Education 2030: Equity and quality with a lifelong learning perspective

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WEF
World Education Forum

 

This blog shows how the World Inequality Database on Education (WIDE) helps track inequalities in education over time and across countries. It reveals a new finding from the database, released to coincide with the World Education Forum at Incheon, that the poorest young women are six times less likely to be able to read than the richest.

Five words are making the headlines in Incheon at the third World Education Forum: equity, inclusion, learning, quality, and lifelong learning.

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World Inequality Database on Education (WIDE)

Since 2002, the EFA Global Monitoring Report has worked in different ways to keep these five themes high on the international education agenda. But one of its tools, the World Inequality Database on Education (WIDE), has since 2012 proven particularly effective in serving this purpose. WIDE is interactive and enables users to compare education outcomes between countries, and between groups within countries, according to factors associated with inequality such as wealth, gender, ethnicity and location. Moreover, users can create charts, infographics and tables from the data, and download, print or share them online.

The database is updated each year. In 2013/4, completion rates for primary and lower secondary education were reported, which gave a more insightful picture of how far we were from achieving key aspects of the EFA vision. In addition, results from learning achievement surveys were added to the usual measures of school participation.  In 2015, WIDE has been expanded to include information on upper secondary completion, transition rates to secondary education, and youth literacy rates. In addition, national surveys were included for large countries like Brazil, India, Mexico, Morocco, and South Africa, which have not been covered regularly by the two main international household survey programmes, the USAID-funded Demographic and Health Survey and the UNICEF Multiple Indicator Cluster Survey.

It was on the basis of combining such data that it was possible for the EFA Global Monitoring Report to estimate that about 100 million children in low and middle income countries do not complete primary school; and that 250 million children of primary school age do not achieve the minimum learning standards in reading and mathematics.

However, the main power of WIDE is the ability to show the extent of country level inequality. To mark the occasion of the World Education Forum at Incheon, a new policy paper is being released today, which showcases the capabilities of the database. A key finding adds to our knowledge showing how children from the poorest households face increasing hurdles from accessing school to progressing through the grades, and ultimately to benefiting from their school experience.

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We know that those from the poorest 20% of households are four times as likely as those from the richest 20% of households not to be in school, five times as likely not to complete primary school, and, as these new calculations show, among young women, six times as likely not to be able to read. Without, at a minimum, foundational literacy and numeracy skills, there are no building blocks for further flexible lifelong learning opportunities.

In some countries these disparities are even higher and demand sustained policy attention. The new booklet identifies twenty countries with some of the largest gaps in recent years in primary completion ratesbetween youth from the poorest and the richest households. In Cameroon in 2011, where 70% of 15-year olds completed primary school, as few as 21% of the poorest reached that target compared with 95% of the richest. By contrast, in Sierra Leone with a similar average completion rate in 2013, 44% of the poorest completed primary school compared with 88% of the richest.

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In addition, the WIDE database shows that overlapping disadvantages can compound education disparities. For example, in Nigeria in 2013, the lower secondary completion rate was 75% in urban areas and 37% in rural areas. Within rural areas, there were large wealth gaps as well: only 10% of the poorest were completing lower secondary school compared with 93% of the richest. And, while there was near gender parity among the rural rich, the poorest rural males (17%) were more than five times as likely to complete lower secondary school as the poorest rural females (3%).

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The draft Framework for Action Education 2030, which is debated this week in Incheon, urges efforts “to extend the ability of governments to report education indicators disaggregated by characteristics such as sex, wealth, location, ethnicity, language, socio-economic status or disability (and their combinations)”. In that context, it quotes the WIDE database as “an example of how such information could be made available to inform action”.

More can be done to improve this database and how it is used. WIDE aimed above all to have a demonstration effect: that it is possible to focus attention on the marginalized and mobilize governments and donors to adapt policies to their needs. However, many governments continue to minimize issues of inequality in their national education plans; donors rarely evaluate their policies from an equity perspective; and, globally, we are yet to develop regional and global baselines of inequality in education – and reach a consensus on what target to set in reducing inequality in the coming fifteen years. The World Education Forum is a great opportunity to turn a page on those fronts.

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This work has been reprinted from the World Education Blog and is therefore made available under the same license.

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