Information Requirements for Educational Planning: Limitations and Gaps in the Existing System
Arun C. Mehta
National Institute of Educational Planning and Administration (NIEPA),
17-B, Sri Aurobindo Marg, New Delhi -11 0016 (INDIA)
To achieve goals of Education for All envisaged in the National Policy on Education (1986) and it's Revised Policy Formulations (1992), proper planning is required. Generally planning exercises are of two types, micro and macro level planning. In micro level planning, educational plans are prepared at the sub-national level, such as, institution, village, block and district level where as macro plans are developed at the level which is just above the sub-national level i.e. state and national level. At the district level, blocks, villages and educational institutions are the unit of micro planning but at the state level, district is an unit of micro planning. In India, barring a few states, educational planning is carried-out at the state level that do not ensure adequate participation of functionaries working at the grassroots level. Of late, National Policy of Education (NPE,1986 & 1992) and Eighth Plan envisaged disaggregated target setting at least at the district level that is also one of the major objectives of a number of projects and programmes currently under implementation in different parts of the country. Therefore, development of district plan at the district and lower levels with emphasis on participative planning is of recent origin. Andhra Pradesh Primary Education Project with the main objective of enhancing the professional competence of teachers, UNICEF assisted Bihar Education Project, World Bank sponsored Uttar Pradesh Basic Education Project, SIDA assisted Shiksha Karmi project in Rajasthan and IDA assisted District Primary Education Programme (DPEP) are some of the programmes which have focus on district planning with emphasis on disaggregated target settings. Among these, the scope and coverage of DPEP project is much more wider than other programmes of the similar nature. The programme was first introduced in the year 1993 in 43 districts of seven states, namely, Assam, Haryana, Madhya Pradesh, Karnataka, Kerala, Tamil Nadu and Maharashtra and later expanded to five districts each of Andhra Pradesh and West Bengal in year 1995. In the second phase, four districts each of Gujarat, Himachal Pradesh and Orissa were included in the programme. Further, it is envisaged that by the end of the Eighth Five Year Plan period i.e. March 1997, about 110 districts would come under the programme (MHRD, 1995). Selections of districts under DPEP are based on the criteria where female literacy rates are less than the national average of 1991 Census and where Total Literacy Campaigns (TLC) have been successful leading to an increased demand for elementary education. The main characteristics of DPEP project (MHRD, 1993) are summarised as follows:
· emphasising the local area planning with district plans being formulated in their own right instead of being derived from a state plan project document;
· infusing greater rigour and professional inputs in planning and appraisal;
· more focused targeting in educationally backward districts and districts where Total Literacy Campaign have been successful;
· more focused coverage would initially focus on primary stage (Classes I-V & its NFE equivalent) with stress on girls and for socially disadvantaged groups; and
· emphasising capacity building and networking of district, state and national level institutes in the fields of education management and social services to provide the resource support for the programme.
The Present Article
In the present article, a detailed list of items on which information is required both at the macro and micro levels of planning is briefly presented which is linked to goals of Education for All. Before that, different stages of plan formulation and implementation is presented. Keeping in view the planning requirements, information needed in future is also discussed in detail which is followed by limitations and gaps in the existing information system. Data gaps have been grouped under different headings, such as, demographic and literacy, enrolment and repeaters, teaching personnel and financial statistics. In the last, suggestions for improvement have been presented.
Before, a detailed list of variables required for planning both at the macro and micro levels is presented, different stages of plan formulation and implementation is briefly presented below.
Stages of Planning
The different stages of planning in general and education in particular are:
I. Diagnosis of Present Position with respect to:
* General Scenario and
* Educational Scenario
II. Review of Past Educational Plans, Programmes and Policies
III. Projections of Major Socio-Economic and Educational Trends
IV. Plan Formulation and
V. Plan Implementation.
In order to meet data requirements of planning stage at I above, a variety of information relating to both general and educational scenario needs to be collected. Information such as on, geography, irrigation, transportation, industry and administrative structure is required so as to prepare a general scenario of the existing infrastructural facilities available in a district and its sub-units. So far as the educational variables are concerned, required information can be grouped under information relating to demography, literacy and education sectors. Under the demographic variables, total population and its age and sex distribution separately in rural and urban areas needs to be first collected. Apart from total population, age-specific population in different age-groups is also required. For programmes relating to primary and elementary education, population of age-groups 6-10, 11-13 and 6-13 years and for adult literacy and continuing education programmes, population of age-group 15-35 years is required. Similarly, single-age population (age `6') is an another important variable on which information needs to be collected. In addition, information on some of the vital indicators, such as, expectation of life at birth, mortality (death) rates in different age-groups, fertility (birth) rate and sex ratio at birth is required so that the same can be used to project future population. For adult literacy and continuing education programmes, number of literates and illiterates in different age-groups is required which should be linked to population in different age- groups. In addition, complete information of TLC programmes implemented in the past in a district with reference to its objectives, strategies and major achievements would be useful, if similar programmes are undertaken in future.
