Ethical Integration of Generative Artificial Intelligence in Islamic Education through Teachers’ Pedagogical Practices and Academic Integrity
Keywords:
Generative Artificial Intelligence, Islamic Education, AI Literacy, Pedagogical Integration, Academic Integrity, Islamic EthicsAbstract
Generative artificial intelligence (GenAI) is increasingly transforming educational practices, yet its integration within Islamic education raises questions concerning pedagogical effectiveness, academic integrity, and moral responsibility. This study investigates how Islamic school teachers integrate GenAI into teaching and learning, examines academic integrity challenges emerging from AI-assisted learning, and analyzes how ethical values guide responsible AI use. Employing a qualitative multiple-case study design, the research involved teachers, school leaders, and students from Islamic educational institutions. Data were collected through semi-structured interviews, classroom observations, and document analysis and analyzed thematically through within-case and cross-case comparison, supported by triangulation and member checking. The findings indicate that teachers use GenAI for lesson planning, instructional material development, assessment design, and differentiated learning, positioning the technology as a pedagogical augmentation tool rather than a substitute for teachers. However, AI-generated assignments, plagiarism, student dependency, uncertainty about authorship, and difficulties in assessing authentic student competence present significant academic integrity challenges. Teachers respond through assessment redesign, AI-use guidelines, verification practices, and increased emphasis on students’ intellectual contributions. Ethical values, particularly amanah, sidq, responsibility, and intellectual integrity, provide a foundation for responsible AI integration. Based on these findings, the study proposes an Ethical Generative AI Integration Model connecting AI literacy, pedagogical integration, academic integrity, Islamic ethical mediation, and responsible AI use, with teacher guidance and human oversight operating across the model.
References
Akgun, S., & Greenhow, C. (2022). Artificial intelligence in education: Addressing ethical challenges in K-12 settings. AI and Ethics, 2, 431–440. https://doi.org/10.1007/s43681-021-00096-7
Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021). On the dangers of stochastic parrots: Can language models be too big? Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, 610–623. https://doi.org/10.1145/3442188.3445922
Bittle, K., & El-Gayar, O. (2025). Generative AI and academic integrity in higher education: A systematic review and research agenda. Information, 16(4), 296. https://doi.org/10.3390/info16040296
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
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, Article 43. https://doi.org/10.1186/s41239-023-00411-8
Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2024). Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International, 61(2), 228–239. https://doi.org/10.1080/14703297.2023.2190148
Creswell, J. W., & Poth, C. N. (2018). Qualitative inquiry and research design: Choosing among five approaches (4th ed.). SAGE Publications.
Eaton, S. E. (2023). Post-plagiarism: Transdisciplinary ethics and integrity in the age of artificial intelligence and neurotechnology. International Journal for Educational Integrity, 19, Article 23. https://doi.org/10.1007/s40979-023-00146-z
Holmes, W., Persson, J., Chounta, I.-A., Wasson, B., & Dimitrova, V. (2022). Artificial intelligence and education: A critical view through the lens of human rights, democracy and the rule of law. Council of Europe.
Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdel, C., Pfeiffer, F., Poquet, O., Sailer, M., Schmidt, A., Seidel, T., … 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
Kvale, S., & Brinkmann, S. (2015). InterViews: Learning the craft of qualitative research interviewing (3rd ed.). SAGE Publications.
Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry. SAGE Publications.
Miao, F., & Cukurova, M. (2024). AI competency framework for teachers. UNESCO. https://doi.org/10.54675/ZJTE2084
Montenegro-Rueda, M., Fernández-Cerero, J., Fernández-Batanero, J. M., & López-Meneses, E. (2023). Impact of the implementation of ChatGPT in education: A systematic review. Computers, 12(8), Article 153. https://doi.org/10.3390/computers12080153
Ouyang, F., Zheng, L., & Jiao, P. (2022). Artificial intelligence in online higher education: A systematic review of empirical research from 2011 to 2020. Education and Information Technologies, 27, 7893–7925. https://doi.org/10.1007/s10639-022-10925-9
Patton, M. Q. (2015). Qualitative research & evaluation methods: Integrating theory and practice (4th ed.). SAGE Publications.
Perkins, M. (2023). Academic integrity considerations of AI large language models in the post-pandemic era: ChatGPT and beyond. Journal of University Teaching & Learning Practice, 20(2), Article 07. https://doi.org/10.53761/1.20.02.07
Schmid, R., Brianza, E., & Petko, D. (2021). Developing a short assessment instrument for technological pedagogical content knowledge (TPACK.xs) and comparing the factor structure of different TPACK variants. Computers & Education, 171, 104271. https://doi.org/10.1016/j.compedu.2021.104271
UNESCO. (2021). Recommendation on the ethics of artificial intelligence. UNESCO.
UNESCO. (2023). Guidance for generative AI in education and research. UNESCO.
Wan Daud, W. M. N. (1998). The educational philosophy and practice of Syed Muhammad Naquib Al-Attas: An exposition of the original concept of Islamization. International Institute of Islamic Thought and Civilization.
Yin, R. K. (2018). Case study research and applications: Design and methods (6th ed.). SAGE Publications.
Yusuf, A., Pervin, N., Román-González, M., & Noor, N. M. (2024). Generative AI in education and research: A systematic mapping review. Review of Education, 12(2), e3489. https://doi.org/10.1002/rev3.3489
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education—Where are the educators? International Journal of Educational Technology in Higher Education, 16, Article 39. https://doi.org/10.1186/s41239-019-0171-0
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