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Data for Learning: Building a Smart Education Data System
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About this ebook
Data are a crucial ingredient in any successful education system, but building and sustaining a data system are challenging tasks. Many countries around the world have spent significant resources but still struggle to accomplish a functioning Education Management Information System (EMIS). On the other hand, countries that have created successful systems are harnessing the power of data to improve education outcomes.
Increasingly, EMISs are moving away from using data narrowly for counting students and schools. Instead, they use data to drive system-wide innovations, accountability, professionalization, and, most important, quality and learning. This broader use of data also benefits classroom instruction and support at schools. An effective data system ensures that education cycles, from preschool to tertiary, are aligned and that the education system is monitored so it can achieve its ultimate goal—producing graduates able to successfully transition into the labor market and contribute to the overall national economy. The “Data for Learning†? titles in the Directions in Development series shed light on challenges in building a data system and provides actionable direction on how to navigate the complex issues associated with education data for better learning outcomes and beyond.
Data for Learning: Building a Smart Education Data System details the key ingredients of successful data systems, including tangible examples, common pitfalls, and good practices. It is a resource for policy makers working to craft the vision and strategic road map of an EMIS, as well as a handbook to assist teams and decision makers in avoiding common mistakes. It is designed to provide the how-to and guide countries at various stages of EMIS deployment. The forthcoming second volume, Data for Learning: Reaching the Promise of Education Data, will focus on digging deeper into the practical applications of education data systems by various user groups in different settings.
Increasingly, EMISs are moving away from using data narrowly for counting students and schools. Instead, they use data to drive system-wide innovations, accountability, professionalization, and, most important, quality and learning. This broader use of data also benefits classroom instruction and support at schools. An effective data system ensures that education cycles, from preschool to tertiary, are aligned and that the education system is monitored so it can achieve its ultimate goal—producing graduates able to successfully transition into the labor market and contribute to the overall national economy. The “Data for Learning†? titles in the Directions in Development series shed light on challenges in building a data system and provides actionable direction on how to navigate the complex issues associated with education data for better learning outcomes and beyond.
Data for Learning: Building a Smart Education Data System details the key ingredients of successful data systems, including tangible examples, common pitfalls, and good practices. It is a resource for policy makers working to craft the vision and strategic road map of an EMIS, as well as a handbook to assist teams and decision makers in avoiding common mistakes. It is designed to provide the how-to and guide countries at various stages of EMIS deployment. The forthcoming second volume, Data for Learning: Reaching the Promise of Education Data, will focus on digging deeper into the practical applications of education data systems by various user groups in different settings.
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