Universal access to educational facilities is one of the important components of Educational for All, hence a variety of information relating to population of a village/habitation is required so that school mapping exercises are undertaken. Exercises based on school mapping play an important role in order to open a new school or whether an existing school is to be upgraded or closed down. Thus, number of villages distributed according to different population slabs is required so that opening of school in a habitation is linked to the existing norms. In case of hilly and desert areas, the population norm of 300 can be relaxed and lowered down to 200. Habitations served by schooling facilities and whether they are available within habitation or a walking distance of one and three kilometers along with total number of habitations in a district is also required so as to assess the existing situation with particular reference to goal of universal access. Similarly, percentage of rural population served by the schooling facilities can also be used as an indicator of access which should be linked to school mapping exercises. Information relating to adult learning and non-formal education centers is also required which should be viewed in relation to illiterates, out-of-school children and child workers.
Once the population is access to educational facilities, the next important variable on which information is required is number of institutions. Within institutions, the first important variable is availability of infrastructural facilities in a school and their utilisation. Information relating to buildings, play grounds and other ancillary facilities, such as, drinking water, electricity and toilets needs to be collected. In other words, complete information relating to scheme of Operation Blackboard (1987) with particular reference to its implementation, adequacy, timely supply and utilisation needs to be collected. Similarly, information relating to number of classrooms and their utilisation, class size, number of schools distributed according to class sizes and number of sections is also required which can be used in institutional planning related exercises. The major objectives of 1987 Operation Blackboard scheme consisting of the following three interdependent components are provision of:
· a building comprising at least two reasonably large all-weather rooms with a deep verandah and seperate toilet facilities for boys and girls;
· at least two teachers in every school, as far as possible one of them a women; and
· essential teaching-learning material including blackboards, maps, charts, toys and equipment for work experience.
The scheme was recently revised so as to (MHRD, 1992):
· provide flexibility to schools in providing teaching-learning material relevant to their curriculum and local needs;
· to relate the scheme with micro planning wherever undertaken, so that supply of inputs is matched by demand side interventations to promote participation;
· intensify training in the use of teaching-learning equipments; and
· extend the scheme to upper primary schools.
Enrolment is the next important variable on which detailed information is required. Both aggregate and grade-wise enrolment together with number of repeaters over a period of time needs to be collected separately for boys/girls & SC/ST population, rural & urban areas and for all blocks and villages of a district. The enrolment together with corresponding age-specific population can be used to compute indicators of coverage, such as, Entry Rate, Net and Gross Enrolment Ratio, Age-specific Enrolment Ratio and indicators of efficiency. Similarly, detailed information on number of teachers distributed according to age, qualifications, experience, subjects etc. along with income and expenditure data is also required for critical analysis so that optimum utilisation of the existing resources is ensured. Thus, from the basic information, a variety of indicators can be generated which can be of immense help to understand a district and its sub-units with particular reference to its demographic structure. It is not only the past and present information that is required but for proper and reliable educational planning, information on some of these variables is also required in future. Further, if the emphasis of planning exercises is on disaggregated target setting, then the entire set of statistics would have to be collected both at the micro and macro levels of planning. The POA (1992) identified poor urban slum communities, family labour, working children, seasonal labour, construction workers, land-less agricultural labour, forest dwellers, resident of remote and isolated hamlets as some of the target groups. Thus information on these groups also needs to be collected, if considerable size of a group(s) is concentrated in a district or its sub-units.
A detailed list of items on which information is required for educational planning is presented below. The list is not an exclusive one and more items may be added looking into the planning requirements at the national, regional and sub-regional levels.
I. Demography and Literacy Data
· Number of districts/tehsils/talukas/administrative and educational blocks;
· Population by age and sex, school-specific age (6-10, 11-13 & 6-13 years), regions, castes and economic levels, sex ratio, density of population, mortality (death) and fertility (birth) rates;
· Distribution of habitations according to provision of primary, middle and secondary schooling facilities, walking distance and population slabs; habitations without schooling facilities;
· Number of villages/towns in different population slabs and
· Number of literates and illiterates by age and sex separately for rural and urban areas and scheduled caste and scheduled tribe population.
