9:00 AM - 5:00 PM
The Numbers Game in Education: A look beneath the surface
Reliable and regular education data provides information on inputs, processes and outcomes of schooling. It can play an important role in planning and policy formulation and in monitoring and evaluation of the schooling system. Over the past two decades the Ministry of Human Development (MHRD) has put systems in place to enable the collection and use of data to formulate annual plans and monitor and evaluate the country’s progress towards achieving different educational goals– primarily for children in the age group 6 to 13 years.
Multiplicity of Data Sources
However these are not the only sources of education data in India. Government and nongovernment agencies have been collectingdata on children and school indiactors for several years, albeit each at different though regular intervals. Overall , there are primarily two types of data sources, which provide information on children in 6-13 years age group –i) the administrative data sources that collect data from schools and thus focus on in-school children,and ii) the household surveys that collect data on both in-school and out-of-school children. The administrative sources include the Selected Educational Statistics (SES), the All India Educational Surveys (AIES) and the more recently established District Information System for Education (DISE) –all of which are collected and maintained under the central Ministry of Human Resource Development (MHRD). The important national level household surveys include the annual sample surveys conducted by the NSSO and the decadal Census, as well as the out of school surveys commissioned by the MHRD (conducted by SRI-IMRB in the years of 2006, 2009 and 2014). As part of the SSA initiative annual household surveys have also been conducted in all states since 2002,to identify out of school children in the same age group. In addition, multipurpose household surveys that have been conducted by non-government organizations like the NFHS, NCAER and ASER, also provide education related information on children corresponding to this age group.
Linking data sources to policy and planning exercise
In spite of these multiple data sources, the use of education data has been quite limited. There are a few reasons for this. One, the different data collection agencies collect data for specific purposes., and theyseldom take into account the framework of other data sources at the time of planning and analysis. This is true even within the government sector. For instance,while MHRD relies on the data from the SRI-IMRB survey, each State uses its own household surveys (conducted as part of SSA) to identify and estimate children out of school. But eventually, the MHRD and the State Education Departments use administrative data sources, primarily the DISE data, for planning [and monitoring] schooling development. In other words, the data from household surveys, which include the estimate of out of school children are not part of the planning process. Household survey data and DISE data should be complementary to each other and both should be used together for monitoring and planning, but this is rarely done at the National or State level. The data from the national level household surveys like NSSO and NFHS,which provide detailed data on school attendance and educational attainment of children from different socioeconomic groups are not taken into account either at the planning stage.
Two, preliminary analyses of the different data sources indicate several differences in definitions used and estimation methodologies. So the indicators constructed from the different data sources are quite different. While the indicators constructed from schools surveys and household surveys are not directly comparable and may vary, the estimates calculated from different household surveys vary as well, as do the estimates calculated from the different administrative sources. For example two large sample household surveys were conducted in 2014. A Report based on 71st round of NSSO indicates thataround 10% of children in the 6 to 13 years age group were not attending school. With more than 200 mn children in this age group in India, this translates into 20million childrenbeing out of school. The Report on Out-of-School Children based on the survey conducted by SRI-IMRB found only 3% of children in the age group were out of school, which in numbers comes to around 6 million children. DISE data collects data on inputs, outcomes and enrolment from school. The 2013-14 round of DISE data estimates an enrolment rate around 91% for children in the 6 to 13 age group, suggesting around 9% of children are out of school, which would be around 18 million children.
Three, data needs to be interpreted with care. Data is often assumed to be neutral, but one needs to be aware that it is not so. Data can be collected to inform the system as well as to judge it. People involved in the data collection process are conscious that it may be used against them. These concerns underlie the process of data collection and data analysis. For example in schools with declining enrolment a teacher is likely to be transferred when number of students fall below a minimum. So there will be an inherent upward bias in enrolment figures of these schools. Data at school and habitation level are fed upwards. So there are possibilities of the picture being clouded at block and district level as well, if it is likely to adversely impact the jobs of education staff at these levels. So the data collection system may be designed to emphasize the positives and mask any negatives.
Impact of data on education governance and research
1. Policy Formulation:
The impact of these differences on policy formulation is likely to be significant. Not only does the estimated proportion of out of school children vary, the profiles of these children vary considerably as well. The variations at state level are even higher. The NSSO data suggests that Uttar Pradesh, Bihar and Chhattisgarh are the States with the highest proportion of children in the 6 to 13 years age group,not attending school. The SRI-IMRB data indicates a very different set of states with the highest proportions of out of school children in the same age group, ie.,Odisha, Uttarakhand and Rajasthan. So depending on the data source, the scope of implementation of the targeted schemes and budget allocation are likely to be different.
These disparities in education statistics confuse the researchers and practitioners, and raise questions regarding the data quality of different data sets. Unfortunately little concern over these discrepancies is seen at the state or the national level, unlike the debates and discussions, which continue over poverty and unemployment estimates.
There is an urgent need now for the different agencies involved in data collection to take cognizance of these issues. The data users (planners, implementers, researchers) need to be aware of the variations in objectives, definitions and procedures underlying different data sources. They need to collaborate and to discuss among themselves the reasons for these differences and the ways these can be resolved. The meeting on August 19, 2015 is being organized as a preliminary attempt to bring together the different stakeholders to discuss these issues.
List of Speakers:
1. Dr TCA Anant, Chief Statistician of India, [tbc]
2. Dr. Arun Mehta, Director, DISE [confirmed]
3. Dr Himanshu, Prof of Economics, JNU [confirmed]
4. Dr. Shailendra Sigdel, UNESCO Institute of Statistics [confirmed]
5. Mr Khuntia, Secretary SE&EL, MHRD [tbc]
6. ABL Srivastava, IMRB [confirmed]
7. Sukhpreet Sekhon, ASER Centre [confirmed]
8. Ms. Anuradha De, Director CORD, [confirmed]
9. Ms. Vimala Ramachandra, Education Research Unit [confirmed]
10. Education Department representatives from Rajasthan & Delhi [confirmed]
11. Dr. JBG Tilak, Professor, NUEPA [confirmed]