Is Fifty Percent GER at Higher Education Level by 2035 Possible?

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Arun C Mehta
Formerly Professor & Head of EMIS Department
NIEPA, New Delhi
E-mail: acmehta100@gmail.com

Introduction

Much before the National Education Policy (NEP) 2020, the Government of India through the University Grants Commission and the Department of Higher Education, Ministry of HRD/Education resolved to achieve a Gross Enrolment Ratio (GER) of 30 percent at the higher education level by the year 2020. Rashtriya Uchchatar Shiksha Abhiyan of the Ministry of Education also set a GER target of 32 percent at higher education level by the year 2022. Apart from 50 percent GER at the higher education level by the year 2035, the following are some of the other important policy resolutions as specified in the National Education Policy 2020 which was approved by the Union Cabinet in its meeting held on 29^th July 2020 under the Chairmanship of the Prime Minister of India.

·        Multi-disciplinary holistic education at the undergraduate level

·        Under Graduate degree to be of either 3 or 4 years, with a provision to issue certification after completion of each year

·        Higher Education Body Commission of India to be the single umbrella for higher education

·        Aim to achieve 100 percent youth and adult literacy by 2030

·        Education sector to reach 6 percent of GDP at the earliest (from its present 4.6 percent)

·        Multidisciplinary Education & Research Universities are to be set up in each district

·        Students from underprivileged classes to be incentivized per merit

·        Expansion of Open and distance learning across the country

·        Graded accreditation & autonomy to achieve excellence in the next 15 years

·        Comprehensive National Curriculum Framework for Teacher Education to be formulated

·        To promote the use of technology, National Educational Technology Forum to be formed; etc.

 

Tables 50% Increase in Higher Education Enrolment by 2035 Arun C Mehta

 

In addition to the target to achieve a 100 percent Gross Enrollment Ratio at school education level by 2030, the following proposals have also been made in NEP 2020 concerning school education in India; instead, the target would have been fixed to achieve a 100 percent adjusted-Net Enrolment Ratio (Adjusted-NER) which is considered a better indicator of participation. In this brief note, we examine whether the Higher Education level alone is capable of achieving a 50 percent GER from its 2018-19 level in the year 2035? Is a moot question that has been examined from different angles including the present status of school education in general and secondary & higher secondary levels in India, in particular. What would be the size of higher education enrolment; if 50 percent GER is to be obtained in 2035 will be another question that would be explored. This has become more so important given the pandemic because of which a significant decline in enrolment in general and school education, in particular, is expected in years that follow, and enrolment at a higher education may also not escape. In addition, the slow down of the economy (GDP contracted by 7.3 percent. in 2020-21) may also adversely affect enrolment at higher education level from the year 2020-21; and thereafter until the economy gets back on to the recovery path which may not happen in the immediate near future

·        Target to achieve 100 percent GER in school education by 2030

·        Education for all children between 3-6 years by 2025

·        Replacing the existing 10+2 with 5+3+3+4: After five years in pre-primary, students to aim at enhanced skills in the new pedagogical system

·        Medium of instruction till Class 5, to be home language or mother tongue

·        Board examination to be broken into two, to test core capabilities

·        Emphasis on socially disadvantaged, girls, socio-cultural identity children for education

·        By 2025, at least 50 percent of students to have exposure to vocational education; etc.

Many of these policy resolutions like the 6 percent expenditure of GDP on education are not new and were also part of the various commissions and committees constituted by the Government of India from time to time including the National Education Commission (1964-1966), popularly known as Kothari Commission. While on the one hand, NEP 2020, clearly specified the year by which the improved GER at higher education level (by 2035) and 100 percent GER at school education level (by 2030) is to be achieved but fail to specify the year by which 6 percent expenditure of the GDP will be attained; rather it has simply said it be achieved at the earliest which has not seen the light of the day even after more than five decades after the same was first recommended. Before we examine the present status of higher education in India and the implication of achieving 50 per GER by 2035, let us first discuss and re-define the Gross Enrolment Ratio.

Redefining Gross Enrolment Ratio

Unlike school education level at which enrolment based indicators such as Gross & Net enrolment ratio as well as Age-specific and Adjusted-NER are frequently computed and use in plan formulation, at the higher education level only Gross Enrolment Ratio is being used to examine the participation of a relevant age-specific population i.e. 18 to 23 years in the higher education programmes. For calculating GER at any level of education, information on total enrolment in a year and the corresponding age-specific population in that year is required. While total enrolment and its male and female bifurcation, as well as enrolment by the social category i.e. Scheduled Castes & Scheduled Tribes, is available from the All-India Survey on Higher Education (AISHS, latest for 2019-20) but the same is not true for the corresponding age-specific population the main source of which is the Census & Registrar General of India, the latest Census figures being available for the year 2011. In the absence of an official projected population based on the 2011 Census, earlier projections based on population up to 2001 are being used by the Ministry of Education to estimate the age-specific population in a year which is adjusted given the total 2011 Census population (details can be seen under the Statistics Section of the Official Website of Department of School Education & Literacy). Because of the limitations in the projected population, GER and other enrolment-based indicators have been seen off the mark in the past decade which is true for all levels of education. Therefore, the latest GER for 2019-20 and also in the past years, the same must be analyzed in light of these limitations. With 50 percent GER at the higher education level, the quantum increase of enrolment in absolute terms cannot be known unless the reliable estimate of the population between the age-group  18 to 23 years is known in the year 2035. The GER for the year 2021 based on the actual Census 2021 population when available may reveal the real situation concerning the participation of 18 to 23 years population in higher education programmes; it is likely to show a declining trend because of the ongoing pandemic across the country.

As per AISHE 2019-10, the GER at the higher education level increased to 27.1 percent from its previous level of 26.3 percent in 2018-19. On the other hand, in absolute terms, the higher education enrolment increased from 37.4 million to 38.5 million during the same period; thus showing an increase of 1.1 million or 2.94 percent over the previous year. A Gross Enrolment Ratio of 27.1 percent roughly indicates that the balance of 72.9 percent population of age group 18 to 23 years is not enrolled in higher education programmes. Can all the remaining 72.9 percent population be treated as out of the education system? Certainly not as a few of them may still either be enrolled in lower levels (not completed higher secondary level), a few of them maybe never enrolled or dropped out from the system, or a few of them may also be enrolled in foreign universities? Compared to overall GER at higher education level, though improved, the GER of Scheduled Castes & Scheduled Tribes population is still low at 23 and 18 percent respectively as against 26.9 percent for male and 27.3 percent for female population. Time has come to explore alternate enrollment-based indicators also for the higher education level (Mehta, 2002). Can higher education grow independently? Can higher education enrolment grow independent to the lower level i.e. higher secondary level which is expected to send graduates to it? Certainly not. Deliberations by Varghese & Mehta (1999) in the case of a World Bank-assisted study on the Upper Primary level of education is worth mentioning.“Universalization of upper primary education in India is normally discussed in terms of enrolling and retaining all children belonging to the age group 11 to 14. This seems more to be a desirable goal to be achieved in the long run than a realizable target at the present levels of development of primary education. Enrollment is a function of the relevant age group at the primary level of education. However, enrolment in upper primary schools is more a function of primary education completion rates than a function of the relevant age group. It is logical to argue that all children in the relevant age group (11 to 14) cannot be enrolled in upper primary classes unless they complete the primary level of education. In other words, all relevant age group children can be provided upper primary education only when all children of the primary school-going age group are enrolled, retained, and complete the primary stage of education. Since primary education is not yet universalized, this implies that the universalization of upper primary education means providing upper primary education for all children who have completed the primary level of education. The present study has adopted this as the operational definition of universalization of upper primary education in India. However, once universalization of primary education is attained, then there cannot be any difference between providing the upper primary level of education to all age group children and those who complete the primary stage of education. The effort at present needs to be to improve the inter-stage transition ratios from primary to upper primary levels of education.”

The above argument is also very much true for the higher education level which will grow in the line of enrolment at the immediate lower level, i.e. higher secondary level which is supposed to supply a continuous flow of higher secondary graduates to the higher education level. This means that the population of age 18 to 23 years, all cannot be admitted to the higher education system simply because of reason that they are not eligible. Higher education level can only accommodate higher secondary graduates. In the light of these observations, there is a need to redefine the Gross Enrolment Ratio at the higher education level to get a better picture of the participation of the relevant age population in higher education programmes. Therefore, instead of a total 18 to 23 years population, the number of higher secondary graduates may be considered in computing ratio which can be termed as Effective Enrolment Ratio at the higher education level.

