Implementing Deep Learning Approaches in Primary Education: A Literature Review - Muhammad Feri; Nur Ismiati; Widya Rahmawati Al-Nur; Farah Nabila Akbar (Jurnal VARIDIKA, 2025)
Deep learning in education has often been associated with technology and artificial intelligence, while its pedagogical meaning remains underexplored, particularly in the context of primary education. Although joyful, meaningful, and mindful learning strategies are widely practiced, there is still a lack of systematic reviews that integrate these approaches into a coherent framework of deep learning in the Indonesian context. This gap highlights the need to examine how deep learning can be adapted to foster holistic student development. This study explores the application of deep learning approaches in primary education through a literature review. Utilizing the PRISMA framework, relevant national and international publications from 2014 to 2024 were reviewed and analyzed. The results indicate that while the term deep learning is often linked to technology, its pedagogical dimensions are still underutilized in classrooms. Key obstacles to implementation include limited teacher training, rigid curricula, inadequate facilities, and resistance to change in educational mindsets. Despite these challenges, deep learning offers significant potential to cultivate critical thinking, empathy, collaboration, and lifelong learning in students. The findings are expected to benefit educators, policymakers, and curriculum developers by providing insights into how deep learning approaches can be aligned with student needs and future educational demands. This review also serves as a reference for researchers to design contextually relevant models of deep learning in Indonesian primary schools