By type, level, management, sex, courses and location; capacity and utilisation of existing institutions; number, intake, out-turn and location of teachers training institutions; institution/teacher ratio, institution/pupil ratio, hostel facilities with intake capacity and actual enrolment; number of single teacher primary schools; number of schools without blackboards; and number of schools with/without building, type of buildings and vocational and technical institutions.
By age i.e. age-grade matrix, sex (boys/girls), grades (I to XII), subjects, area (rural/urban) and institution-wise (primary, middle etc.); average daily attendance; enrolment of SC and ST population; admission data (entry rate) and data on various courses; out-of-school children in different age-groups, repeaters and drop-outs by age, grade and sex and transition rates by sex and at terminal classes and scholarships granted and number of beneficiaries under different schemes.
(c) Teaching Staff
Teachers by age and sex, rural/urban, grade and scales of pay, subjects, qualifications and experience, trained and untrained and stage for which employed, attrition rate, Operation Blackboard information on teachers post: sanctioned, appointed and transferred, teachers-training institutions, persons trained and type of training.
(d) Building and Area
Type, ownership and year of construction, present status; number and size of rooms with nature of their utilisation and seating capacity; vacant area available for new or additional construction; intake capacity; availability of drinking water, toilet and electricity facilities, playground facilities and Operation Blackboard information on number of classrooms/buildings sanctioned and constructed.
Physical facilities in school library and their utilisation (number of books, average number of readers etc.), laboratory equipment, furniture, sports material, audio-visual aids, additional requirements, and OB information on educational kits and their utilisation, supply and adequacy.
(f) Non-teaching Staff
Number and working of inspection and supervisory staff, non-teaching staff by pay scales, sex and school-wise supervisions or inspections per month/year, persons involved in data collection according to qualifications and training at different levels.
(g) Examination Results
Examination results of all terminal classes, results of National Talent Search Examination, administrative services by state and universities-wise and policy of no detention.
(h) Income and Expenditure
School-wise, scheme-wise, recurring and non-recurring capital and revenue, income and expenditure; and expenditure on incentives and scholarships, private cost on education, tuition fee, laboratory fee and other fee.
(i) Miscellaneous Information
In addition, miscellaneous information on the following items is also required which in most of the cases either not available or very limited information is available:
· Parent Teacher/Mother Parent Organisation
· Student Union/Organisation
· Student Health Services
· Sports Facilities
· State Institute if Educational Management and Training
· Navodaya Vidhalayas
· Total Literacy Campaigns
· Distance Education
· Teaching Material and Text Books
· Village Education Committees
· Circle Education Committees
· Number of Working Days in an Academic Year
· Mid-day Meal Scheme and
· On-going Programme/Projects.
It is not that all the data required for planning is available but information on a good number of variables is conspicuous by their absence so as the quality of data which is questioned, time and again, by the data users and researchers (Mehta, 1996,1). Generally, secondary sources are explored for diagnosis of the existing situation but for the variables which are not available at lower or the lowest level, primary data needs to be collected. For example, age-grade matrix is one such variable which is not available at the micro level but plays an important role in setting-out disaggregated targets. Hence, information on age-grade matrix and other variables of similar nature is required for which sample surveys at the local level needs to be conducted and data generated. So far as the information on demographic variables is concerned, Census publications should be explored for both present and past data. Information on educational variables can be collected and used from the publications of State Education Departments which may or may not be available in detail as required in planning exercises. However, state-wise information is available on most of the variables from the MHRD publications but latest publications are not available (Mehta 1993 & 1996,1). As noticed above, information relating to infrastructure, access, ancillary facilities, age-grade matrix etc. is available from the NCERT publications but only at few points of time. Keeping in view the data requirements at the micro-level, relevant Officers may be approached for NCERT data at the district level but again time-series information is not at all available at a single place (Mehta, 1996,2).
