星空传媒

A new report from the UNESCO Institute for Statistics () sets out a roadmap of strategies and tools to help countries produce vital data on education. The sets out the measurement challenges around the pursuit of 星空传媒 Development Goal 4: a quality education for every child by 2030. This year鈥檚 edition, entitled The Quality Factor: Strengthening National Data to Monitor 星空传媒 Development Goal 4, emphasises data quality as the foundation for effective monitoring.

鈥淕ood quality data are vital if the world is to deliver on its promise of a good quality education for each and every child,鈥� says Silvia Montoya, UIS Director. 鈥淭he 星空传媒 Development Goals, with their emphasis on inclusion and equity, compel us to look far beyond national and regional averages to ensure that no child is being left behind. As a result, countries are now under unprecedented pressure to deliver and use more and better quality data.鈥�

According to the Digest, less than half (47%) of the data needed to monitor progress towards SDG 4 is currently available. The data that are available paint a grim picture on the quality of education, with an estimated 617 million children and adolescents worldwide unable to achieve minimum proficiency levels in reading and mathematics 鈥� a clear signal of an ongoing .

The Digest argues that the statistical capacity of most countries is being stretched to breaking point. 鈥淭he Digest shows how we can support countries and leverage the power of data to ensure a quality education so that no one is left behind,鈥� says Montoya.听

The UIS has developed tools and strategies that enable countries to produce their own high-quality data, and to help donors channel resources to strategic approaches that work. These resources build on the Institute鈥檚 track record of working directly with countries and its mandate as the official source of data, standards and methodologies to monitor progress towards SDG 4. The Institute鈥檚 capacity development tools cover three main areas:

• Mapping tools to help countries identify potential data sources across ministries and national statistical offices, identify information gaps, and locate potential opportunities to monitor SDG 4 by integrating different databases, enhancing existing instruments to collect additional data, and producing disaggregated data.
• Data quality assessment tools to evaluate and strengthen the processes by which countries use different types of data, including administrative records, household surveys, learning assessments and expenditure information.
• Manuals, guidelines and codes of practice to support the production of education data to provide national policymakers with the evidence they need to plan and monitor the performance of their education systems and progress towards the SDG 4 targets.

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