The Implementation of Learning Analytics in Managerial Decision-Making in Educational Institutions

Abstract

The increasing availability of educational big data has transformed decision-making processes in educational institutions, necessitating the integration of learning analytics to support data-driven managerial practices. This study aims to analyze the implementation of learning analytics in strengthening managerial decision-making through an integrated and evidence-based approach. The research employs a qualitative method with a descriptive-analytical design using a literature-based approach. Data were collected from recent scholarly journal articles and analyzed through content and thematic analysis to identify key patterns related to learning analytics, decision-making processes, and institutional management. The findings reveal that learning analytics significantly enhances academic monitoring, curriculum evaluation, resource allocation, and strategic planning by providing predictive insights and real-time data. It also improves decision accuracy and organizational performance compared to traditional intuition-based approaches. However, challenges such as limited organizational readiness, data integration issues, and ethical concerns regarding data governance remain critical barriers. The discussion emphasizes that successful implementation requires strong leadership support, a data-driven organizational culture, adequate technological infrastructure, and continuous staff training. In conclusion, learning analytics can effectively strengthen managerial decision-making in educational institutions when supported by integrated governance, organizational readiness, and ethical data practices