Another indicator that plays an important role for enrolment at the higher education level to grow is the transition rate from higher secondary to higher education level which can be computed by using the number of higher secondary graduates the system has produced in the previous year to the total number of students admitted in the first year of graduation during the next year is multiplied by 100 to get the transition rate. The future course of enrolment at the higher education level will be guided by these two indicators. Unfortunately, both of these indicators are not readily available from official sources.  Based on few assumptions, NIEPA (December 2020), in its recent study on NEP 2020: Implementation Strategies attempted transition rate from secondary to higher education level (88.1 percent) and used the same in building up different developmental scenarios towards assessing the NPE 2020 goal of 100 percent GER at school level in 2030 and 50 percent GER at the higher education level in 2035. In the light of these observations policy directive of 50 per GER at higher education level should be examined in terms of effective-GER and transition rate from higher secondary to the higher education level rather than simply based on GER. A low transition rate may adversely affect prospects of higher education enrolment to grow in the years that follow.

Effective-Enrolment Ratio = Number of students admitted in the first year of graduation in a year is divided by the number of higher secondary graduates the system has produced in the previous year is multiplied by 100

Transition Rate from Higher Secondary to Higher Education Level = Number of higher secondary graduates the system has produced is divided by the number of students admitted in the first year of graduation level during the next year is multiplied by 100

 Projected Population (18 to 23 years)

To know the size of the higher education enrolment in 2035, we need a projected population of age-group 18 to 23 years in that year. Generally, population projections are made available from sources, like United Nations Population Division (UNPD), the World Bank, and the United Nations Population Fund (UNFPA).  In addition, individual researchers also provide projections for the country as a whole or even at the sub-national level. It was also a practice of the Registrar General & Census Commissioner, India to undertake projections immediately after the latest census figures are out on behalf of the Planning Commission (now renamed as NITI Aayog) who in turn used to set up a committee of experts which was first constituted in the year 1958 which continued up to the Census 2001. Unlike the previous constitution of the Expert Committees, the Technical Group on Population Projections based on the 2011 Census was constituted by the National Commission on Population, Ministry of Health & Family Welfare, Government of India on July 2014 report of which was made available in the public domain as late as on July 2020. In the absence of the Official Projections enrollment-based indicators, such as GER were computed based on the adjusted projections made earlier based on up to the 2001 Census. Since the Official Projections were released in July 2020 and AISHE 2018-19 in August 2019, AISHE couldn’t use the Official Projections made available by the Technical Group on Population Projections. But AISHE 2019-20 GER which was released in June 2021 is also not based on the official projections for the unknown reasons.

GER 2019-20: Based on Expert Committee & United Nations Projections

By using the adjusted population (18 to 23 years), the Gross Enrolment Ratio at higher education level obtained through the AISHE 2019-20 comes out to be 27.10 percent: Total enrolment, 38.53 million & age-specific 18 to 23 years population, 142.20 million. In the light of the Expert Committee projections, the same can now be re-calculated for the year 2019-20 (Table 1). The age-specific population (18 to 23 years) based on the Expert Committee projections in 2019-20 comes out to be 150.79 million which gives a GER of 25.55 percent; a difference of 1.55 percentage points. It is hoped that AISHE while presenting GER 2020-21 will not only use the Expert Committees projections for 2020-21 but may also like to revise its previously computed GER during the period 2011-12 to 2019-20. An attempt has also been made in the present article to re-calculate GER in the light of the Expert Committee projections during the period 2011-12 to 2019-20 and the same separately for the male as well as for female population is presented in Table 2 along with the GER published by the AISHE which reveals a slight variation in both the estimates in the initial years but the same in the later years, especially in the years 2018-19 & 2019-20, as reported above, is found significant which is true for both the GER of the male and female population.

In addition to the Expert Committee, projections are also made available by the United Nations in 2019 (Department of Economic and Social Affairs, Population Division: World Population Prospects 2019, accessed on June 3, 2021, from https://population.un.org/wpp/DataQuery/e). As per these projections, India would have had a total population of 1366.42 million in 2019 to which, if a percentage of 11.33 is applied will give a total of 154.82 million population in the age group 18 to 23 years. Using the United Nations projections and a total enrolment of 38.54 million, gives a GER of 24.89 percent in 2019-20 which is quite similar to one estimated based on the Expert Committee projections. Thus both the estimates of GER computed based on the Expert Committee (25.55 percent) and United Nations projections (24.89 percent) suggest that GER 2019-20 is a bit lower than one provided by the AISHE (27.1 percent).

Size of Enrolment, if a GER of 50 Percent is achieved in 2035

The details of the Expert Committee projections are presented in Table 1 which reveals that India’s total population is expected to be 1513.6 million in 2035 as against 1553.7 million projected by the United Nations (2019); actual Census 2011 population being 1210.9 million. In this note, Official Projections (July 2020) made available by the Technical Group on Population Projections set up by the National Commission on Population (Government of India) has been used to estimate the quantum of the enrolment in 2035 in the absolute and percentage form. The total population of India is expected to grow at an annual rate of 0.9196 percent per annum or 311.43 million in absolute terms between the years 2011 to 2036. The share of the 18 to 23 years old population to total population in the 2011 Census was 11.38 which as per the Expert Committee projections is likely to be declined to 9.18 percent in 2035; the year by which India desires to attain a GER of 50 percent. The size of the 18 to 23 years population in 2035 is likely to be 138.99 million. To attain 50 percent GER, the size of higher education enrolment in 2035 would be required to be 67.12 million which is 74.17 percent higher than the actual AISHE enrolment in the year 2019-20. Thus to attain a GER of 50 percent in 2035, higher education enrolment will be required to grow at an average annual growth rate of 3.53 percent per annum. Will it be possible? To know it below we examine the growth of higher education enrolment in India, we analyzed both the absolute and average annual growth rate between different periods. We would also explore whether it be attained at the current status of school education in India.

Challenges Ahead to Meet 50 Percent GER

Given the growth rate achieved in enrolment at the higher education level in the past, with a little push achieving a growth of 3.53 percent per annum to attain a GER of 50 percent in 2035 looks achievable. A look at the Tables 2 & 3 reveals that enrolment at the higher education level increased at an annual compounded rate of 3.58 percent during the period 2011-12 to 2019-20 the same in case of female enrolment (4.77 percent) was significantly higher than their male (2.46 percent) counterpart during the same period. In the initial period (1950-51 to 1960-61) just after the independence, female enrolment increased at an annual rate of 14.05 percent compared to 8.51 percent in the case of male enrolment. However, thereafter the same could able to increase with every passing year but couldn’t maintain the pace. However, all during the years, the rate of increase was never below1.98 percent except the period 1980-81 to 1990-91. Further, it has been observed that the higher education enrolment experienced a high growth rate of 11.83 percent during the decade 2000-01 to 2011-12; again growth rate in case of female enrolment (13.26 percent) was significantly higher than their counterpart males (10.81 percent) which may be attributed to more number of higher education institutions including the independent institutions included in the data collection as well as the inclusion of any course, like hotel management, nursing, etc having a duration of three years after the higher secondary level when the AISHE was launched in the year 2011-12. Thereafter, higher education enrolment couldn’t look back and maintain its increasing trend during the remaining period of AISHE (up to the year 2019-20). As has already been mentioned above the same has increased at an average annual rate of 3.58 percent per annum during the period 2011-12 to 2019-20. During recent years, the growth rate of women’s enrolment has been higher than the men’s enrolment which looks to reach the saturation point. Further, it has been observed that the average annual growth rate during the period 2012-13 to 2019-20 each year further reveals that the same has consistently increased and was above 3.53 percent each year, 7.31 percent being the highest during the period 2012-13 to 2013-14 all which suggest that the same remained higher than the required growth rate of 3.53 percent per annum to achieve the targeted 50 percent GER/3.53 percent annual growth rate in 2035.

