A Pilot Study of Estimating Out-Of-School Children in India

30 November 2016
A Pilot Study of Estimating Out-Of-School Children in India
By Public Accountability and Governance in Education (PAGE) at CPR

Why is the study important?

The numbers of out-of-school children (OOSC) put out by various official sources in India, show wide variations. For instance, the Ministry of Human Resource Development (MHRD) survey by Social and Rural Research Institute – Indian Market Research Bureau (SRI-IMRB) estimate of this figure is around 6 million, while for the same year 2014, the National Sample Survey (NSS) figure is around 20 million.

The problems lie not just in the definitions of OOSC used by different sources but also in the systems of collecting and collating data as well as the methods of estimation used by each source:

  • For instance, all school-based information defines an out of school child as one that is enrolled one year and not the next and/or continuously absent for a certain period of time. Household level data of never enrolled is not included in these estimates. Besides, school data  is collected only by teachers who may have a conflict of interest in relation to some indicators, such as inflating student attendance for purposes of mid-day meal allocations and or preserving their own jobs, which are dependent on enrolment figures. Teacher may also be under pressure from parents to not strike names of children off the records. 
  • Drop-out rates, which are estimates based on subtracting days of continuous absence over a period of time from the enrolment figures also vary from state to state (two weeks of absence in Karnataka to three months in Gujarat). This makes inter-state comparisons extremely difficult. 
  • Further, these estimates do not take into account sporadic or irregular attendance, which is known to be very high in most rural schools.
  • Finally household level data on never enrolled also tends to be highly inaccurate due to i) lack of records on births and deaths and, ii) each data collection agency posing the question in a different way, eliciting a different response from the household. Lack of standardisation across basic indicators thus obscures the data count.

These anomalies call for a closer look at the issues around estimation of OOSC, particularly the attendance patterns of children, with special emphasis on sporadic or irregular attendance, as that has an impact on learning levels as well. With learning outcomes dominating the policy discourse on education, unpacking the links between attendance and learning and its distribution across social categories is therefore important.

This study of out-of-school children was undertaken in order to understand the phenomena of OOSC through an intensive micro-study of all children in a single Gram Panchayat (GP or Panchayat).

How was the study conducted?

It is based on a household survey that provides the population of children in the GP who attend schools located within the boundaries of the Gram Panchayat, as well as a survey of all enrolled children in schools located within the GP.

This enables a mapping of children from the household survey data and school data to obtain a final sample of children from the Panchayat attending schools located in the Panchayat.  Thereafter the attendance of these mapped children is tracked through the course of one academic year by making bi-weekly visits (before and after the serving of the Mid-Day Meal (MDM)) to capture attendance patterns of the children.  

The study surveys every school age child in the selected Panchayat, who attends school in the Panchayat region, with the intention of:

  • delineating OOSC by gender, social category and other household factors that might have an impact on attendance rates;
  • deciphering the attendance patterns and hence the extent of real drop -outs among children according to gender and social category. 

The major emphasis of the current study is thus to provide a methodological framework to broaden the scope of defining OOSC by highlighting important issues that have hitherto been neglected in the estimation and analysis of out of school data.

Findings from the study:

The tracking of attendance and the patterns it discerns tells us the following:

  • Irregular or sporadic attendance is a huge phenomena–more than twice the number of children who recorded continuous absence are actually sporadically absent–but not recorded in the official figures related to OOSC.
  • Children who are never enrolled constitute an ‘invisible’ category as far as the system is concerned, as they are not recorded in any official document within the education system.
  • Extremely poor birth registration records exacerbate the problem of invisibility of children not in school.
  • There are wide variations in the attendance of children from different social groups, including gender, which need further research in order to develop strategies for mainstreaming them.
  • Various pressures–both at the societal and the school level–have led to overstating attendance of children in the school records to the detriment of children and their chances of improving their learning levels. This is reflected in the difference between the school records and head count data collected during the survey.

Policy implications of the study findings:

The survey results in several policy implications. These include:

  • First, a better data regime, that accounts for OOSC in a more robust as well as realistic manner, taking into account sporadic absence as well as the invisible children;
  • Second, adjusting the school calendar to align it with the agricultural cycle of the area permitting children who are needed by the families in peak season to do so, without disrupting their education;
  • Third, management of a local database by the Panchayat for purposes of data validation as well as tracking basic indicators such as student and teacher attendance, in addition to improved birth and death registration. For some indicators, community authentication would be helpful to check for anomalies that creep in, especially in instances where teachers may have an incentive in misreporting. While this authentication may not be very precise, it would help to red flag some figures, which could then be cross checked using more rigorous methods.
  • Fourth, developing an early warning system to help identify children at the risk of dropping out so that the school administration and community may take steps early on to prevent the eventual dropping-out of the child.

The full report can be accessed here.

The views shared belong to individual faculty and researchers and do not represent an institutional stance on the issue.