Generally cross-sectional data for analysing existing situation and time-series information for capturing trends is required, time period of which depends upon the nature of variable which is to be extrapolated. The next important question which may crop-up is the level at which information needs to be collected which depends upon the unit of planning. As soon as the diagnosis exercise is over, the next stage of planning needs review of past plans, policies and programmes implemented in the district with respect to their objectives (Mehta, 1996,3). Generally, these programmes are related to promotion of education of SC/ST & girls, Total Literacy Campaigns etc.. Reasons of failures and success of a particular programme need to be thoroughly analysed. If need be, the existing programme with or without modifications can be continued which should be followed by setting-up of targets on different indicators. Broadly, following are the areas on which future targets need to be fixed which may vary from block to block even within a district:
* Population Growth Rates
* Entry Rate
* Gross & Net Enrolment Ratio
* Drop-out, Repetition and Promotion Rates in different grades
* Retention Rates and
* Per Pupil/Unit Cost.
Targets on the above items should be practicable, feasible, achievable and should be based on the immediate past and linked to policy guidelines. During the recently concluded (1994) Overseas Development Administration and Government of India Appraisal Mission to nineteen districts of Madhya Pradesh under DPEP project, it was noticed that in most of the districts, enrolment projection exercises were not undertaken and target on Gross Enrolment Ratio in year 2001 was fixed arbitrary by assuming 20 per cent as an estimate of overage and underage children in all the blocks of nineteen districts without even knowing of the actual grassroots realities. Neither aggregate nor grade-wise enrolments were projected. In the absence of which it is rather impossible to estimate reliable annual number of beneficiaries, additional requirements of teachers, opening of new schools, etc.. As mentioned one of the other important objectives of the DPEP project is to reduce the existing level of drop-out rate for all students to less than 10 per cent which means a substantial increase in existing retention rate. Though retention rate at Grade V has been computed in all the DPEP districts of Madhya Pradesh, no attempt has been made to compute grade-wise promotion, repetition and drop-out rates, all which plays a significant role to obtain goals of Universalisation of Primary Education. Similarly, the UNICEF, Government of India and Government of Bihar joint Appraisal Mission to Bihar Education Project (BEP) observed that process of disaggregated target setting in BEP districts has been started but the future targets on drop-out and retention rates are still fixed in an isolation without even knowing the present status of grade-to-grade drop-out and retention rates. Also, targets on enrolment ratio (gross) have been fixed even with out knowing the existing entry rate which infact help us in identifying the disaggregated areas and groups with in the district. In seven BEP districts, the methodology adopted in computing drop-out rate is not conventional which in most of the cases produced retention rate even more than 90 per cent (see BEP Appraisal Mission Report, 1994). If the targets are not reliable, future enrolment would also become unreliable which in turn will make all corresponding estimates unreliable. The Eighth Five Year Plan also fixed national targets on access, retention, attainment and monitoring systems which are summarised below (MHRD, 1993):
· Universal enrolment of all children, including girls and persons belonging to SC/ST;
· Provision of primary school for all children within one kilometer of walking distance and of facility of non-formal education; and
· Improvement of ratio of primary school to upper primary school to at least 1:2.
· Reduction of drop-out rates between Classes I to V and I to VIII to 20 and 40 per cent respectively; and
· Improvement of school facilities by revamped Operation Blackboard, to be extended to upper primary level also.
· Achievement of minimum levels of learning by approximately all children at the primary level, and introduction of this concept at the upper primary stage on a large scale.
· Local level committee, with due representation to women and teachers, to assist in the working of primary education to oversee its functioning and
· Improvement of the monitoring system for UEE.
Future Information Requirements
Once the reliable targets are set-out, the next important task is to work-out additional number of children who will be joining education system over a period of time which is required annually so as to know number of beneficiaries which cannot be reliable unless detailed enrolment projection exercises are undertaken. For example, a number of schemes are proposed in the DPEP project which are most likely to benefit children in the schools, it would be an additional advantage, if disaggregated estimates of enrolment are made available at the block level separately for boys and girls, rural and urban areas and Scheduled Castes and Scheduled Tribes children. Therefore, apart from the past and present information, information on a number of variables in future is also needed which may or may not be readily available. Before a list of items on which future information required is presented, we first examine enrolment projection techniques, methods and models with particular reference to availability of data (see for details, Mehta 1995,2).
