Educational Development Index (EDI, NIEPA)
Internationally, Human Development Index (HDI) and Education for All (EFA) Development Index (EFA-DI) have been used for cross country comparisons in overall human development and universalising elementary education respectively. Both HDI and EFA-DI measures outcomes. The HDI measures development by combining indicators of life expectancy, educational attainment and income. It uses adult literacy rates and combined gross enrolment ratio for primary, secondary and tertiary schooling as indicators of educational development and gives adult literacy more significance in computing the index. On the other hand, EFA development index uses one indicator as a proxy measure for each of the four EDI components and each component is assigned equal weight in the overall index. The indicators used are: (i) total primary net enrolment ratio; (ii) adult literacy rate; (iii) survival rate to Grade V; and (iv) average of three gender parity index for primary education, secondary education and adult literacy, with each being weighted equally. The provision and use of elementary education services in India has been improving quite fast during the last decade. However, the development has not been uniform across the states and districts in the country. The elementary education related interventions have been creating and improving access and infrastructure, investing in more teachers and their quality and several processes, aimed at improving educational outcomes related to not only enrolment and retention, but improving the learning levels. From the point of view of an education system that is transforming itself, it is important to look at not only the outcome indicators, but at the input and process indicators too. The purpose of an index that summarizes various aspects related to input, process and outcome indicators is to identify geographic areas that lag behind in overall education development. In India, DISE provides information on various schools based inputs and processes as well some indicators related to outcomes. Based on the DISE data, an effort has been made by the National University of Educational Planning and Administration(NUEPA) and the Government of India (MHRD, Department of School Education and Literacy) to compute an Educational Development Index(EDI), separately for Primary and Upper Primary levels of education and also a composite index for the entire Elementary education1 for which the Government of India constituted a Multi-Disciplinary Expert and Core Group on EDI in2005-06 of which NUEPA was also a member2. It identified indicators and developed computation methodology. The basic purpose of computing an EDI is to know comparative status of a state vis-à-vis other states with regard to different aspects of universalisation.
The Working Group on EDI identified a number of indicators falling under different aspects of universalization of education, covering input, process and outcome indicators. This set of indicators take note of all aspects and is expected to present the true picture of universalisation. The variables used to compute EDI in the present exercise are presented in Table E1. It may also be noted that EDI in India is still evolving and each indicator used have a specific purpose. However, they are not fixed and hence a review is being undertaken periodically and new indicators are added to the existing set of indicators or a few of them maybe dropped out or used in the modified form. From 2008-09 EDI computation, improved version of a few variables has been used. Percentage of schools with SCR > 60 and PTR > 60 are replaced with Percentage of schools with SCR > 40 and PTR > 40. Percentage of female teachers has been modified with percentage of schools with female teachers (in schools with 2 and more teachers). Similarly single-teacher schools are replaced with percentage of schools with less than 2 teachers (primary schools only).Percentage of schools with < 3 teachers is replaced with Percentage of schools with< 3 (upper primary only)teachers. One new variable is added in case of outcome indicators i.e. Transition rate from Primary to Upper Primary level (only for Upper Primary level).Average student-classroom ratio, pupil-teacher ratio and percentage of passed children to total enrolment are deleted. As many as 21 indicators have been used in computing EDI which are further re-grouped into the following four sub-groups:
- Teachers, and
- Outcome Indicators
DISE provides information in case of most of the seindicators that have been used to compute the EDI at Primary and Upper Primary levels of education in 2009-10. Under the access indicators, two indicators namely, percentage of un-served habitations and availability of schools per thousand child population (6-11/11-14 year) have been used. The projected child population provided by the Office of the Registrar General of India has been used while the percentage of un-served habitations has been obtained from the All-India Education Survey: 2002-03. It may be noted that the information on un-served habitations is latest available for year 2002-03, though a number of Primary and Upper Primary schools have been opened across the county since then. Thus the same may not present the true picture with regard to availability of schooling facility in 2009-10. However, in view of the absence of other independent source of data on coverage of habitations, except state reports, EDI continues to use2002-03 data, which will be updated as and when independent data becomes available. In the absence of which, the same has been corrected with reference to new schools (government) opened since 2002-03. In addition, ratio of Primary to Upper Primary schools/sections has also been used as an indicator of access at Upper Primary level of education. While computing the ratio, both Primary and Upper Primary schools as well as Primary and Upper Primary sections attached to Secondary and Higher Secondary schools have been considered. The Working Group on EDI identified four indicators under infrastructure set of indicators. Percentage of schools with student-classroom above 40, percentage of schools with drinking water facility and percentage of schools with common toilet and percentage of schools with girls’ toilet