SUPERVISI BERBASIS DATA DALAM SUPERVISI PENDIDIKAN

Abstract

Educational supervision plays an important role in improving the quality of learning. However, supervisory practices that rely solely on supervisors’ intuition and subjective experience often result in inaccurate assessments that are difficult to justify. In response to these limitations, the paradigm of data-based or data-driven decision-making has emerged, placing objective evidence as the primary basis for the supervision process. This article aims to examine the concept, theoretical foundations, components, implementation, benefits, challenges, and risks of data-based supervision in the context of educational supervision. The method used is a library research approach by reviewing national and international journal articles published between 2019 and 2026. The findings indicate that data-based supervision supports more accurate, systematic, and accountable decision-making compared to traditional supervision and is increasingly supported by the use of digital platforms. Nevertheless, its implementation still faces challenges, including limited data quality, low data analysis capacity among supervisors, resistance to change, and the risk of data being used punitively rather than for professional development. This article recommends strengthening training, technological support, and coaching-oriented data governance to ensure the sustainable implementation of data-based supervision.