Macro Data Governance Policies in Public Learning and Education

Abstract

This study aims to systematically review and analyze macro-level data governance policies in public learning and education to identify their institutional, ethical, and technological dimensions. The research employed a qualitative systematic review approach. Data were collected through targeted searches in international databases such as Scopus, Web of Science, and Google Scholar. A total of 12 relevant scholarly articles were selected and analyzed thematically using Nvivo software version 14. The analysis followed open, axial, and selective coding, leading to the identification of three main themes: policy and institutional frameworks, ethics and data trust, and digital transformation in educational data governance. Credibility was ensured through theme verification and theoretical saturation. Findings revealed that educational data governance relies on three key pillars: institutional policymaking and data regulation to ensure transparency and accountability; ethical and security considerations in protecting educational data and fostering public trust; and technological capacity building through digital infrastructures and data literacy among teachers and administrators. The results also indicated that successful data governance policies are those that balance technological innovation with ethical principles and promote data-driven educational equity. The study concludes that data governance in public education is not merely a technological necessity but also an institutional and social imperative. Its success depends on collaboration between governments, technology sectors, and civil organizations to transform data into a tool for informed decision-making, educational justice, and learning quality improvement. Strengthening legal frameworks, enhancing data ethics education, and developing flexible technological infrastructures are essential prerequisites for achieving this goal.