The techniques of enrolment projections can broadly be classified into two groups, namely, mathematical and analytical methods (Mehta, 1996,4). Mathematical methods require aggregate enrolment data at least for ten years, and only total enrolment can be projected by employing both linear and non-linear equation methods. These methods involve an extrapolation of the past into the future and assume that the past trend in enrolment would continue into the future. On the other hand, in analytical methods, apart from actual enrolment, estimation, assumptions and targets on items mentioned above are required. The demographic pressures on education can also be captured in the analytical techniques as the computation of entry rate is based on the population of school entrance age `6' years. This rate has a significant bearing on future enrolment. Analytical methods are based on Student Flow Analysis which starts at the point where students enter into an education cycle i.e. Grade I. If the information on number of repeaters is available, the method is known as Grade-Transition method, otherwise it is known as Grade-Ratio Method. Thus, an element of judgement in terms of policy variables can be introduced in analytical methods, therefore, the method is appropriate for detailed enrolment projections (for details see Mehta, 1996,2). The method requires following set of data:
· Future age-specific (6-10 & 11-13 years) and single age population (`6'), say up to year 2000-01
· Grade-wise enrolment for at least two consecutive years and
· Grade-wise repeaters (optional) for the same years of which enrolment is available.
The above list reveals that age-specific and single-age population are two important variables on which future enrolment is significantly based upon. Projection of age and sex distribution of population requires detailed information on base year vital rates and assumptions on a number of items mentioned above. Thus, keeping in view scant demographic data at the state level, it is not possible to undertake detailed population projection exercise. Similarly, future population of age `6' plays an important role from which the system is expected to receive continuous flow of students through Grade I in years which follow but the same is not available on regular basis and whatever is available is through Census publications once in a decade. Future estimates on the variable is rarely available at the sub-national level and whatever is available is at state and all-India level and the same for 1991 is not even released at the state leve (Mehta 1996,5). However, for fifteen major states estimates of the Standing Committee of Experts on Population Projections (1989) set-up by the Planning Commission for the period 1990, 1995, 2000 and 2005 are available. Both age-specific and single-age population separately for male and female population is available but the same is based on population up to the 1981 Census. Thus, the Standing Committee estimates are bound to change as and when revised estimates based on 1991 Census are made available. However, population projections is rarely available at the district level and hence, there is no option but to undertake independent exercises. The available expertise at the district level do not suggest that they are in a position to undertake independent population projection exercises but Mehta (1996,5) has recently identified that Ratio Method of Population Projections is appropriate for the micro level projections and do nor demand detailed set of data on vital indicators which are generally not available at the micro level. Therefore, unless reliable estimates of population are available, different indicators of planning would continue to present mis-leading picture.
The variables required in future can be grouped under population, enrolment, teachers and cost of education apart from some information on future indicators of efficiency. Broadly, following are the items (quantitative) on which information in future is required:
I. Demographic Variables
(I) Population (Rural & Urban & SC & ST)
* Total Population
* Age-Sex Composition of Population
* Rate of Population Growth
* Single Age Population and
* Age-specific Population: 6-10, 11-13 & 15-35 years.
(ii) Literacy Status of Population
Literates and Illiterates in different age-groups and distribution of literates according to educational level.
II. Educational Variables
Indicators of Coverage
* Gross Enrolment Ratio\Net Enrolment Ratio and
* Age-Specific Enrolment Ratio
* Entry Rate
* Promotion Rate
* Repetition Rate
* Transition Rate and
* Drop-Out Rate
(iv) Indicators of Educational Quality
* Internal Efficiency of Education System
* Input/Output Ratio
* Wastage Ratio
* Pupil Teacher Ratio
* Percentage of Non-teaching Expenditure
* Accessibility of Educational Facilities and
* Pass Percentage in different Examination
(v) Other Miscellaneous Variables
* Projection of Teachers Requirements
* Projections of Financial Requirements
* Additional Number of Schools/Sections Required
* Institutional Building Requirements
* Subject-wise Surplus and Shortage of Staff and
* Manpower Projections.
Efficiency of education system and projections are thus two important areas of planning which require basic information on enrolment and repeaters. Though, data on both of these variables are available but the same has a number of limitations. Therefore before the data gaps are presented, some of the important distortions in data noticed recently by Mehta (1995,2) is presented below.
Though state-wise enrolment is available but for many a states the same is not available even for the year for which the publication is latest available. In many of the remaining states, the previous year enrolment data is repeated in the next years publication. In Andhra Pradesh grade-wise enrolment for years 1988-89 and 1989-90 and in Haryana, enrolment of girls reported in year 1988-89 in Grades V and VI are exactly the same. In Madhya Pradesh both enrolment and repeaters reported in years 1988-89 and 1989-90 are same where as in Orissa, enrolment of Grade I in year 1988-89 is not at all reported. In Rajasthan, enrolment in Grade I and II are jointly reported for the same year. Further, it has been noticed that in West Bengal, grade-wise enrolment reported for three consecutive years namely, 1987-88, 1988- 89 and 1989-90 is exctly the same. Thus, keeping in view the limitations in enrolment data, it is not possible to undertake detailed enrolment projection exercise in a number of states.
