Deep Learning-Based Planning Model for Islamic Education in Indonesian Integrated Schools

The digital transformation in education necessitates a new approach to teaching Islamic Religious Education (IRE), particularly in the context of SMPIT Fitrah Insani Leles Garut. This study addresses the integration of deep learning (DL) methods into IRE learning planning, a topic that has rarely been researched. Using a qualitative approach with an intrinsic case study design, data were collected through in-depth interviews, participatory observation, and documentation studies. The focus was on exploring the integration of the DL curriculum, institutional readiness, teacher preparedness, and the development of a DL-based IRE learning planning model. The findings revealed that the integration of DL into the IRE curriculum is still in its early stages, with limited digital infrastructure and low teacher pedagogical literacy. However, quantitative results indicated a positive trend, with students showing a 30% increase in engagement when using DL-based methods, especially in project-based learning and contextual activities. Despite these early successes, a systematic DL-based IRE learning planning model is necessary for further development, supported by policies, teacher training, and infrastructure improvement. This study contributes to the development of a technology-based Islamic curriculum that is contextual, adaptable to the 21st-century educational landscape, and demonstrates potential for improving IRE learning outcomes.