Beyond Academic Integrity: A Human Security Analysis of Generative AI Use in University Students’ Academic Writing

Authors

  • Muhammad Zulfadhli Program Studi Teknik Industri, Universitas Bhayangkara Jakarta Raya, DKI Jakarta, Indonesia
  • Hafizah Program Studi Pendidikan Guru Sekolah Dasar, Universitas Bhayangkara Jakarta Raya, DKI Jakarta, Indonesia
  • Siti Setiawati Program Studi Informatika, Universitas Bhayangkara Jakarta Raya, DKI Jakarta, Indonesia
  • Asep Hidayatullah Program Studi Pendidikan Bahasa Indonesia, Universitas Galuh, Jawa Barat, Indonesia
  • Laely Farokhah Program Studi Pendidikan Guru Sekolah Dasar, Universitas Negeri Jakarta, DKI Jakarta, Indonesia
  • Ella Rahmah Program Studi Teknik Industri, Universitas Bhayangkara Jakarta Raya, DKI Jakarta, Indonesia
  • Annisa Syafia Program Studi Teknik Industri, Universitas Bhayangkara Jakarta Raya, DKI Jakarta, Indonesia

DOI:

https://doi.org/10.55909/jpbs.v5i5.1858

Keywords:

beyond academic integrity, human security analysis, generative AI, students’ academic writing

Abstract

This study aims to analyze students' use of Generative Artificial Intelligence (GenAI) in academic writing through the lens of human security. A descriptive qualitative approach was employed, utilizing data from 60 open-ended questionnaire responses and 35 semi-structured interviews, analyzed using the Framework Method. The findings indicate that students use GenAI for idea development, drafting, language refinement, information seeking, and material comprehension; key benefits include time efficiency, ease of task completion, and support for writing skill development. Questionnaire and interview data also revealed vulnerabilities regarding information reliability, privacy, access inequality, dependency, cognitive autonomy, creativity, authorship, and the clarity of institutional policies. The study concludes that the use of GenAI requires management through information verification, data protection, independent thinking, transparency, AI literacy, and clear institutional guidelines. Therefore, AI governance in higher education should shift from a compliance-oriented approach to a student-centered framework that balances technological benefits, security, equitable access, and academic autonomy.

 

 

References

Afzal, M., Arshad, N., & Shaheen, A. (2025). ChatGPT and the Future of Academic Writing: Enhancing Productivity and Creativity. Journal of Engineering and Computational Intelligence Review, 3(1), 1–11. https://doi.org/10.63544/0drypd66

Aldabbus, S., & Almansouri, E. (2022). Academic Writing Difficulties Encountered by University EFL Learners. British Journal of English Linguistics, 10(3), 1–11. https://doi.org/10.37745/bjel.2013/vol10n3111

Aljuaid, H. (2024). The Impact of Artificial Intelligence Tools on Academic Writing Instruction in Higher Education: A Systematic Review. Arab World English Journal Special Issue on ChatGPT, 26–55. https://doi.org/10.24093/awej/ChatGPT.2

Alyafei, R. A. S. M., Al-Kfairy, M., Alfandi, O., & Alrabaee, S. (2026). Safeguarding Students’ Academic Integrity in the Age of Generative AI: Challenges and Solutions. Kybernetes, 1–19. https://doi.org/10.1108/K-04-2025-0878

Chan, C. K. Y., & Hu, W. (2023). Students’ Voices on Generative AI: Perceptions, Benefits, and Challenges in Higher Education. International journal of educational technology in higher education, 20(1), 43. https://doi.org/10.1186/s41239-023-00411-8

Farokhah, L., Herman, T., Wahyudin, Zulfadhli, M., & Juwita, S. R. (2025). How Can Self-Regulated Learning Supports Mathematics Literacy of Students in Digital Era? A Quantitative Study. Review of Integrative Business and Economics Research, 14(4), 360–374.

