Strategi Pengembangan Human Capital Guru Berbasis Deep Learning: Analisis SWOT pada Sekolah Dasar Berbeda Kesiapan

Abstract

This study aims to analyze strategies for developing teacher human capital through deep learning in elementary schools at different levels of organizational readiness. The study uses a qualitative, multi-site case study design across two public elementary schools in one sub-district that represent high and low readiness. Data were collected through in-depth interviews, learning observations, and document analysis, then analyzed using an interactive model and SWOT analysis to formulate teacher development strategies. The results show that schools with high readiness develop teacher human capital more comprehensively through active instructional leadership, a collaborative culture, and support for digital infrastructure, enabling the implementation of deep learning at a more advanced stage. Conversely, schools with low readiness still face limitations in teacher pedagogical capacity and digital literacy, requiring a phased development strategy that focuses on strengthening basic competencies and continuous pedagogical mentoring. Cross-site analysis confirms that effective teacher development strategies are context-specific and differentiated by school readiness level. This study concludes that the development of teacher human capital through deep learning should be designed with readiness in mind, integrated with instructional leadership, and aligned with school organizational culture. These findings make a conceptual contribution by explaining the importance of differentiating teacher development strategies to encourage the implementation of sustainable deep learning in elementary schools, especially in developing countries with varying levels of school readiness.