Separately, a glance at the undergraduate level (Table 3) reveals that the same has also been consistently increased from 23.9 million in 2012-13 to 29.8 million in the year 2018-19; but declined slightly to 29.6 million in 2019-20, the year for which the AISHE is the latest available. Further, it has been observed that the share of undergraduate enrolment to total higher education enrolment is about 80 percent which is also true separately for men and women enrolment however women enrolment at 80.26 percent is slightly higher than their male counterparts. During the same period, the GER at the higher education level has also shown a consistent improvement which in the latest AISHE year is 27.1 percent for total enrolment as against as GER of 26.9 percent in case of men and 27.3 percent for women enrolment. Further, a look at the percentage share of women’s enrolment to total enrolment at the higher education level also shown a consistent increase which was as low as 11.30 percent in 1950-51 but further increase to 39.30 percent in 2008-9 and 49.03 percent in 2019-20. As it seems that with a little push, the share of women’s enrolment may further move towards 50 percent of the total higher education enrolment.

The Way Forward

The growth in higher education enrolment which has been attained since the independence and more specifically in the recent past is termed impressive and has been achieved during the normal course of time when there was no epidemic like the COVID-19 and the ongoing pandemic which has changed the lives of many. The COVID-19 pandemic has affected educational systems across the World, leading to the closures of schools, universities & colleges, and other such institutions. According to UNESCO, around 1.4 billion learners across the world were not able to attend school or university. The impact was more severe for the disadvantaged and socially deprived sections of the society and their families, causing economic hardships on families. It is not that the lives of only the students have been affected but their parents are also badly affected, many of who have lost their jobs and those who could manage their jobs, the salaries have gone down, many of the parents remained without salaries and few of them are still without the salary. The Centre for Monitoring Indian Economy (CMIE) based on the 30-day moving average estimated that as of 5th June 2021, the unemployment rate which remained high at 12.57 percent has badly affected both the rural (11.5 percent) and urban (15.5 percent) areas of the country. The average unemployment rate for May 2021 stood at 11.90, 14.71, and 10.63 percent respectively in all, urban, and rural areas which were as high as 45.6 percent in the case of Delhi. CMIE further estimated that because of lockdown due to pandemic in different states there was a loss of as many as 7.46 million jobs in April 2021 which affected both the salaried and non-salaried jobs. As per CMIE, a total of 10 million people lost their jobs during the second pandemic and the income of about 97 percent of the households’ has declined since the beginning of the pandemic last year. A good number of workers in the fear of long lockdown migrated to their home town mostly to the rural areas which were as high as 800 thousand alone in Delhi; this affecting education of their wards. Many of them may remain in villages and a few of them may not return to work; thus significantly affecting the education of their wards. Those who manage to continue their jobs but with a reduced salary, many of them have migrated their wards from low-fee private schools to government schools. In addition, children of government schools and their parents who migrated to villages may see a steep decline in enrolment in government schools in 2020-21 data collection of which is currently undergoing across the country.

GER of 100 percent at School Education by 2030

Needless to say that higher education level cannot grow independent to school education because of which as mentioned above NEP 2020 envisages attaining a GER of 100 percent in case of school education in India by the year 2030. To view the current status of school education in India and whether the same is in a position to help India in attaining a GER of 100 percent in 2030, various enrolment and efficiency-related indicators including the retention and transition rates have been critically analyzed during the period 2017-18 & 2018-19. Higher education enrolment is not expected to increase unless the efficiency of the school education system is improved to a significant effect which at present is found to be a highly inefficient one and also the quality of enrolment statistics has deteriorated recently because of the erratic enrolment at the elementary level of education. Unlike AISHE, UDISE+ is not yet available for the year 2019-20 as the time-lag in school education statistics has recently increased significantly.

Enrolment-based Indicators

Gross & Net Enrolment Ratio as well as Age-specific Enrolment Ratio and Adjusted-NER at different levels of schools education and corresponding age-group, such as 6 to 10+, 11 to 13+, 6 to 13+, etc. have been analyzed (Table 4). In addition, efficiency indicators, such as, average annual drop-out rate, retention, and transition rates both at the state as well as at all-India level have also been analyzed all of which have implications for India achieving the goal of universal school education & high GER at the higher education level.

Table 4 presents a variety of enrolment-based indicators at different levels of education at the all-India level which reveals that despite significant improvement in all spheres of school education in India, the goal of universal school education is still a far distant dream which is not likely to be realized shortly. Enrolment decline during 2018-19 over the previous 2017-18 is in the tune of 2.63 million will further deteriorate efforts being made towards achieving the goal of school education in general and universal primary education in particular which is reflected in enrolment ratio at the primary level of education. During 2017-18 to 2018-19, enrolment in Grade I declined to 24.75 million from 25.09 million in 2017-18; thus showing a decline of 0.34 million in absolute terms or 1.3 percent in percentage form. It is also worth mentioning that a huge decline of about 59 million enrolment was noticed in 2017-18 when Student Data Management Information System (SDMIS) in-sync with U-DISE was launched in 2016-17.

Primary Level

Irrespective of a type of enrolment ratio, a steep decline has been observed across enrolment types amongst which GER at the primary level is the steepest one which has decline to 92.56 in 2018-19 from its previous 102.79 level in 2017-18 because of which enrolment ratio at upper primary, secondary and higher secondary levels may see a steep decline in years that follow (Table 4).

A Gross Enrolment Ratio of 92.56 percent in 2018-19 indicates that roughly about 7 percent of children including the overage and underage ones are yet to be enrolled against which 89.14 percent children of age 6+ to 10+ years are enrolled in Grades I to V; thus indicting that remaining 11 percent children are not enrolled in Grades I to V but all of them may not be treated as out of school as a few of them may be enrolled in higher grades for which the Adjusted-NER is computed. A 93.60 percent Adjusted-NER indicated that about 94 percent of the total 6+ to 10+-year-old children are enrolled but not necessarily in the corresponding Grades I to V. This otherwise also indicate that the remaining 6 percent of the total 6+ to 10+ years-old children are not enrolled either in corresponding Grades I to V and or higher grades. On the other hand, 94.26 percent Age-specific Enrolment Ratio indicates that more than 94 percent of the total 6+ to 10+-year-old are enrolled and the remaining 6 percent are yet to be enrolled which is huge if the size of the population is somewhat 118 million. It may also be observed that 2018-19 figures are that of before COVID-19 which was first noticed in January 2020 in India because of which schools may experience a large number of dropouts which is not confined only to government schools but has also affected small private unaided schools. The year 2020-21 & 2021-22 may see a further decline in enrolment; thus affecting severely efforts being made in India towards universal school education. It is also interesting to observe that except Lakshadweep, all other States & UTs have shown a significant decline in GER in 2018-19 over the previous year 2017-18; all of which indicate far-reaching implications for other levels of education to grow (Table 5).

Upper Primary Level

Net Enrolment Ratio at Upper Primary level indicate that the same has declined to 68.99 percent in 2018-19 from its previous level, 70.52 percent thus indicating that about 31 percent of the total 11+ to 13+ year children are not enrolled in the corresponding Grades VI to VIII which is considered as huge towards achieving the goal of universal elementary enrolment (Table 5). On the other hand, a 76.97 percent Adjusted-NER indicates that about 33 percent of the total 11+ to 13+ children are yet to be enrolled in corresponding Grades VI to VIII or higher grades. On the other hand, 88.55 percent Age-specific enrolment ratio at the upper primary level indicates that about 11 percent of children of age-group 11+ to 13+ are yet to be enrolled. State-specific NER at the upper primary level further indicates that the same has declined in 2018-19 in most of the states with Bihar (71.01 percent), Gujarat (72.80 percent), Jharkhand (71.18 percent), Madhya Pradesh (69.57 percent), Uttar Pradesh (58.26 percent) and West Bengal (71.65 percent) having low to very low NER all which indicate task ahead is challenging one and need meticulous planning at all levels of school education to attain 100 percent GER in 2030.

Elementary Level

In addition to primary & upper primary levels of education, enrolment ratios have also been analyzed at the elementary level of education. A NER of 81.46 percent at the elementary level indicates that a significant 19 percent of children of 6+ to 13+ years are not enrolled in the corresponding Grades I to VIII. The remaining children of this age group may either be out of school or a few of them may either be enrolled in higher grades (Table 6). Adjusted-NER further suggests that a little over 87 percent are enrolled either in Grades I to VIII or also in the higher grades. On the other hand, a 92.08 percent Age-specific enrolment ratio suggests that only 8 percent of children of 6+ to 13+ years are yet to be enrolled (15 million) which in absolute terms is huge as the size of the total population of this age group is 188 million. If India wants to achieve the goal of universal school enrolment in 2030, it has to give attention to large states, such as Andhra Pradesh, Bihar, Jharkhand, Gujarat, Madhya Pradesh, Odisha, Rajasthan, Uttar Pradesh, West Bengal, and other such states having low enrolment ratio at the elementary level of education.