Gale, N. K., Heath, G., Cameron, E., Rashid, S., & Redwood, S. (2013). Using The Framework Method for the Analysis of Qualitative Data in Multi-Disciplinary Health Research. BMC Medical Research Methodology, 13, 117. https://doi.org/10.1186/1471-2288-13-117

Hardi, R., Nurmandi, A., Purwaningsih, T., & Manaf, H. A. (2025). Smart City Governance and Interoperability: Enhancing Human Security in Yogyakarta and Makassar, Indonesia. Frontiers in Political Science, 7, 1553177. https://doi.org/10.3389/fpos.2025.1553177

Hongxia, H., & Razali, A. B. (2025). Impact of Chatgpt on English Academic Writing Ability and Engagement of Chinese EFL Undergraduates. International Journal of Instruction, 18(2), 323–346. https://doi.org/10.29333/iji.2025.18218a

Huang, C., Alhur, A. A., Azam, M., & Naeem, S. B. (2025). The Challenge of Academic Integrity in the Age of Generative Artificial Intelligence. Libri, 75(4), 339–354. https://doi.org/10.1515/libri-2025-0024

Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., ... & Kasneci, G. (2023). Chatgpt For Good? On Opportunities and Challenges of Large Language Models for Education. Learning and individual differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274

Lu, Q., Yao, Y., Xiao, L., Yuan, M., Wang, J., & Zhu, X. (2024). Can Chatgpt Effectively Complement Teacher Assessment of Undergraduate Students’ Academic Writing? Assessment & Evaluation in Higher Education, 49(5), 616–633. https://doi.org/10.1080/02602938.2024.2301722

Malik, W., & Gul, S. (2024). Bridging The Gap: Exploring The Intersection of Cybersecurity and Human Security in The Digital Age. Competitive Research Journal Archive, 2(4), 195–202.

Maphoto, K. B., Sevnarayan, K., Mohale, N. E., Suliman, Z., Ntsopi, T. J., & Mokoena, D. (2024). Advancing Students’ Academic Excellence in Distance Education: Exploring the Potential of Generative AI Integration to Improve Academic Writing Skills. Open Praxis, 16(2), 142–159. https://doi.org/10.55982/openpraxis.16.2.649

Perkins, M. (2023). Academic Integrity Considerations of AI Large Language Models in the Post-Pandemic Era: Chatgpt And Beyond. Journal of University Teaching and Learning Practice, 20(2), 1–24. https://doi.org/10.53761/1.20.02.07

Siloko, B. E. (2024). Human Security, Sustainable Livelihoods and Development: The Case off the Niger Delta Region in Nigeria. Global Discourse, 14(2–3), 411–432. https://doi.org/10.1332/20437897Y2024D000000037

Ward, A., Manoharan, S., & Ye, X. (2024). Exploring Academic Integrity in the Age of Generative AI. In 2024 21st International Conference on Information Technology Based Higher Education and Training (ITHET) (pp. 1–5). IEEE. https://doi.org/10.1109/ITHET61869.2024.10837603

Zdravkova, K. (2026). Generative Artificial Intelligence and the Ambiguity of Academic Integrity in Higher Education. Education Sciences, 16(7), 1120. https://doi.org/10.3390/educsci16071120

Zulfadhli, M., Anshori, D. S., Sastromiharjo, A., Farokhah, L., & Juwita, S. R. (2026). The Connection Between Students’ Understanding of Scientific Articles and Writing Skills: A Correlation Study in Higher Education. Review of Integrative Business and Economics Research, 15(1), 776–788.

Downloads

Published

2026-09-18

How to Cite

Zulfadhli, M., Hafizah, Setiawati, S. ., Hidayatullah, A. ., Farokhah, L. ., Rahmah, E. ., & Syafia, A. . (2026). Beyond Academic Integrity: A Human Security Analysis of Generative AI Use in University Students’ Academic Writing. Jurnal Pembelajaran Bahasa Dan Sastra, 5(5), 4235–4250. https://doi.org/10.55909/jpbs.v5i5.1858

Issue

Vol. 5 No. 5 (2026): September 2026 | inprogress

Section

Articles

License

Copyright (c) 2026 Muhammad Zulfadhli, Hafizah, Siti Setiawati, Asep Hidayatullah, Laely Farokhah, Ella Rahmah, Annisa Syafia

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.