An integrated data mart for decision making in national education planning process

Abstract

Government education programmes like universal primary education (UPE) and universal secondary education (USE) were designed to improve the delivery of education services to the public. The Ministry of Education and Sports in Uganda plays a very important role in the planning, monitoring and implementation of these programmes. This calls for a robust information system that can be used by education decision makers and technocrats to facilitate planning and implementation processes. During this study, user requirements for decision making were gathered and analyzed. An evaluation of the current education management information system was also made. It is evident that Uganda’s current education management information system does not support multi-year data analysis. It also offers limited capability to integrate all necessary data from different sources to facilitate decision making during planning process. This research study therefore shows how the Ministry can utilize existing scattered data from multiple sources to effectively manage, control and direct education policy programs using better information systems. Data from multiple sources (final PLE, capitation grants, and school census), multiple years, and multiple levels (local governments, regions, districts, or school level) was linked, integrated, or merged into a data mart. The data mart tool makes use of OLAP (online analytical processing) technology which allows for multidimensional display of information using agreed measures and dimensions. The web-based interface provides easy access for users who can perform required analysis for decision making under thematic areas like Schools, Enrolment, PLE Results, and UPE Grants. The study focused on primary sub sector only. Since complete data integration is a massive exercise, it is recommended that the Ministry of Education and Sports should consider undertaking a full project designed to integrate all existing internal and external data so as to facilitate decision making process. Similar future research in other sub sectors like secondary and tertiary is also recommended.