Secondary & Higher Secondary Level

Quite disappointed to observe the status of secondary and higher secondary levels of education as the net enrolment ratio is reported to be as low as 48.60 and 30.78 percent respectively which indicate that more than 50 and 70 percent of children of the corresponding age groups in 2018-19 were yet to be enrolled (Tables 7 & 8). Can secondary and higher secondary levels grow independently to lower levels? Certainly not. Enrolment in secondary level i.e. Grades IX & X is not a function of the corresponding age-specific population i.e. 14-15 years but is a function of elementary graduates i.e. those who successfully pass Grade VIII. Thus unless the efficiency of the elementary level of education is not improved to a significant effect, neither the goal of universal secondary nor higher secondary education is expected to be achieved. Therefore, in the next section, a few of the efficiency-related indicators are critically analyzed which also plays an important role in ensuring 100 percent GER at school education in 2030.

Dropout Rate

On the one hand, there is a steep decline in enrolment and on the other hand, those who stay do not complete an educational level and leave the system before the completion. Table 8 presents the dropout rate at primary, upper primary and secondary levels of education for both Cohorts 2016-17 and 2017-18 in the case of General, Scheduled Castes, and Scheduled Tribes population. The drop-out rate at the primary level, irrespective of the social category has shown an increase for the 2017-18 cohort from its previous level i.e. Cohort 2016-17 which is obvious because of the steep decline in enrolment during 2017-18 and 2018-19. Of the total enrolment (123.81 million) in Grades I to V in 2016-17, 3.51 percent dropped out from the system before the completion of a grade as against 4.45 percent during the year 2017-18. It may be recalled that the size of enrolment in primary grades in 2017-18 was in the tune of 122.38 million in 2017-18. A 4.45 percent drop out at all-India level is termed as average annual drop out rate which over the primary cycle of five years come to around 17.8 percent which means that of the total enrolment in Grades I to V, roughly about 18 percent dropped out from the system before the completion of the primary level. Both the SC (5.16 percent) & ST (5,48 percent) categories also reported a high drop-out rate compared to 4.37 percent in the case of the OBC category. Barring the General category, contrary to general belief dropout rate in the case of boys is a bit higher than their counterpart girl which is true for the SC, ST, and OBC children.

A glance at the state-specific drop-out rate at the primary level of education (Table 9) further reveals that about 11 states have drop-out rates higher than the national average of 4.45 as against 10 states having lower rates at the upper primary level (national average 4.68 percent). At the secondary level, irrespective of boys and girls, the dropout rate is very high barring a few states such as Chandigarh, Himachal Pradesh, Lakshadweep, and Kerala. A few states from the north-eastern region, such as Arunachal Pradesh (13.78 percent), Meghalaya (16.88 percent), and Nagaland (11.41 percent) are having the dropout rate above 10 percent in case of primary level. On the other hand, Bihar (7.76 percent) and Uttar Pradesh (9.71 percent), the most populous states of the country having high dropout rate is unless checked, the goal of universal primary education may not be cherished shortly. At the upper primary level, Bihar (12.43 percent), Chhattisgarh (7.02 percent), Gujarat (7.39 percent), Jharkhand (10.21 percent), Madhya Pradesh (5.93 percent) and Uttar Pradesh (5.74 percent) have high dropout rate all of which suggests that the top most priority must be given to theses states to check high incident of drop out. Further, it has been observed that compared to drop out at the primary and upper primary level, the same at the secondary level is alarmingly high at 17.87 percent in addition to which states like Bihar also having a high drop out (28.46 percent) rate at this level of education. On the one hand, there is a high incidence of dropout at the primary level and those who complete the primary level do not stay and drop out before they complete the upper primary level of education. Besides, all those who complete the upper primary level of education, do not necessarily have been transited to the next level of education because of which the next indicator we discuss below is the transition rate (Table 10).

Transition Rate

The Transition Rate for the year 2017-18 presented in the Table 10 reveals that about 91 percent of children transit from the primary to upper primary level of education and no significant deviation is observed between boys and girls transition rate. However, more children from the general category (94 percent) transit from primary to upper primary level compared to 87, 88, and 89 percent of children respectively transit from the SC, ST, and OBC category. The transition rate remains almost stagnant for the past so many years. On the one hand, a good number of children left the system before the completion of primary level, and on the other hand, about ten percent of children drop out from the system in transition; thus severely affecting the efforts being made towards universal school education by 2030. There is no option but to improve the efficiency of the primary education system which must send an adequate number of primary graduates to the upper primary system. Thereafter children must continue in Grades VI to VIII and complete Grade VIII and transit to the first grade of the next higher level, i.e. Grade IX of secondary level. The gains that we achieved towards universal enrolment are slowly but surely being losing fast and we are back to square one. If not improved, India may not achieve a target GER of 100 percent by 2030 and a GER of 50 percent in 2035 at the higher education level as envisaged by NEP 2020.

The state-specific transition rate presented in Table 11 indicates that only three states, namely Bihar, Jharkhand, and Uttar Pradesh have a lower transition rate than at the national average of 91 percent from primary to upper primary level against 9 and 12 states from the elementary to secondary and from secondary to higher secondary level of education. Further, it is observed that the lowest 77 percent transition rate has been observed in the state of Bihar and the highest, 100 in a couple of states. Further, no significant difference is observed in boys and girls transition from the primary to upper primary levels of education and from elementary to secondary level of education; however, in a few states, more girls used to transit than their boy’s counterpart in case of secondary to higher secondary level of education. The transition rate in the most populous states of Bihar, Jharkhand, Madhya Pradesh, Rajasthan, and Uttar Pradesh is unless improved, India may not move towards achieving the goal of school education in the real sense. It is sorry to observe that in most of the efficiency and enrolment-based indicators no visible improvement has been noticed which is despite the nationwide programmes currently under implementation.

Retention Rate

The last indicator which we discuss below also falls under the category of efficiency indicators is retention rate at the primary and elementary level which gives us information about the retaining capacity of the system (Table 12). Grade V enrolment is linked to enrolment in Grade I five years back as against Grade VIII enrolment is linked to Grade I enrolment 8 years back and so at the secondary and higher secondary levels of education. A look at Table 12 reveals that that prima-facie it looks that both boys and girls almost equally retain which is true for all levels of education. A retention rate of 86.30 percent at the primary level of education indicate that only 86 of the total 100 children who entered the system five years back could able to reach Grade V; the balance of 14 children couldn’t reach Grade V in 2018-19 and dropped out from the system however a few of them still be in the system because of the repetition. It may be recalled that the average annual drop out rate in 2018-19 at the primary level presented above is 4.45 percent which also indicate that about 17.80 percent of the total enrolment in Grades I to V couldn’t remain in the system which is huge if the size of total primary enrolment is in the tune of 122.38 million. The retention rate of girls at the primary level of education (86.90 percent) is a bit higher than their counterpart boys (85.70 percent); which is also true for many states. On the other hand, 67 percent children of those who enrolled in Grade I eight years back could only reach Grade VIII in 2018-19 which otherwise indicate that 33 percent of the total enrolled couldn’t remain in the system; however, a few of them may still be in the system because of the repetition. On the other hand, only 56.90 and 38.00 percent could remain in the secondary and higher secondary levels of education indicating about 43 and 52 percent of the total enrolment couldn’t remain and dropped out from the system. Not only the universal secondary and higher secondary levels of education but even universal primary and elementary education is not in the sight which is quite similar to the situation a decade back.

Despite the high incidence of drop out a few could manage to complete primary, elementary and other levels of education. The GER, NER, Age-specific ER, Adjusted-NER, Transition Rate, and Retention rates analyzed suggest that even in quantitative terms India is still far away from attaining the status of universal primary education in a real sense less we achieve the universal elementary and secondary level of education. The low level of participation at the primary level and high incidence of dropout suggest that the system is inefficient and not supplying an adequate number of primary graduates to the upper primary level of education in the absence of which upper primary level of education is not adequately growing. Needless to mention that upper primary and other higher levels of education cannot grow on their own as upper primary is not a function of the corresponding age-specific population i.e. 11+ to 13+ years but it is the function of primary graduates. Therefore, there is no option but to improve the efficiency of the primary level of education and further improve the transition from primary to the upper primary level of education. None of the levels of education can grow independent to the immediate lower level which is also true for higher education level which as envisaged in NPE 2020 cannot attain a 50 percent GER unless the higher secondary level supplies an adequate number of graduates on regular basis.

