UNRAVELING THE ESSENCE OF DEEP LEARNING APPROACH APPLICATION: IDENTIFYING CRITICAL FACTORS FOR EFFECTIVE IMPLEMENTATION IN SCHOOLS

Abstract

The Deep Learning Approach is increasingly viewed as a valuable educational model for preparing students with crucial 21st-century skills, including critical thinking, creativity, teamwork, and effective communication. Nonetheless, the effective application of the approach is significantly influenced by the specific local context, the capabilities of implementers at various levels, and their understanding and interpretation of Deep Learning concepts and principles.  This research seeks to gain in-depth insights into practitioners' experiences and perspectives, as well as the support systems needed to implement a Deep Learning approach in schools in Southwest Aceh. This is a qualitative methodology that uses Focus Group Discussions (FGDs) and interviews as the main methods of data collection, which were later analyzed using NVivo 12 software. The findings indicate that the implementation of Deep Learning remains in its early, fragmented stage, limited to a small number of schools, and primarily focused on preparatory activities such as teacher training, lesson planning, and limited dissemination. The study also reveals divergent stakeholder perspectives: the Education Office assumes a predominantly administrative role; school principals emphasize instructional leadership. At the same time, teachers demonstrate strong enthusiasm, but face constraints related to administrative workload and limited digital literacy. Furthermore, effective implementation requires systemic support, including alignment between national and local policies, strengthened digital infrastructure, and structured, sustained professional mentoring. These findings highlight the importance of context-responsive and system-level support in addressing implementation gaps and enabling effective Deep Learning practices in decentralized education systems.