). Faculty as street-level bureaucrats: Discretionary decision-making in the era of generative AI. Frontiers in Education, 10, Article 1349217. https://doi.org/10.3389/feduc.2025.1349217

Bui, T. T. U., & Tong, T. V. A. (2025). The impact of AI writing tools on academic integrity: Unveiling English-majored students’ perceptions and practical solutions. AsiaCALL Online Journal, 16(1), 1–18.

Chan, C. K. Y. (2023). A comprehensive AI policy education framework for university teaching and learning. International Journal of Educational Technology in Higher Education, 20(1), Article 38. https://doi.org/10.1186/s41239-023-00415-1

Harrington, B., Zlotnikova, I., & Nadarajan, G. (2025). Did Alice do wrong? Cross-cultural differences in student perceptions of generative AI use in university computing education. ACM Transactions on Computing Education, 25(2), Article 14. https://doi.org/10.1145/3689214

Kopperoinen, A. (2025). Are business school students using AI to cheat in academia? LUT University Publications.

Lau, Y. L., Abu Bakar, A. L., Chau, S. K., Sik, R. Y., Yap, J. T. K., Yong, H. W., Tan, J. C., & Ambikapathy, A. (2025). Language course writing task and AI-generated writing detection: An ethical concern. Education Sciences, 15(3), Article 312. https://doi.org/10.3390/educsci15030312

Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & PRISMA Group. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. PLoS Medicine, 6(7), e1000097. https://doi.org/10.1371/journal.pmed.1000097

Nelson, A. S., Santamaría, P. V., Javens, J. S., & Ricaurte, M. (2025). Students’ perceptions of generative artificial intelligence (GenAI) use in academic writing in English as a foreign language. Education Sciences, 15(2), Article 198. https://doi.org/10.3390/educsci15020198

Schrepel, T. (2025). Generative AI in legal education: A two-year experiment with ChatGPT. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4765129

Snyder, H. (2019). Literature review as a research methodology: An overview and guidelines. Journal of Business Research, 104, 333–339. https://doi.org/10.1016/j.jbusres.2019.07.039

Toyama, M., & Yamazaki, Y. (2021). A systematic review of research on digital transformation. Journal of Business Research, 133, 374–387. https://doi.org/10.1016/j.jbusres.2021.04.044

Zunder, T. H. (2021). Systematic and semi-systematic reviews in transport research. Transport Reviews, 41(4), 473–489. https://doi.org/10.1080/01441647.2021.1889701




Refbacks

  • There are currently no refbacks.


Copyright (c) 2026 Mira Tania, Cindy Amalia Mughni