Development of Islamic Religious Education (PAI) Learning Based on Deep Learning at the Elementary, Junior High, and Senior High School Levels
DOI:
https://doi.org/10.25217/jrie.v7i1.6606Keywords:
Pembelajaran PAI, Deep Learning, Teknologi PendidikanAbstract
Islamic Religious Education (PAI) at the primary and secondary school levels faces major challenges in addressing social phenomena among students, such as the rise of violence, intolerance, and the misuse of digital technology. Conventional one-way approaches are considered insufficient to engage students’ affective and spiritual dimensions. Therefore, innovative learning models that are adaptive and contextual are urgently needed by leveraging technological advancements, particularly artificial intelligence based on deep learning. This study aims to examine and design strategies for developing deep learning–based PAI instruction that is relevant to implementation at the elementary, junior high, and senior high school levels, while also identifying the challenges and implications of its application within the Indonesian educational context. The research employed a qualitative approach using library research methods. Data were collected from a range of scientific literature, journal articles, and educational policy reports. Content analysis was conducted to identify key concepts, trends, and gaps in previous studies. The findings reveal that the integration of deep learning in PAI instruction can foster more personalized, adaptive, and reflective learning. Each educational level requires a different approach, ranging from interactive storytelling at the elementary level, adaptive content at the junior high level, to reflective chatbots at the senior high level. However, its implementation faces technical, ethical, and human resource challenges that are not yet evenly addressed. The development of deep learning–based PAI instruction has the potential to enhance learning effectiveness and support students in internalizing Islamic values more profoundly. This study recommends teacher training, the development of Islamic technology-based curricula, and cross-sectoral collaboration to realize religious education that remains relevant in the digital era
References
Amin, L. H., Nashir, M. J., Abdullah, H., Aulia, N., & Zaki, A. N. (2024). A Qualitative Analysis of Obstacles and Challenges in Implementing the EDLINK Application at the Surakarta. Edumaspul: Jurnal Pendidikan, 8(1). https://doi.org/10.33487/edumaspul.v8i1.7629
An, A. N., et al. (2025). Understanding the integration of deep learning and artificial intelligence in Qur’anic education and research through bibliometric analysis. Education Policy International Journal, 14, Article e2025012. https://doi.org/10.22521/edupij.2025.14.12
Baidowi, K. (2023). Empowering Self-Regulated Learning: A Case Study Using Edlink Application At PBA IAIBA Purwoasri Kediri. Kitaba, 1(3). https://doi.org/10.18860/kitaba.v1i3.23408
Darwanto, D., & Khasanah, M. (2021). Pembelajaran Daring dengan Menggunakan Platform Edlink. Eksponen, 11(1). https://doi.org/10.47637/eksponen.v11i1.366
Fitriani, D., Alaby, A., & Kusumajati, W. (2022). Project-Based Learning Through Sevima Edlink Apps to Improve Students' Academic Writing of Education Program at STKIP Kusumanegara. JELTL, 5(1). https://doi.org/10.47080/jeltl.v5i1.1747
Hidayat, M., et al. (2024). Multimedia-based interactive teaching materials and automatic assessment in PAI using deep learning. Indonesian Journal of Islamic Studies, 1(2). https://doi.org/10.1234/ijis.v1i2.909
Jasmansyah, J., et al. (2025). A study of deep learning approach in Islamic education and Western education perspective: A literature review. In Proceedings of the 5th International Conference on Education, Humanities and Social Science (ICEHoS) (pp. 93–108). Atlantis Press. https://doi.org/10.2991/978-2-38476-450-1_7
Koubaa, A., et al. (2019). Activity monitoring of Islamic prayer (salat) postures using deep learning. arXiv Preprint. https://doi.org/10.48550/arXiv.1911.04102
Mursalin, E., Setiaji, A., & Kasim, E. W. (2022). Penerapan Learning Management Systems (LMS) berbantuan Sevima Edlink: Efektifkah dalam menunjang Perkuliahan Daring? Jurnal Pendidikan Edutama, 9(1). https://doi.org/10.30734/jpe.v9i1.2254
Mustoip, S., et al. (2024). Implementation of artificial intelligence in Islamic religious education learning at madrasah ibtidaiyah. Eduprof: Islamic Education Journal, 6(1), 72–77. https://doi.org/10.47453/eduprof.v6i1.268
Owoc, M. L., et al. (2021). Artificial intelligence technologies in education: Benefits, challenges and strategies of implementation. arXiv Preprint. https://doi.org/10.48550/arXiv.2102.09365
Papakostas, C. (2025). Artificial intelligence in religious education: Ethical, predictive, and adaptive dimensions. Religions, 16(5), 563. https://doi.org/10.3390/rel16050563
Purnamawati, S., & Mahartika, I. (2023). Penggunaan E-learning Sevima Edlink: Kajian Persepsi Siswa. Konfigurasi, 7(1). https://doi.org/10.24014/konfigurasi.v7i1.21618
Sahlan, S., Donuata, P., & Fitriani, N. (2022). How do students respond to the use of the Sevima Edlink Application in learning at the university? Jurnal Riset dan Kajian Pendidikan Fisika, 9(2). https://doi.org/10.12928/jrkpf.v9i2.141
Wahyudi, A. (2020). Sevima Edlink Social Learning Network for Nursing Science Students at STIK Binahusada Palembang. Language and Education Journal, 5(1). https://doi.org/10.52237/lej.v5i1.153
Zahrudin, D., & Al Bahij, A. (2025). A deep learning-based ISMUBA instructional model to foster integrity character in elementary Islamic education. International Journal of Research and Innovation in Social Science, 9(03), 5602–5609. https://doi.org/10.47772/IJRISS.2025.903SEDU0409
Zhang, J. (2025). Cognitive bias in generative AI influences religious education. Scientific Reports. https://doi.org/10.1038/s41598-025-99121-6
Zukri, P. A., Asynari, E., & Jatmiko, N. (2020). Standar Kelengkapan Fitur E-learning Supply Chain Management pada Produk Backlog Menggunakan Metodologi Scrum. STMSI, 9(3). https://doi.org/10.32520/STMSI.V9I3.738
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