Concluding Observations: Pandemic Likely Impact on Higher Education

Because of the facts presented above both the higher education as well as the school education sector will not remain the same like it was before the outbreak of the COVID-19. For about last more than 15 months no face-to-face learning is taking place which is true for all the levels of education in India. Even the Central Board of Secondary Education (CBSE) & Indian Certificate of Secondary Education (ICSE) has canceled the Board Examinations so as the host of the State Secondary Boards and National Institution of Open Schooling (NIOS); thus affecting everyone, rich or poor. Further, as per the Right to Education Forum, about ten million girls in India could drop out of secondary schools due to the pandemic; thus severely affecting enrolment at the higher education level in the years that follows. In addition, the recent steep decline in school education enrolment would also severely influence higher education enrolment to grow.

The post-pandemic impact on higher education is likely to be affected by both the face-to-face as well as distance learning modes. Both the students at home, as well as those who desire to join international universities and international students who desire to join the Indian higher education system, are expected to be severely affected by the COVID-19. Jain & Ruby (2020) discusses different dimensions which would have far-reaching implications for the enrolment at the higher education level to grow. The face-to-face programmes are affected by the high incidence of dropouts across the school levels of education. Part of the growth in higher education enrolment is because of private institutions that have almost trapped all the potential students who can pay the fee under its ambit but are not likely to maintain the momentum as they have almost reached the saturation point. Growth in higher education enrolment in the recent past is also attributed to increased distance learning through the online platform but the same, especially in the rural areas is marred by the high cost of contents as well cost and speed & stability of the internet connectivity. All these limitations are further compounded by the COVID-19 which would affect demand for higher education and parents’ choices for the same to which falling economy has added fuel in the fire; thus may likely to dent India’s efforts towards attaining a GER of 50 percent in 2035. The impact of COVID-19 on prospects of higher education enrolment is like to be more severe than the famous 2009 recession which the World had experienced. It may impact India more than the other countries as its economy in terms of GDP during 2020-21 is contracted by a historical 7.3 percent which may result in less funding for the educational programmes in general and higher education in particular which has already started reflecting into. Economy revival is not expected before the financial year 2022-23. Because of the fear of the spread of pandemic, schools, colleges, offices, institutions and universities are closed for almost 15 months and students both in schools and colleges, parents, teachers & faculty, administrators all stayed at home many of who as described above have lost jobs or their salaries have been cut significantly all which force parents to rethink about the education of their wards once the lockdown is over especially the higher education sector. Their capacity to fund higher education will now be re-evaluated once the pandemic is over. They may even decide to withdraw or stop funding higher education of their wards or may defer admission for a year or two all of which in addition to the availability of lower funds from the government sources; higher education GER may not escape the impact of all these factors. As has been presented above that because of the pandemic, the unemployment rate remained very high at 12.57 and loss of 7.46 million jobs all of which would affect demand for higher education in years to come. Parents may have no option but to withdraw their ward or postpone their admissions if the fee is not reduced or waived or financial assistance is provided to all those who lost their jobs or drawing low salaries and the impact of the pandemic is more on this segment of the population. As of now, no financial assistance has been promised by the UGC or the Central Government to the families affected the most all which would influence higher education enrolment to grow in years that follow.

Because of the pandemic, to reduce chances of infection and cost-cutting, students avoid traveling far places and look for opportunities nearby which resulted in a lack of adequate places in the local higher education institutions while at other locations the same may be found in surplus. As has been specified above those who were planning to go abroad for higher studies may now opt to skip because of the fear of infection and travel cost and look for opportunities locally near home or they may defer their decision for a year or two. Because of the comparatively low cost of higher education, India may attract a few additional international students both of which may help in increasing enrolment but may not affect GER to a great extent. If this is found true, India may expect to have students from diverse backgrounds in the year that follows. Alternatively, to avoids face to face learning, students may also look for opportunities in open and distance learning mode which may also result in low cost of education for which India may need to provide stable internet connectivity, especially in the rural areas which is need of the hour in addition to which we need to relook into the cost of distance and open learning programmes in India. NEP 2020 while envisaging a 50 percent GER by 2035 also based on the assumption that distance and open learning degree courses will play a pivotal role in achieving it. If we could provide affordable distance learning programmes, the same may also attract students towards higher education those who because of one or the other reasons couldn’t yet join the system. Available data further indicate that share of distance and open learning enrolment to total higher education enrolment is almost stagnant for the last so many years. We must now act to popularize distance learning programmes and ensure that they are treated at par with face-to-face programmes. Because of the COVID-19 and hardships, parents may like to move towards distance education programmes for which the government should also provide additional incentives to ensure that we do not miss the opportunity. To ensure this to happen we must create a conducive environment by creating necessary infrastructure with emphasis on internet connectivity and bandwidth in both the rural and urban areas which must be made affordable. Despite which people in rural areas will still be facing a shortage of computers and devices to access the online programme. As per the NSSO data, only 10.7 and 23.8 percent of households have had access to computers and internet connectivity respectively in 2017-18. Additionally, well-established institutions especially in the rural areas and also in the universities must strengthen their online platforms to ensure that learners get access to these facilities to use the same for the distance and open learning programmes/degrees on their premises or there be an option of guided online degree programmes. All these efforts, still may not able to significantly contribute to the desire for GER of 50 percent in 2035. The initiatives as indicated above may still be found insufficient because of which tie-up with the big business houses to establish learning centers may also be explored which may be funded through the CSR funds. Like AISHE, a separate MIS may be initiated to develop a sound database exclusively for open and distance learning programmes which must also include all state and private open universities. To see all these to happen, let us wait for 2020-21 & 2021-22 enrolment statistics which is most like to experience a declining trend which is not good to attain a high GER of 50 percent in 2035.

References

All India Survey on Higher Education 2019-20 & Other Years, Department of Higher Education, Ministry of Education, Government of India, New Delhi, released in June 2020.

Can There be Alternative Indicators of Enrolment: A Critical Review of Frequently Used Indicators, Journal of Educational Planning & Administration, July 2002, NIEPA, New Delhi.

Can India Achieve its Enrolment Target Post-pandemic?, Eklovya Jain and Alan Ruby, University World News: The Global Window on Higher Education, 25 July 2020.

Investment Priorities & Cost Analysis: A Study of Upper Primary Education in India (with Dr. N. V. Varghese), Vikas Publishing & NIEPA, New Delhi, 2001.

National Education Policy 2020, Ministry of Human Resource Development, Government of India, New Delhi, July 2020.

NEP 2020: Implementation Strategies, National Institute of Educational Planning and Administration, New Delhi, December 2020.

NSSO 75th Round on Key Indicators of Household, Social Consumption on Education in India, Ministry of Statistics and Programme Implementation, National Statistics office, Government of India, July 2017 to June 2018.

United Nations (2019), Department of Economic and Social Affairs, Population Division: World Population Prospects 2019, accessed on June 3, 2021, from https://population.un.org/wpp/DataQuery/e.

Rashtriya Uchchatar Shiksha Abhiyan: National Higher Education Mission (PDF). Ministry of Human Resource Development. National Informatics Centre. Retrieved 2 February 2014

Technical Group on Population Projections National Commission on Population, Ministry of Health & Family Welfare, Government of India, July 2014. Family Welfare, Government of India, July 2014.

How Much We Gained: A Case of U-DISE+

 

Arun C Mehta
Formerly Professor & Head
Department of Educational Management Information System
National University of Educational Planning & Administration (NIEPA), New Delhi
(E-Mail: acmehta100@gmail.com & WhatsApp: +91 98681-84981)

Background
It is mandatory for each district of the Country to formulate Annual Work Plan and Budget under the aegis of the recently launched integrated School Education programme, namely the Samagra Shiksha which was also true for the previously launched nation-wide Sarva Shiksha Abhiyan (Elementary Education for All) programme. The concept of developing district plans was initiated during the World Bank assisted project, namely District Primary Education Programme (1994-95 to 2000-01) under which 272 districts across 18 states were covered. District Annual Plans are supposed to be appraised first internally at the state level which is in turn appraised by a team of Consultants at the Technical Support Group of Samagra Shiksha at the national level after which the same is submitted to the Project Approval Board for appraisal, approval, and release of the funds (in installments) to the State Implementation Society. District School Education Plans are supposed to be developed by the District Planning Team by following the plan formulation guidelines but in most of the districts plans are now being developed at the State level which generally lack academic flavor as the same in most of the cases is based on the EXCEL Tables designed by the Technical Support Group of Samagra Shiksha.

