INTEGRATING DEEP LEARNING FRAMEWORKS IN DIGITAL SCHOOL TRANSFORMATION: A QUALITATIVE STUDY ON STRATEGY FOR NURTURING FUTURE INNOVATORS IN INDONESA - Cici Puspaningrum; Nada Nabilah (RADJA PUBLIKA, 2025)
In the era of rapid technological advancement, integrating deep learning frameworks into schools is increasingly seen as a catalyst for cultivating innovation-driven students. This study explores how deep learning—particularly tools such as TensorFlow and Keras—is being utilized within the Indonesian school transformation agenda to support the development of future innovators. Using a qualitative approach, data were gathered through interviews, focus group discussions, and document analysis involving teachers, school leaders, and education experts from various digital-ready and underserved schools. The study revealed three key themes: pedagogical innovation through AI, implementation challenges, and shifts in innovation culture. Deep learning was found to enhance interdisciplinary, project-based learning and student agency, yet its success depended heavily on infrastructure, teacher competence, and visionary leadership. While urban schools showed promising practices, rural contexts faced persistent barriers. These findings highlight that the true transformative potential of deep learning lies not only in its technical application but in the socio-pedagogical ecosystems that support it. The study calls for balanced investment in both technology and human capital to position schools as innovation incubators for Indonesia’s AI-powered future.