Similarly, a number of limitations are also noticed in data on repeaters. Though, state-wise number of repeaters is available but many a states do not collect information on it which may be due to implementation of no detention policy upto primary level. But at the same time, till recently states such as, Andhra Pradesh, Jammu & Kashmir, Maharashtra, Tripura and West Bengal did not report incidence of repetition in any grade. On the other hand some states, such as Haryana and Madhya Pradesh, strictly follow policy of no detention upto Grade II, where as Nagaland, Tamil Nadu and Uttar Pradesh follows it upto Grade III. Also, in Jammu & Kashmir, Meghalaya, Rajasthan and Sikkim when repeaters are taken out from enrolment, they exceed enrolment in the previous grade which give promotion rate more than hundred per cent. This may be either due to mis-reporting of number of repeaters or due to large scale enrolment of migrants from other areas to a particular grade. In Madhya Pradesh, till recently (1989-90) a large number of children used to repeat a particular grade but suddenly, it is reported zero. The drop-out rate in Haryana in Grade I reduced to zero in 1989- 90 from about five per cent in previous year. For capturing the trend in repetition rate, time-series information on repeaters is required but the series which was discontinued in 1970-71 but revamped in 1984-85 is available only up to the year 1991-92 (Mehta 1995,1).
Since, enrolment and number of repeaters in different grades plays an important role in working-out indicators of efficiency and future enrolment, unreliable data may dramatically change the future scenario and even make the exercise meaningless and futile.
Different data gaps can be grouped under the following sub- headings:
* General Gaps
* Demography and Literacy
* Infrastructure and Schools Effectiveness
* Enrolment and Repeaters
* Teaching Personnel
* Financial Statistics and
* Miscellaneous Gaps.
(i) Time-series Data
Lack of time-series data at the district level is an important limitation of the existing information system. At present district-wise statistics on selected educational items is available for year 1971-72 and 1977-78 and for the year 1981-82, it is available only for some of the states. As mentioned, the publication which used to disseminate district-wise information was discontinued and hence no data is being disseminated at the district level. The unpublished survey data of NCERT is available for the years 1973, 1978, 1986 and 1993, which if made available at single place may help in constructing a time-series at at least six points of time. On the other hand statistical abstracts of different States & UTs disseminate educational statistics at district level but their coverage is too limited to undertake detailed planning exercises. Also the date of reference vary from state to state and the information available is scattered and coverage not uniform. Due to change in boundaries and creation of a number of new districts, the limited time-series information that is available, is not free from the limitations.
(ii) Rural/Urban Distribution
Until 1970-71, the whole set of data was available separately for rural, urban and all areas but the series was discontinued in 1971-72 and revamped in the year 1976-77. Also, whatever data is available for rural areas is found to be inadequate and basic information on a good number of variables is simply not available.
(iii) Administrative Staff
Data on administrative and non-teaching staff is too scanty to be useful, with the result that the total requirement of personnel and facilities is difficult to determine.
B. Demography and Literacy
Though population figures are available from the Census publications, projections of population in the specific age-group and single age `6' at the state level have been found to be suffering with large margin of errors (Mehta, 1996,5). At the district level, the projections are rarely available and if available, not reliable. A number of indicators required in planning is based on population which if not available/reliable, may significantly affect the targets which are required to set-out at different stages of planning. One of the other important characteristics of population on which information is obtained in the Census is literacy. In 1991 Census, on the request of MHRD and Planning Commission, the population aged seven years and above is classified as literates and illiterates as against five years and above in the previous Census (see Census of India 1991 publications). At this stage, since data on age-population is not available, the two Census figures on literacy cannot be compared. Though, officially the school entrance age is six but studies (NIEPA, 1992, 93,1 & 95) show that a large number of under-age children are in Grade I which do not justify the change in definition of literacy which is also supported by NSSO data on Participation in Education (1991). Also, the future population of age-group 15-35 years is rarely available on regular basis at the district and its sub-units level. Therefore, it is very difficult to judge the performance of literacy promotion programmes in terms of its coverage and achievements.
C. Enrolment & Repeaters
One of the important indicators of coverage is Net Enrolment Ratio which is based on age-grade matrix but is currently not available. In the absence of which, progress towards UPE and UEE cannot be judged and monitored efficiently. However, few estimates are available at the state level but at the district level reliable estimates are not available.