Annual Work Plans are exclusively based on the data generated through the Unified District Information System for Education (U-DISE) which was till recently managed (1994-95 to 2017-18) by the apex National Institute/University of Educational Planning and Administration (NIEPA). District Information System for Education (DISE) was also initialed under the DPEP initially for the primary education which was subsequently extended to first, upper primary (elementary education), and then to the secondary and higher secondary levels of education and is termed as the most successful and longest initiative (a collaboration of NIEPA, UNICEF, and Ministry of HRD) towards strengthening EMIS/Educational Statistics in India. From the year 2018-19, renamed U-DISE+ is being managed by the Department of School Education and Literacy of the Ministry of Education/HRD technical aspects of which is being managed by the National Informatics Centre (NIC) located in the Ministry.

Till recently, it was a practice to formulate Annual Work Plans based on the current year’s data but the same is de-railed since the U-DISE has become U-DISE+ or the data collection and management work under U-DISE is transferred to the Ministry of Education which is now being managed by National Informatics Centre and Deputy Director-General located in the Ministry of Education. It is also of importance to mention that as of February 2021, data collection work concerning U-DISE 2020-21which should have been initiated as of 30^th September 2020 has not yet been started. Even data for the year 2019-20 is not available (in most of the states) and none of the set of 14-publications based on U-DISE 2017-18 and more recent years is made available in the public domain which was a routine practice till recently when the same was being managed by the Department of EMIS at NIEPA. Even U-DISE 2017-18 data in the form of Flash Statistics is yet to see the light of the day (now released in April 2021 without ritual Foreword & From the V-C’s Desk) but unfortunately, several articles have been published exclusively based on U-DISE 2017-18 data by other agencies other than NIEPA and Ministry of Education (formerly Ministry of HRD) and are available in the public domain (Recent Trends in India: Contractual Teachers by Vimla Ramachandran & Ganesh Nigam & School Education in India: Data Trends & Policies, Central Square Foundation)

Given the limitations in the educational statistics which was being managed by the Planning, Monitoring, and Statistics Unit of the Department of Higher Education located in the Ministry of Education, U-DISE was initiated in 1994-95 by NIEPA, New Delhi in collaboration with the UNICEF and Ministry of Education at the time the country launched one of the wide-spread programme concerning primary education with the support of the World Bank, namely the District Primary Education Programme (DPEP). The collaboration between these agencies is perhaps the longest one in the history of educational statistics in India which survived for almost three decades. Initially, DISE was to cater to the need of the primary level of education which was extended to the entire elementary level of education when the country launched another ambitious programme towards achieving the goal of universal elementary education through Sarva Shiksha Abhiyan programme which was launched in 2001. 

Further with the RTE and RMSA, DISE Data Capture Format was modified to meet its requirement but there were two systems, one DISE, and the other SEMIS because of which there were lots of duplicity and wastage of resources. From the year 2012-13, by using one unified format, data from the entire school education, from primary to secondary and higher secondary levels of education is being collected and since then DISE is popularly known as U-DISE or Unified DISE and has acquired the status of the Official Statistics and all the parallel collection of information system in case of school education in India abandoned. Over the time the quality, sharing, dissemination, utilization, consistency of data improved but questions used to be raised about the quality and consistency of enrolment data because of which in the year 2016-17 an effort was made to collect individual student data on 35 parameters in-sync with U-DISE to generate all U-DISE enrolment tables based on student information and its very first year, detailed students records of around 210 million were collected but the whole exercise was discontinued in a year thereafter for unknown reasons. Because of the recommendations of the NEP 2020, it is heard that fresh efforts are being made to re-initiate the student data collection.

Below some of the achievements gained through U-DISE at NIEPA is listed:

Landmark Achievements: U-DISE up to the Year 2017

• Through the concerted efforts, MIS units have been made operational both at the district and state levels across the country and are equipped with necessary hardware and software.
• The U-DISE has eliminated data gaps as comprehensive information on all aspects of school education is now available over a period of time at all disaggregated levels, such as school, cluster, block, district, state, and national levels.
• Both the district elementary as well as secondary education plans are exclusively based on U-DISE data and annual plans were used to be developed based on the current year data which were submitted to the PAB for appraisal and approval.
• Liberalization of data to ensure that data reaches all data users in a user-friendly mode. A separate online channel was devoted to easy hassle-free downloading of the data and online generation of reports as per the requirement of users on hundreds of parameters.
• What is more remarkable about U-DISE is that it has drastically reduced the time-lag in the availability of educational statistics, which is now down from 7-8 years to about a year at the national level, and only a few months at the district and state levels.
• A set of 15 publications were used to be brought out annually covering both elementary as well as secondary levels of education.
• School Report Cards of an individual school for the period 2005-06 to 2016-17 were made available which also includes a rating of each school based on the 10 RTE parameters.
• Every bit of information collected through the U-DISE was made available to block, district, and state-level MIS units to ensure that data is adequately used where the strong U-DISE software having powerful reporter modules was installed, the officers used to generate all requisite indicators at their own at their desired levels. The data to state-level was provided by the block and district level MIS Officials which has had helped to create ownership and accountability of data.
• U-DISE was being managed by a small team at the national level with support from the UNICEF and Ministry with an annual budget of Rs. 10 million approximately. All the U-DISE websites were hosted in-house in NIEPA for which a special data center was developed which was equipped with necessary servers and other necessary equipment.
• For many years, data was cross-checked by a third party not involved in the data collection and SSA on sample basis sharing of which was used to be shared with all the stake-holders.
• The web-portal may be very attractive but of not much use unless the quality of data has been provided by the respondents which are qualitative in nature. Keeping this in the mind, numerous interactive programmes to discuss Data Capture Format with the respondents, namely school headmasters, CRC and BRC Coordinators, District, and State MIS Officers and other stakeholders were conducted over a period through EDUSAT which was used to be received by thousand and thousand respondents from across the country.
• It was an annual major activity to release the data in a special data release programme which was used to be attained by data users which have helped immensely in creating awareness about the data.

As has already been mentioned that U-DISE from the year 2018-19 is being managed by the Ministry of Education through the NIC, it is hoped that the quality, reliability, consistency, utilisation, sharing, and dissemination of data from the year 2018-19 from its 2017-18 level will further improve in the year that follows.  Before U-DISE was shifted to the Ministry of Education, there was a proposal for the national roll-out of Teacher Module as a part of the Extended U-DISE in the form of Shaala Kosh in May 2018 which was initiated by the Ministry towards “its efforts to revamp the existing U-DISE system to make it relevant to today’s educational requirements, this was an attempt to develop a comprehensive integration of State MIS Systems”. Before Shaala Kosh, the Ministry also had launched Shala Asmita Yojana (to replace U-DISE) the task of which was envisaged to be completed by February 2017 but nobody knows its status? In a letter to all the States & UTs on 29^th May 2018, through Annexure I concerning Shaala Kosh, the following observations regarding U-DISE are worth to mention some of which are also documented in the U-DISE+ Booklet produced by the Ministry (https://udiseplus.gov.in/#/Publication) at the time of taking over U-DISE from NIEPA is briefly presented below:

Quality of Data: “The current system does not incorporate a comprehensive list of validation checks which results in low data quality”.

Ease of Use: “The current system is offline and employee a pen-paper format to collect data. This results in yearly data collection exercise which is time-consuming and has monetary implications”.

Data Usage and Dissemination: “There is huge time-lag between data collection and data usage. The data is currently collected as of 30^th September and is used next year. This time lag results in usage and stale data and thus inaccurate decision making. The current system does not provide information to all the relevant stakeholders”.

Lack of Coordination and Supervision: “NIEPA lacked the requisite infrastructure, expertise, and authority for coordinating with officials of the States and UTs to ensure smooth and timely availability of the information. Further, the UDISE was being handled in the project mode by a small team, and data was hosted in a private server rendering it vulnerable”.

