Out of school children: evidence brief

Autor(es): Dyer, Caroline; Bhattacharjea, Suman; Alcott, Benjamin; Thomas, Steffi Elizabeth

Organisation(s): People's Action for Learning Network; University of Leeds (UK). Faculty of Social Sciences

Date: 2021

Pages: 13 p.

Serie: Leave No One Behind in Education: evidence brief

Series Volume: 2


In 2010, UNICEF and the UNESCO Institute for Statistics (UIS), working with national governments, launched a global Out Of School Children Initiative (OOSCI), which the Global Partnership for Education (GPE) joined in 2013. OOSCI’s objectives include deriving profiles of out-of-school children, analysing barriers that have led to their exclusion, and encouraging stronger international attention towards bringing all children into school. There is a new urgency to this topic, since, in 2020, the global COVID pandemic precipitated widespread drop out from school and exposed the fragility of education systems, particularly for children in highly socio-economically disadvantaged families. This Evidence Brief focuses on the concept of being left behind in education, with reference to OOSC. There are two prominent international frameworks in use for evidencing exclusion, upon which this Brief draws. One derives from the OOSCI and the second is the CREATE Consortium’s model of zones of exclusion. This Evidence Brief also draws on three categories of being left behind (1. Left out altogether; 2. Enrolled but left behind; 3. Likely to leave) and populates them with data from six countries in the PAL Network: Kenya, India, Mexico, Pakistan, Tanzania, and Uganda. In addition, it investigates the implications of being left behind for children’s learning. In so doing, it contributes to the existing evidence in two key ways: First, it demonstrates how data from the PAL Network can be used to populate these zones of exclusion. Because these are household-level data sets, they provide information that many other data sources cannot. Second, it illuminates how household surveys can be used to identify specific groups of children in the ‘at risk’ category, which is an important capability for future planning.

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