D. Teaching Personnel
In order to undertake stock of the existing situation with regards to teachers at different levels, detailed information on number of teachers with respect to its adequacy, distribution of teachers according to sex, qualifications, age, training, subjects etc. seperately in rural and urban areas is required but unfortunately information on most of these items is simply not available or the same may be available at the lowest level but is not properly dissminated. In the absence of adequate data, it is not possible to ascertain whether teachers are equally distributed in rural and urban areas or the distribution of female and qualified teachers are even. Amongst such variables, teachers attrition rate is an important indicator but not available. In the absence of which, future estimates of teachers requirement on account of attrition is difficult to obtain. However, on sample basis some estimates of attrition rates are now available (NIEPA, 1995). For the first time, the information on the variable is collected in the Sixth All India Educational Survey but the same has not yet been disseminated.
E. Financial Statistics
(i) Selected Educational Statistics provides budgeted expenditure on education as aggregate of all levels of education but capital account budget is not given. Also, budgeted expenditure on education is not comparable with the data given in the Education in India (Volume II). The statistics on direct expenditure on education is available by levels of education where as indirect expenditure is not available by levels. On the other hand, institutions are classified into primary, middle and high/higher secondary schools, based on the top class in the school, which possess serious problems in estimating cost of education by levels meaningfully (Dhar, 1978 and Tilak, 1985).
(ii) Recently, NIEPA (1993) organised a two days seminar on Educational Statistics with emphasis on Financial Statistics in India. Some of the data-gaps identified in the workshop are summarised below:
(a) The financial statistics which is available is generally not free from errors and all the sources of finance for education is not included. For example, local bodies, such as, Municipal Corporations run both Primary and Middle schools but the expenditure incurred by them is generally not available and hence is not included in the statistics on educational expenditure.
(b) The data needed for calculating unit cost at different levels of education, namely, Primary, Middle, Secondary/Higher Secondary and other higher levels is not readily available. There are schools which have both Primary and Middle classes and some teachers teach students of both of these stage and more stages. Thus, it is not only difficult to collect teachers separately at Primary and Middle levels of education but in such cases, it is difficult to distribute expenditure on teachers salaries and other recurrent expenditure by level and type of education (Srivastava, 1993).
(c) The information on private expenditure is generally not available and is difficult to determine. Many private schools particularly those which are unaided do not supply the required information on income and expenditure, and even when they supply the data very often it is not very reliable (Srivastava, 1993). Similarly, the private expenditure incurred by parents on their wards books, stationary etc. is not available by any of the regular sources but occasionally the same is available by NSSO as a part of its household survey on consumption.
(d) The available financial statistics indicate that bulk of expenditure is incurred on teachers salaries. But separate statistics on pensions, gratuity etc. is not available or the same is included in the teaching expenditure is not clear. Similarly, it is also not clear whether expenditure on administration or welfare services or examinations are part of the existing statistics on educational expenditure.
(e) The existing financial information on educational variables is collected through ES-II(S) and ES- II(C) which were evolved by splitting the then existing ES(II) form on the recommendations of High Level Committee on Educational Statistics (1982). The committee recommended that `at the elementary stage, the data should be collected only on (a) teachers salaries: (b) other recurrent costs grouped together: and (c) capital costs: at higher levels a more detailed classification of items of expenditure is necessary. In the case of schools fully financed by the government or local bodies, such data should be collected from the concerned educational authorities. In the case of private aided and unaided schools, a separate form should be used to collect income and expenditure data'.
In addition to the data gaps identified above, there is a limited or absolutely no data available on the following items;
* Average Daily Attendance in School/College;
* Distribution of Institutions by Capacity and Size and of Classes by Size and Space;
* Unrecognized Institutions;
* Correspondence Courses;
* Teachers by Age and Qualifications;
* Socio-economic Composition of Enrolment;
* Non-formal Education;
* Information on Scholarships;
* Free Student-ships & Free Concessions;
* Mid-day Meals;
* Operation Blackboard Scheme;
* District Institutes of Educational Training;
* Navodaya Vidhyalayas;
* Distance Education;
* Part-time Courses etc..
