Analysis of Educational Planning Policy in Developing a Deep Learning-Based Curriculum to Shape Learners’ Character - Sekartika, Titin; Amalia, Kaniati; Hazin, Mufarrihul; Purwoko, Budi (Publik : (Jurnal Ilmu Administrasi), 2025)
The regulatory implications of implementing Deep Learning require adjustments to Government and Ministerial Regulations to improve flexibility and quality of learning. The application of Deep Learning as a learning approach in Indonesia not only changes the way of teaching in the classroom, but also has an impact on existing educational regulations. This research uses a literature study approach, collecting data from books, journal articles and education policy documents on education planning in developing curriculum based on deep learning approaches, and character education. In-depth analysis was conducted by identifying the main focus and linking it to best practices in education, as well as analyzing case studies of successful implementation of deep learning approaches. Recent statistical data is also integrated to strengthen the research findings. This article aims to analyze the educational planning policies underlying the development of deep learning-based curriculum as an innovative effort in learner character building. The findings of the analysis show that existing policies tend not to explicitly accommodate the potential of deep learning in the affective domain and holistic character development. Implementing a deep learning-based curriculum for character building requires a paradigm shift in education planning. Future policies need to more clearly articulate the character goals to be achieved through deep learning, provide a framework that supports the development of innovative pedagogy, and ensure the readiness of infrastructure and educator capacity. The synergy between policy makers and education practitioners is crucial to realize the transformative potential of education in shaping a generation with strong and adaptive characters.