Empowering ethical ai usage in course assignment: A guide for Islamic revealed knowledge students at centre for foundation studies
DOI:
https://doi.org/10.15282/ijhtc.v11i2.14068Keywords:
Artificial Intelligence, Course Assignments, Ethical Guideline, Islamic Revealed KnowledgeAbstract
The increasing use of Artificial Intelligence (AI) tools in higher education has transformed how students access information, particularly for those studying Islamic Revealed Knowledge (IRK) at the Centre for Foundation Studies, International Islamic University Malaysia (IIUM). This shift raises ethical concerns about aligning AI use with Islamic values and academic integrity. While AI can improve learning efficiency, its misuse may lead to plagiarism and an overreliance on technology in Islamic studies. This study aims to create important guidelines that integrate Islamic ethical principles into AI-assisted course assignments. A purposive sampling technique was used to select a sample of 160 IRK students from CFS IIUM for this study. Preliminary results from the study indicate significant reliance to AI among IRK students without having proper guideline. The findings indicate that ethical AI use in Islamic academic settings should adhere to principles like Amānah (trust), Ikhlāṣ (sincerity), and Taqwā (God-consciousness), which underpin Tawhidic epistemology. These values help to ensure responsible AI usage that maintains the integrity of Islamic knowledge and academic honesty. The study precisely recommends ethical guidelines specifically tailored for the IRK context to promote responsible AI usage in line with academic and Islamic values. In conclusion, the paper presents strategic recommendations to assist educators in embracing an advanced education system that collaborates AI with Islamic ethics, ultimately preparing Islamic students to meet future need and critical challenges.
Downloads
References
https://archive.org/details/quran-english-translation-and-commentary-by-yusuf-ali.
Bicknell, K., Brust, C., & Settles, B. (2023). How Duolingo’s AI learns what you need to learn: The language-learning app tries to emulate a great human tutor. IEEE Spectrum, 60(3), 28–33. https://doi.org/10.1109/MSPEC.2023.10061631.
Carobene, A., Padoan, A., Cabitza, F., Banfi, G., & Plebani, M. (2024). Rising adoption of artificial intelligence in scientific publishing: Evaluating the role, risks, and ethical implications in paper drafting and review process. Clinical Chemistry and Laboratory Medicine, 62(5), 835–843. https://doi.org/10.1515/cclm-2023-1136.
Giglio, A. D., & Costa, M.U.P.D. (2023). The use of artificial intelligence to improve the scientific writing of non-native English speakers. Revista da Associação Médica Brasileira, 69(9), e20230560. https://doi.org/10.1590/1806-9282.20230560.
Jukiewicz, M. (2024). The future of grading programming assignments in education: The role of ChatGPT in automating the assessment and feedback process. Thinking Skills and Creativity, 52, 101522. https://doi.org/10.1016/j.tsc.2024.101522.
Kementerian Pendidikan Tinggi. (2025). Dasar pendigitalan pendidikan tinggi 2025–2030. Kementerian Pendidikan Tinggi. https://repositori.mohe.gov.my/220/1/Dasar_Pendigitalan_Pendidikan_Tinggi_2025-2030.pdf.
Koppisetti, V. S. K. (2024). Deep learning: Advancements and applications in artificial intelligence. ESP International Journal of Advancements in Computational Technology, 2(2), 106–113. https://doi.org/10.56472/25838628/IJACT-V2I2P114.
Qadir, J. (2023). Engineering education in the era of ChatGPT: Promise and pitfalls of generative AI for education. 2023 IEEE Global Engineering Education Conference,1-9.https://doi.org/10.1109/educon54358.2023.10125121.
Shetye, S. (2024). An evaluation of Khanmigo, a generative AI tool, as a computer-assisted language learning app. Studies in Applied Linguistics and TESOL, 24(1). https://doi.org/10.52214/salt.v24i1.12869.
Sounderajah, V., Ashrafian, H., Golub, R. M., Shetty, S., De Fauw, J., Hooft, L., Moons, K., Collins, G., Moher, D., Bossuyt, P. M., Darzi, A., Karthikesalingam, A., Denniston, A. K., Mateen, B. A., Ting, D., Treanor, D., King, D., Greaves, F., Godwin, J., Pearson-Stuttard, J., … STARD-AI Steering Committee (2021). Developing a reporting guideline for artificial intelligence-centred diagnostic test accuracy studies: the STARD-AI protocol. BMJ open, 11(6), e047709.https://doi.org/10.1136/bmjopen-2020-047709.
UNESCO. (2021). AI and education: Guidance for policy-makers. UNESCO. https://doi.org/10.54675/PCSP7350.
Vieriu, A. M., & Petrea, G. (2025). The impact of artificial intelligence (AI) on students’ academic development. Education Sciences, 15(3), 343. https://doi.org/10.3390/educsci15030343.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 The Author(s)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
