Data-Driven Decision-Making in Educational and Professional Policy

This study examines how Data-Driven Decision-Making (DDDM) is operationalized in educational policy across selected countries and evaluates the adaptability of these global practices to the Ukrainian context. Using a comparative qualitative methodology, the research analyzes international models—such as centralized Education Management Information Systems (EMIS), AI-based learning platforms, and stakeholder dashboards—from countries including the United States, Finland, Singapore, Bangladesh, and South Sudan. These were assessed alongside Ukraine’s existing digital infrastructure, including platforms such as Mriia, Diia.Education, and POVIR. Findings indicate that while foundational systems exist in Ukraine, they are fragmented, lack interoperability, and suffer from disparities in digital access and professional capacity. The study highlights transferable lessons from global systems, such as the importance of policy-aligned EMIS frameworks, the utility of public-facing dashboards, and the value of open-source platforms for cost-effective scalability. A phased roadmap is proposed, recommending system consolidation, investment in data literacy training, and the development of a cross-sectoral data governance strategy. Limitations include the exclusive reliance on secondary data and the absence of field-based perspectives. Future research should prioritize stakeholder engagement and longitudinal studies of pilot initiatives. The study contributes novel insights into post-conflict digital education governance, offering policy-relevant strategies to strengthen data-informed decision-making in Ukraine. Particular attention is given to higher professional education, including pharmacy and legal training programs, where the digitalization of curricula and instructional innovation can be enhanced through targeted DDDM adoption.