are such indicators. The third set of indicators, five in numbers, are teacher related indicators. Percentage of Schools with Female teachers, Schools with Pupil-Teacher Ratio > 40, Percentage of Schools with< 3 teachers, Percentage of schools with less than 2 teachers, Teachers without Professional Qualification are such indicators under this category. Out of which percentage of schools with less than 2 teachers is used at Primary level and percentage of schools with less than 3teachers is used at Upper Primary level. The last set of indicators is related to outcome indicators; this set contains a total of 9 indicators amongst which Gross Enrolment Ratio is the most important one. While computing GER, projected population provided by the Office of the Registrar General of India have been used to work out 6-11 and 11-14 year population. For assessing the participation of SC/ST children, percentage difference of SC/ST population in 2001 Census and percentage of SC/ST enrolment to total enrolment at Primary and Upper Primary level of education has been used (in case of negative difference, the same is treated as zero; thus meaning that all children are enrolled).Gender Parity Index (enrolment) is another important indicator which shows the extent of participation of girls compared to their counterpart boys in educational programmes. One of the other important outcome indicators is ratio of exit class over Class I enrolment which has been used only at Primary level. At Upper Primary level, a new indicator, namely Transition Rate from Primary to Upper Primary Level of education has been used. This is a new indicator added from last year. A few states reported this to be above 100 percent which is treated as hundred in EDI computations. Average dropout and repetition rates are other important outcome indicators which have been computed by using DISE data based on common schools in 2008-09 and 2009-10. In case of states having negative dropout rate are considered as missing values. Percentage of appeared children passing with 60 percent and above marks in terminal Grades IV/V and VII/VIII, considered as proxy indicators of learners’ attainment, are also used as outcome indicators in EDI. Needless to mention that while analyzing EDI, data limitations presented above should be kept in mind.
- Indicators used for constructing EDI were pre-determined by the MHRD, Government of India. Contributions received from the members of the Multi-Disciplinary Expert and Core Group on EDI constituted by the MHRD in 2005-06 is gratefully acknowledged.
- Indicators were normalized before the Principal Component Analysis was applied to decide the factor loadings and weights.
- Separate dimensional indices were constructed first before finalizing the EDI; and Number of access-less habitations has been obtained from the Seventh All India Education Survey and drop-out rate at Upper Primary level from the Selected Educational Statistics.
- Wherever necessary projected child population provided by the Office of the Registrar General of India has been used.
Methodology of EDI
A cursory look at the set of 21 indicators reveals that they have either direct or inverse relationship. Some of these indicators are in ratio form and others in percentage form. In view of this, each indicator considered in EDI computation is first required to be normalised. Normalised values range between0 and 1 and it indicates the relative position of states with reference to a selected indicator. Thus in case of each indicator, in view of its nature, the best value and the worst value are identified which are then used to transform by using the following formula: habitations (best value, zero), percentage of schools having PTR and SCR above 40 (best value, zero), and percentage of teachers without professional qualification (best value, zero). Upon receiving normalized values, the next step was to assign factor loadings and weights. Weights to indicators can be assigned in a number of ways. One can judge the significance of an indicator and accordingly assign weight which is based up on the value judgment of an individual. On the other hand, one can assign equal weights to all the indicators or assign different weights to different indicators according to significance of an indicator. The weight-age in the computation of an EDI in the present exercise is determined by using Factor Loadings and Eigen Values from the Principal Component Analysis (PCA). PCA helps in reducing large number of indicators in a few (indicators/categories) without losing their significance which also simplifies analysis. PCA helps in weighing each indicator according to their statistical significance. The components identified are known as Principal Components which explain maximum variance among a set of indicators. Therefore, the Principal Component Analysis is used to obtain factor loading and weights of the indicators in each of the four sets of indicators, which is done first at the Primary level and then at the Upper Primary level of education. Needless to mention that Primary stage/level of education consists of all Primary schools/sections irrespective of the type of schools; and Upper Primary stage/level of education consists of all the Upper Primary schools/sections irrespective of the type of schools. This means that all the schools imparting elementary education across the country irrespective of school type are considered in computing EDI which includes schools under the government as well as private managements. Thus, indices for all the four types of indicators have been first obtained separately for Primary and Upper Primary level of education which is then used to compute composite EDI for Primary and Upper Primary level of education where NVij represents normalized index of ith indicator of jth state and Xi is the original value of the ‘ith’ indicator. Unlike previous years, in case of a few variables, policy options were explored to identify the best values instead of based on the observed values (normalized values in case of such variables, if obtained above one are treated as one). Some of such variables are: access-less separately. Composite EDI for Primary and Upper Primary levels of education is used to obtain composite EDI for the Elementary level of education.