Doha, Qatar, May 7 (IPS) – In 2024, Globally, 273 million children, adolescents and youth were out of school According to UNESCO Institute for Statistics. Although this is a staggering number, the data is incomplete. 2026 global education monitoring report warn that the global out-of-school population could be reduced by at least 13 million if humanitarian sources are used to close data gaps in conflict-affected contexts.
When education data fails, most likely the children who will be excluded will not simply be out of school. There are also people who are completely missing from the systems meant to find them.
This is why data gaps are not just a technical issue, they are a structural driver of exclusion. If a child is not in the dataset, they are less likely to show up in school planning processes, teacher-allocation formulas, textbook purchasing systems, transportation routes, or targeted social protection programs that could keep them enrolled.
The 2026 GEM report highlights the depth of the challenge. In primary and secondary education, One in three countries does not report inequalities based on urban-rural location and one in two countries does not report inequalities based on wealth. When such information is missing, education policies relying on national averages hide those children who are furthest behind.
Why do children disappear from education data?
An Education Foundation Above All Contemporary paper on counting of children not going to school This explains how administrative enrollment figures may differ from reality in predictable ways. The system may undercount children who are present but not registered; Reduce the count of late registrants when data is taken only once at the beginning of the year; or overstating participation by counting registered children who never attend.
And, these are not small measurement errors. This is precisely how children slip through institutional cracks, especially those affected by poverty, displacement, disability, language barriers and gender discrimination.
finding missing children
Consider what happens when programs take identity as seriously as instruction.
In our joint project with Educate Girls in rural Rajasthan in India, we found that official child-tracking data often misses children in remote villages. To address this, community volunteers conducted a large-scale door-to-door survey of more than three million households in more than 9,000 villages to identify out-of-school girls.
This effort enabled the program to identify, enroll, and retain thousands of girls who were previously absent from official records. The lesson from this exercise was simple: It’s hard to serve children you can’t see. But when systems intentionally invest in identification and verification, those learners can be found.
The same challenge applies to children with disabilities, who are often hidden by stigma and underestimated by systems that do not consistently measure disability. In our ten-country inclusive education program implemented with Humanity and Inclusion across Africa, we sought to “bring children out of the shadows” through community outreach, disability-sensitive identification tools, and ongoing tracking of participation. The program successfully enrolled more than 32,000 schoolchildren with disability and supported strong retention outcomes.
These experiences show that exclusion does not just mean access to education. It is also about whether the system can identify and track children who face multiple barriers to participation.
What can robust education data systems do
In many countries, governments and partners are beginning to recognize that strong education data systems are essential to identifying and supporting the most excluded learners. For example, in Rwanda, the Zero Out of School Children initiative uses the Waliku application, a digital monitoring tool developed with partners including Save the Children and the Ministry of Education.
Teachers use mobile platforms to register out-of-school children, record attendance and track absenteeism patterns. When repeated absences occur, the system generates follow-up alerts so that school or community workers can contact families and support re-enrollment.
In partnership with UNICEF and the Government of the Gambia, efforts are underway to integrate education data with health and civil registration systems through DHIS2, which will help authorities identify children missing from school records and coordinate responses across sectors.
Other partnerships show how digital tools can strengthen detection and surveillance in different contexts.
In Nigeria, a partnership project with UNICEF has developed the Tracking Re-Entry of Children into Education (TRACE) system that combines community mapping and school records to track children’s identities through enrollment and progress.
In Kenya, under the EAA Foundation-UNICEF partnership, a digital attendance application enables real-time monitoring of school attendance, allowing schools to detect absenteeism patterns and intervene early.
Digital systems are proving valuable even in delicate contexts. In Syria, the EAA Foundation-UNICEF partnership project has developed a self-learning program child monitoring system to track children participating in alternative learning pathways when formal schooling is interrupted.
In Zanzibar, an EAA Foundation-UNICEF partnership project has developed a mobile-based monitoring tool that supports the identification and follow-up of out-of-school children at the community level, while an EAA Foundation-World Bank partnership project in Djibouti has developed digital tools that help track participation in alternative education programs and support the transition to formal schooling.
Overall, these initiatives reflect a significant shift: education systems are moving from periodic aggregate reporting to child-level identification, real-time monitoring, and early-warning systems.
As these systems evolve, particularly with advances in analytics and artificial intelligence, they provide the ability to predict dropout risks and guide targeted interventions, helping to ensure that every child remains visible within the education system.
So, what should change?
Governments should treat education data not just as a reporting obligation, but as an inclusion tool. This means investing in learner-level education information systems that can uniquely identify learners, track attendance and progress, and, where appropriate, securely link education data with civil registration, health and social security systems.
Governments should also regularly combine and integrate data from different sources to address gaps in national statistics.
Second, development partners should fund data systems as core public infrastructure. Without the ability to know which children are missing, where they are, and what barriers they face, funding classrooms, teachers, and learning materials is unsustainable when leaving the ministry.
Results-based financing should reward governments and implementers for verified inclusion outcomes, not just overall enrolment.
Education agencies and partners should standardize how the world counts ‘excluded’. Globally tested equipment already exists. For example, UNICEF-Washington Group Child Functioning ModuleProvides a standardized approach to identifying children with disabilities in surveys and administrative systems.
For displaced learners, strong coordination between education and humanitarian data systems is essential. According to UNHCR, there are 12.4 million Refugee children of school age worldwide, and about 46% of them are out of school.
The conclusion is straightforward: the most excluded children are often the least counted.
Bridging the education gap requires bridging the education data gap, so that every child is visible, accessible and well supported before exclusion becomes permanent.
IPS UN Bureau
© Inter Press Service (20260507070225) – All rights reserved. Original source: Inter Press Service