Lack of Accountability due to Absence of Audit Trail: “The data was uploaded in the system by district/block MIS officials who were contractual in nature. In many states, the data entry work was totally outsourced. Hence, there was no clear traceability/audit trail of those who were responsible for the authenticity of the information provided.” “Transfer of official at the cluster, block and district levels further compounded the problem as a result of which the data was never verified. Since there was no accountability, the officials concerned did not take adequate care to upload consistent and correct data, thereby compromising the reliability of the UDISE”

Multiple Versions of Data Collection Software: “Because of the limitations of UDISE, many states and UTs developed their own MIS systems to collect data required in UDISE DCF. Therefore at the national level, the Department had to contend with two sets of data. Thus, over time, the authenticity and utility of the UDISE gradually decreased and aggregation of data at the national level became difficult”

Single DCF for all Categories of Schools: “In UDISE there was one Master DCF for all schools irrespective of the category. However, many of the fields were not applicable to a particular category of school. “This created confusion as a result of which there were instances where the data for the relevant school category was wrongly inserted. Consequently, the information provided by the schools suffered from inconsistencies”.

Lack of Verification and Analysis of Data: “It was mandatory from 2006-07 for all states and UTs to carry out sample checking of U-DISE Data. However, largely due to the lack of proper guidelines, the verification of the UDISE data was hardly being carried out. Bulky paper reports were never analyzed and feedback was not made available to States and UTs.”

It is unfortunate to observe that even after almost three years of UDISE+, no visible improvement is observed concerning most of the above observations from its 2017-18 level. On top of the above, the time-lag which was brought to less than a year at the national level and only a few months at the block, district, and state levels have again started to increase. It was said that “the time-lag (under U-DISE) results in usage and stale data and thus inaccurate decision making” is now more true for U-DISE+ data. Not only the 2017-18 complete U-DISE data (15 publications) is yet to see the light of the day but initiatives made by the Ministry from 2018-19 data collection under U-DISE+ has further increased the time-lag in data. As of date, data collection for the year 2020-21 has not even been fully initiated (now initiated in April 2021), and work concerning 2019-20 data is still going on in many states. For two years, Annual Work Plans through EXCEL Tables under Samagra Shiksha were continued to be based on 2017-18 data which had no such tradition in the recent past.

One of the important visible changes which have been observed is the development of a dedicated portal for the U-DISE+ but that itself doesn’t guarantee improvement with regard to the concerns raised for taking over the U-DISE. It was expected that because of the online portal, data-entry will take place from the school but barring a few Secondary and Higher Secondary schools the same couldn’t be achieved simply because only 32.66 percent of the total 1.5 million schools covered under U-DISE+ have had a computer in the school as against 18.73 percent schools having the internet connectivity. Even only 63.43 and 32.70 percent of the total 39,077 Senior Secondary schools have had computer and internet connectivity in school in 2018-19 (see Table 2). The percentage of schools runs by the Department of Education having computer and internet facility is as low as 24.06 and 8.05 percent respectively. About 8,35,488 schools (53.87 percent) out of a total 15,51,000 schools covered under U-DISE+ during 2018-19 are government-managed schools of which 75.94 percent schools didn’t have a computer in school; for all practical purposes they are either dependent on cyber café or the Office of the BRC Coordinator where both the internet and computer facility is expected to be available but even these centers in many locations face the problem of uninterrupted (if available) power supply and bandwidth as most of them at these centers still has got access to only 2G connection. In addition, only 73.86 percent of the total 1.5 million schools had electricity connections in 2018-19. Apart from the schools run by the Department of Education, the majority of schools run by the other government departments including the Local Body Department (1,34,882 schools & 37.60 percent having computers) and Tribal Welfare Department  (31,435 schools & 8.37 percent having computers) also didn’t have access to computers and internet connection. As it seems without strengthening computer and internet facilities in schools across the country, off-line U-DISE was switched to on-line as a percentage of schools with these facilities over the same in 2017-18 do not show any significant improvement.  One can easily understand the plight of states where the majority of schools do not have access to the computer in the schools. Three states, namely Bihar, Madhya Pradesh, and Uttar Pradesh has a total of 5,16,523 schools imparting school education which is 33.30 percent of the total 1.5 million schools covered in U-DISE+ in 2018-19 which also means that one in every three schools in the country is located in these three states but these schools do not have got computer (89.50 percent) and internet (89.72 percent) connection in 9 out of every 10 schools. The percentage of schools with the computer is as low as 6.58 percent in Madhya Pradesh compared to 11.08 percent such schools in Bihar and 12.53 percent schools in one of the most populous states having the highest number of schools in the Country, i.e. Uttar Pradesh.  It would be of interesting to know how these schools would have managed data-entry during 2018-19. It is a moot question to know whether they made data-entry in on-line or off-line mode and also the location where data-entry was made and whether they took school records or filled-in paper DCF to a data-entry point i.e. mostly the BRC; thus forfeiting the basic purpose of developing a paperless U-DISE+. Unlike paper authentication (on DCF) by the school and other higher levels in the case of U-DISE, U-DISE+ prescribed on-line verification at each level. It is not known how on-line verification would improve the quality and consistency of data and on what basis block and other higher levels have approved the information submitted by the lower levels in the absence of information on paper? It has also been observed that despite being an online system, schools in most of the locations continue to maintain a hard copy of information fed into the online U-DISE+ system mostly soft copy of which is provided by the state level MIS by downloading the same from a link provided by the U-DISE+ national team.

In most of the other schools, data entry could take have done by the MIS Official either at the Block or District level which have had necessitated visit of the respondents i.e. School Head-Master/Teacher to the BRC Office which might have got access to a computer with electricity and internet connectivity; thus forfeiting the basic reason of developing an online paperless system.

The current system (i.e. U-DISE) does not provide information to all the relevant stakeholders was another observation but far from the reality. The beauty of the previous form of the U-DISE before taking over by the Ministry was that every bit of information was available to block, district and state MIS In-charge/Data-Entry operator on his/her own system which was equipped with the powerful reporter and consistency check module which in the new arrangement is completely missing as only limited data now reaches back to the lower levels which are provided by the national level authorities to state MIS which in turn reach lower levels. It was routine to generate reports by the district and block level MIS Officials by themselves by using the U-DISE Software installed on their terminal that is now made dependent on the higher authorities and feel handicapped which surely would affect the effective and adequate use of data.  At the time of taking over, it was said that “the current system does not incorporate a comprehensive list of validation checks which results in low data quality” even though U-DISE off-line software have had very strong consistency check modules on hundreds of parameters and was available to all the MIS staff irrespective of a level in the absence of which it is not known how the quality of data under U-DISE+ in general and enrolment data, in particular, would improve.

Dissemination and free availability of data were some of the strengths of U-DISE. A set of 15 publications were used to be brought out annually which is now completely discontinued. It is strange that nobody raises concerns about the missing publications, not even by the Project Approval Board of Samagra Shiksha. In addition to publications, users were provided raw data and an online portal to generate tables on hundreds of variables (2005-06 to 2016-17) which is also discontinued for unknown reasons. However, a comprehensive data sharing policy is now put in place which has a lot of restrictions on downloading and use of data. Department of School Education & Literacy will use pseudo code and school name rather than sharing the actual U-DISE Code for unknown reasons. The Department also reserves the right to deny access to any user with or without any reason? The earlier simple system of data sharing has now been made a bit complicated which may discourage users than encourage using data. As it seems, it is the end of liberalization of the use of school education data initiated in 2005-06 when school report cards were launched. Under the previous U-DISE, it was a usual practice to share dump of the entire data except for sensitive data (contact number, email, etc.) to institutional and other data users but under the new U-DISE+ system full set of data is not being shared and whatever, data is shared one has to bring it into usable form; thus if 15 users have been provided data, all 15 users will do the same to make the data usable.