Going through the list of data-gaps identified above, one gets the impression that the same have been identified time and again in a number of seminars and conferences organised in the past but to no significant improvement has been noticed.. However, sporadic attempts have been made to bridge the gaps on the basis of sample surveys but the same had a number of limitations in view of its periodicity and coverage. Till the items on which information is currently missing are included in regular collection of statistics/all-india educational surveys, the statistics so collected on sample basis cannot serve the purpose in a manner for which they are required in planning exercises. It has also been noticed that the existing missing information on a number of variables is available but the same is scattered, hence need efforts to integrate different data bases which are in existence in the country. Time-series data at the district level is one such gap which can easily be filled-up with the available statistics. Similarly future information on variables of vital importance can also be generated, if built-in procedures and routines are developed within the existing information system. Some of the missing variables have already been formed part of the Sixth All India Educational Survey conducted by the NCERT with September 30, 1993 as its date of reference. The functionaires of those who are currently engaged in data collection work at different levels unless involved in the formulation of educational plans, the existing limitations in the information system cannot be improved upon for which disaggregation at the lowest possible level i.e. either at the institutional or village level would ensure particiaption of all concerned at different levels. Hence. Local-level Information System (LIS) with focus on infrastructural facilities and classroom interventations would need to be developed. Various steps have been initiated in the recent past to develop an integrated Educational Management Information System in the country, which if developed will help us to overcome the limitations and gaps in the existing information system. Among such efforts, DPEP proposes to develop an EMIS at the district level which is envisaged to collect information on a number of missing items but the same would take some more years to fully develop, as the project is not likely to be expanded to remaining districts of the country in the near future.
Census of India, Paper-2 of 1991, Office of the Registrar General, Government of India, New Delhi, 1992.
Dhar, T.N. (1978), Educational Statistics in India: Organisational Arrangements, Problems and Defficiencies, NSCEPA, New Delhi.
Mehta, Arun C. (1993), A Note on Educational Statistics in India, Journal of Educational Planning and Administration, VII(1), pp 105-17, January, New
Mehta, Arun C. (1995,1), Education for All in India - Myth and Reality, Kanishka
Publishers, New Delhi
Mehta, Arun C. (1995,2), Student Enrolment Flows and Projections, Report of the World Bank Sponsored Project, NIEPA, New Delhi.
Mehta, Arun C. (1996,1), Reliability of Educational Data in the Context of NCERT
Survey, Journal of Educational Planning and Administration, NIEPA, New Delhi, July.
Mehta, Arun C; (1996,2), Introduction to All India Educational Surveys: School Education, Educational Administration and Technical Manpower Information System, NIEPA, New Delhi.
Mehta, Arun C. (1996,3), Development and Utilisation of Database for Non-formal
Literacy Programme and Networking of Computers, Journal of Adult Education,Adult Education Association of India, , April-June, New Delhi.
Mehta, Arun C. (1996,4), Projection Techniques:Enrolment, Modules on Micro-level
Educational Planning, NIEPA, New Delhi, processed.
Mehta, Arun C. (1996,5), Population Projections: Sub-National Dimensions, Commonwealth Publishers, New Delhi.
Ministry of Education and Culture (1982), Report of High Level Committee to Review
the Educational Statistics System in India, Government of India, New Delhi.
MHRD (1986 & 1992), NPE : Programme of Action, New Delhi, Government of India, New Delhi.
Ministry of HRD (1993), DPEP Guidelines, Department of Education, New Delhi, Government of India
MHRD (1992,93 & 95), Annual Report : 1991-92, 1992-93 & 1994-95, Government of India, New Delhi.
NIEPA (1992), Report of Use of Sample Survey Techniques in Educational Statistics, Educational Planning Unit (mimeograph), New Delhi.
NIEPA (1993,1), National Sample Survey for Monitoring of UEE: 1990-91, New Delhi,
NIEPA(1993,2), Report of the Seminar on Educational Statistics with emphasis Financial Statistics in India, New Delhi, February.
NIEPA (1995), National Sample Survey for Monitoring of UEE :1991-92, Report (Phase II), NIEPA, New Delhi.
NSSO (1991), Participation in Education, 42nd Round (July 1986-June 1987), Sarvekshana, Vol. XIV, No.3, January - March.
Standing Committee of Experts on Population Projections(1989), Planning Commission. Government of India, New Delhi.
Srivastava, A.B.L; (1993), Problems and Issues in Collection of Financial Data Relating to Education, Report of the Seminar on Educational Statistics with emphasis on
Financial Statistics in India, New Delhi, February.
Tilak, J.B.G. (1985), Data Base for analysis of Costs of Education in India, Readings in Educational Finances in India, NIEPA, New Delhi.
UNICEF (1994) Sponsored Review-cum-Appraisal Mission Report of the Bihar Education Project, New Delhi.