In what could be the first of its kind, a pilot study based in Kumbhalgarh, Rajasthan, has tried to identify out-of-school children (OOSC) and created a format for an Early Warning System (EWS) to determine potential drop-outs. The study was conducted by the Centre for Policy Research (CPR) and though small in outreach, it managed to draw out important conclusions about the OOSC which is important because India has the highest number of OOSCs in South Asia and second highest in the world. With Prime Minister Narendra Modi’s aim to ensure education to every child, OOSC remains a major challenge since there is a lack of defined data that helps in drafting policies.

The pilot study found out that Scheduled Tribes (STs) had the lowest and most variable attendance rates. Interestingly, attendance of minority children was the highest, followed by OBC students. There was a marginal difference in male and female attendance, with males’ being slightly higher.

Kiran Bhatty, Senior Fellow, CPR, talking about the methodology of the study said, “One panchayat called Gawar in Kumbhalgarh, Rajasthan, was selected and attendance of children studying till Class VIII was tracked. It covered nine government schools, 470 households and four villages. A total of 611 children were tracked throughout the year through unannounced visits twice a week before and after mid-day meals. Data from household surveys and school registers were matched and examined for discrepancies.”

Estimating OOSCs is particularly difficult because the definition of a “drop-out” varies with data sources as well as jurisdiction. Different states in India have different definitions. It ranges from seven days of continuous absence in Karnataka to three months of continuous absence in Gujarat, while the SSA norms deem 45 days of continuous absence as a drop-out. But none of the definitions takes into account sporadic absenteeism or irregular attendance patterns in the estimation of OOSC.

The study found that during the course of 2015-16, analysis of school records showed that 24 children in total had dropped out as per official definition i.e. absence of 45 days or more continuously. Of these, 15 had been removed from the school records, while nine remained in the school records. As per the definition of the study, i.e absence of 45 days or more irrespective of continuity, 317 children had dropped out.

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Radhika Saraf, CPR, who was also a part of the pilot study explaining the EWS, said, “We also developed the idea of an Early Warning System (EWS) to red-flag potential drop-outs. This has been done by identifying a child absent for a minimum of 20 days over a 72-day or three-month period. The result was that the total number of children at the risk of dropping out from school was 515.

Kiran Bhatty said, “The regression analysis of the study told us that caste had a significant impact on average attendance. Students belonging to the minority section had higher attendance than those belonging to SC category. While those belonging to the ST category had lower attendance compared to the SC category, there is no significant difference between average attendance of SCs and OBCs. The average student attendance was significantly higher in schools with female teachers. Attendance was highest in schools with fifth as highest grade, followed by schools with eighth grade as the highest grade. It was the lowest in schools with eleventh as the highest grade. Higher the class, more the chances of dropping out.”

Other findings of the study were that the school infrastructure had a significant impact on student attendance. Local conditions such as agricultural seasons have an impact on attendance patterns. 

The study recommended that the definition of OOSC should be expanded to include regularity of attendance. Household and school data bases should be aligned. Local database at the panchayat level should be updated with strict maintenance of birth registration records. A system should be introduced to red-flag irregular attendance in the school and the school calendar should be set up in accordance with agricultural cycle.

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