Some of the other concerns raised are deliberated below:

Lack of Coordination and Supervision: “NIEPA lacked the requisite infrastructure, expertise, and authority for coordinating with officials of the States and UTs to ensure smooth and timely availability of the information. Further, the UDISE was being handled in the project mode by a small team, and data was hosted in a private server rendering it vulnerable” which is factually incorrect. NIEPA has got the adequate infrastructure for the smooth functioning of U-DISE. Yes, the U-DISE at NIEPA was being handled in the project mode by a small team which was the beauty of the system that was evolved over more than two decades. Achievements by a small team had always been applauded at different forums including by the Joint Review Missions of SSA and RMSA. It is glad that a small U-DISE Team could manage the affairs of the U-DISE over a period of time efficiently which the present large team loaded with multiple resources couldn’t deliver as envisaged at the time of launch of U-DISE+. U-DISE/SDMIS data was never hosted on a private server. A data center was developed at NIEPA where all the servers are located. Www.dise.in, www.udise.in, https:student.udise.in and www.schoolreportcards.in all are hosted in-house on servers installed in NIEPA. NIEPA doesn’t have the expertise is a joke of the day as it has got the best-experienced faculty those who have soiled their hands in playing with the numbers. Is the present leadership more experienced? It would not be an easy task for any agency to bring out a set of 15 publications annually. Time will show whether the new arrangement accepts this challenge or term the existing publications simply not required (nothing has been published as of now). Will it able to maintain and update www.schoolreportcards.in or the same may also not even found useful. Unfortunately, an institution lacking in expertise was allowed to be engaged for over more than two decades. Yes, NIEPA doesn’t have authority to directly deal with the States and UTs but it had never experienced any problem in communicating, coordinating, and dealing with the states which are evident with the fact that even in the absence of the letter released by the ministry before the launch of U-DISE 2016-17, it had successfully collected student data of about 210 million which by no standards is a mean achievement. States treat NIEPA and its Faculty more seriously than any other institution concerning MIS.

Lack of Verification and Analysis of Data: “it was mandatory from 2006-07 for all states and UTs to carry out sample checking of U-DISE Data… However, largely due to the lack of proper guidelines … the verification of the UDISE data was hardly being carried out. Bulky paper reports were never analyzed and feedback was not made available to States and UTs.” The statement is partially correct as this was perhaps one of the weak areas of U-DISE. Guidelines to conduct random sample checking of data were provided and are still available at www.dise.in because of which at one point of time as many as 27 states conducted such studies and submitted to the national level summary of which was made available to states and shared which is available in the public domain for five years. However, momentum couldn’t be maintained in the subsequent years because of inadequate funds for the same which despite the JRM recommendations, and repeated requests from the states were never been provided in the absence of which slowly the number of states conducting such studies declined. Major findings of studies conducted used to be shared with the states annually (in July) during the annual conference of MIS Coordinators of both SSA and RMSA. It was expected that sample checking of UDISE+ data across the country by an independent agency will soon be initiated but the task of checking of data is assigned to officers who are part of the system? Is this third-party verification? But, first let us wait for the full 2019-20 data, which is already late by more than a year as most of the states have missed the deadline. Preparation for U-DISE 2020-21 is supposed to be started in September 2020; do states and districts are left with enough time to utilize and analyze UDISE+ 2019-20 data? Even if the UDISE data of a year is populated next year, the same is not expected to be updated from the schools because of which it will be impossible for U-DISE+ to become real-time data in the real sense. In the process which is now been adopted, there is no date of reference (i.e. 30^th September), it is said that since it is real-time data, no date of reference is required? This is a departure from being followed over the last more than 50 years. Was it recommended by Experts or a committee headed by an expert, were the states taken into confidence, or was just decided by some individuals without knowing its implications? DISE/U-DISE may be a good case study to know how an institutionalized well-established project can be de-railed at the whims of an individual or two without acquiring any responsibility.

Lack of Accountability due to Absence of Audit Trail: “The data was uploaded in the system by district/block MIS officials who were contractual in nature. In many states, the data entry work was totally outsourced. Hence, there was no clear traceability/audit trail of those who were responsible for the authenticity of the information provided.” Transferring the U-DISE from NIEPA to the ministry will make the contractual staff regular? Since the transfer, how many of the MIS Officials are made regular? Was it because of NIEPA, the MIS staff are contractual, or because of the SSA Guidelines? Except, in the initial period, that too only in a couple of states, never the data entry work had ever been outsourced, totally a false statement. Bihar has outsourced Block Information Centre with one manpower and one Laptop for UDISE+, others may also have done similar arrangements for UDISE+ which is mainly because schools are not equipped to facilitate on-line data entry.  “Transfer of official at the cluster, block and district levels further compounded the problem as a result of which the data was never verified. Since there was no accountability, the officials concerned did not take adequate care to upload consistent and correct data, thereby compromising the reliability of the UDISE” Has the transfer now been stopped? Data was always supposed to be verified first at the cluster level by the CRC Coordinator (100 percent) and thereafter at the block (20 percent) and district level (10 percent). Also, there was a strong in-built consistency check module in U-DISE off-line software which is now missing in the new setup. Even a complete reporter module has not yet been provided. District MIS Coordinators/In-charges have not got access to raw data, unlike the previous arrangement under which every bit of information along with the reporter module to generate ‘n’ number of indicators at district and lower levels were made available. Instead of taking signature (on DCF) at all these levels, the emphasis is now on authentication at all these levels online, which is very tiresome for schools that do not get access to computers. Since data was not fed by the schools onto the online portal, the authentication in most of the cases is being carried out by the Data Entry Operators at the Block level which forfeited the basic purpose of developing an online system. Mute point is to ensure which is key to the quality of data is whether schools have submitted correct data? Which cannot be assured by taking signatures on-line or off-line? How many capacity-building programs, like through EDUSAT have been conducted and how many respondents (HMs, Principals, Head-Teachers, etc.) across the Country have been imparted training before the launch of the UDISE+?

Single DCF for all Categories of Schools: “In UDISE there was one Master DCF for all schools irrespective of the category. However, many of the fields were not applicable to a particular category of school. … This created confusion as a result of which there were instances where the data for the relevant school category was wrongly inserted. Consequently, the information provided by the schools suffered from inconsistencies”. False statement and questioned the understanding of those who are engaged in U-DISE+. Yes, U-DISE had only one DCF unlike 18 DCFs under present UDISE+ and was used to be printed from the SW for over more than a decade. The previous year’s data, except enrolment, was printed as per the category of school obtained based on the lowest and highest class in a school. As it seems officials engaged now were initially more confused than the respondents i.e. schools. Printed DCF from SW has had helped immensely in improving the consistency of data. All the schools were supposed to get 2017-18 populated data under U-DISE+ 2018-19 which is not true for schools that are upgraded in between. Despite the on-line system, the majority of schools got blank printed DCFs which are expected to adversely affect the quality and consistency of UDISE+ data. Were the filled-in DCF checked by the CRC Coordinators or being checked online only? Even at this stage, there is no alternative to the Printed DCF irrespective of how good schools are equipped with computer and internet connectivity.

Multiple Versions of Data Collection Software: “Because of the limitations of UDISE, many states and UTs developed their own MIS systems to collect data required in UDISE DCF. Therefore at the national level, the Department had to contend with two sets of data. Thus, over time, the authenticity and utility of the UDISE gradually decreased and aggregation of data at the national level became difficult” False statement, in fact, the quality and reliability as well as utility of U-DISE data improved with each passing year. What more one can expect that PAB used to appraise and approved annual work plans based on the current year’s data which has now been badly missed. The current year’s plans are no more developed using the current year’s data. Every year by now states used to submit data which is nowhere true now, we have already missed a year or two. There is now a gap of a year, 2019-20 data shall be used in 2021-22? In which years work plan? At the national level, states never at any point in time, submitted two sets of data. It is not because of the limitations of U-DISE data, states developed their own MIS systems just because of their state-specific requirements. After the transfer how many states have discontinued their own MIS systems is a mute question that must be answered. The majority of the states continues using their MIS systems despite the UDISE+ in place and will upload the data by using the Web Service/API onto the online portal. Is this an improvement over the previous arrangement? Certainly not! Previously, we have only one off-line uniform system, now we have more than 25 such systems. States who didn’t have the state MIS system previously are also now planning (like West Bengal) to develop one such system so that UDISE+ requirements are met.

It is expected that improvements as envisaged while launching the U-DISE+ will be visible in years that follow concerning time-lag, consistency, utilization, dissemination, sharing, quality, and reliability of data. Not only this, U-DISE+ has to maintained overall achievements of U-DISE which may not be an easy task. It is also hoped that the district planning module developed by NIEPA will be implemented in the real sense, for sure not only based on EXCEL Tables which may be resulted only if all those who are engaged in planning shake hands.

• U-DISE Vs UDISE-Plus (MS-DOC)
• U-DISE Vs UDISE-Plus (PDF)