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Indicators of Educational Development: Concept and Definitions
Arun
C. Mehta
·
DIAGNOSIS
OF THE EXISTING SITUATION
INTRODUCTION
To
achieve the goal of `Education for All' envisaged in the National Policy on
Education (1986) and its Revised Policy Formulations (1992), proper planning
and effective implementation is required.
Generally planning exercises are initiated at two levels, micro and
macro levels of planning. In micro planning, plans are prepared at sub‑national
level, such as, institution, village, block and district level, whereas 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 units 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, which do not ensure adequate participation of functionaries
working at grassroots level. Of late,
National Policy on Education (NPE, 1986 & 1992) and Eighth Plan envisaged
disagregated target setting at least at the district level, which is also one
of the major objectives of a number of projects and programmes currently under
implementation in different parts of the country. Such programmes are IDA
assisted District Primary Education Programme (DPEP), ODA assisted Andhra
Pradesh Primary Education Project, UNICEF assisted Bihar Education Project (now
under the ambit of DPEP), World Bank sponsored Basic Education Project in Uttar
Pradesh (also under DPEP) and SIDA assisted Shiksha Karmi and Lok Jumbish
projects in Rajasthan among of which the scope and coverage of DPEP is much
more wider than other programmes of similar nature. The programme was first initiated in the year 1993 in 43
districts of seven states, namely, Assam, Haryana, Madhya Pradesh, Karnataka,
Kerala, Tamil Nadu and Maharashtra. At present, the programme is under
implementation in about 150 districts of fifteen states. Therefore, development of district plan at
the district and lower levels with emphasis on participative planning is of
recent origin. DIAGNOSIS OF THE EXISTING SITUATION
There are different stages of planning but
diagnosis of the educational development is one of the most important stages of
planning. It is taking stock of the present situation with particular reference
to different objectives and goal of `Education For All' in general and
`Universalisation of Elementary Education' in particular. One of the other main objectives of the
diagnosis is to understand district and its sub‑units with reference to
educational development that has taken place in the recent past. Generally, cross‑sectional data for
analysing existing situation and time‑series information for capturing
trend is required, period of which depends upon the nature of a variable, which
is to be extrapolated. The next
important question is the level at which information need to be collected which
depends upon the basic unit of planning.
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 to decide location of 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 existing norms. In case of hilly and desert areas, the
population norm of 300 is generally relaxed and lowered down. Habitations served by schooling facilities
and whether they are available within habitation or a walking distance of one
and three kilometers along with the total number of habitations in a district
is also required, so as to assess the existing situation with reference to
universal access. Similarly, percentage of rural population served by schooling
facilities can also be used as an indicator of access, which should be linked
to school mapping exercises. Similarly, information relating to adult learning
and non‑formal education centers is required which should be analysed in
relation to number of illiterates, out‑of‑school children and child
workers. Once the indicator of access is analysed, the next
variable on which information is required is number of institutions. Within the
institutions, the first important variable is availability of infrastructure in
a school and its utilisation.
Information relating to buildings, playgrounds and other ancillary facilities,
such as, drinking water, electricity and toilets need to be collected and
analysed. In other words, complete information relating to scheme of Operation
Blackboard (MHRD, 1987) with reference to its implementation; adequacy, timely
supply and utilisation need 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. 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, Scheduled Caste and Scheduled Tribe
population, rural & urban areas and for all the 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 and subjects along with income and expenditure data
is also required for critical analysis, so that optimum utilisation of the
existing resources is ensured. 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 a few variables is also required
in future. If the emphasis of planning exercises is on disaggregated target
setting, then the entire set of statistics would have to be collected both at
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 need to be collected, if considerable size of a group(s) is
concentrated in a district or its sub‑units. It is not that all the data required
for planning is available but information on a good number of variables may not
be available. Generally, secondary
sources are explored for diagnosis of the existing situation but for the variables,
which are not available, primary data need to be collected. For example, age‑grade
matrix is one such variable that is not readily available at the micro level
but plays an important role in setting‑out-disaggregated targets. Hence,
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 sources of
data are concerned, Census publications for demographic and publications of
State Education Department may be explored for educational data but the same
may or may not be available in detail as required in the planning
exercises. However, state‑wise
information is available on most of the variables from the publications of the
Department of Education, Ministry of Human Resource Development (MHRD) but
latest publications are not available.
For information relating to infrastructure, access, ancillary facilities
and age‑grade matrix, NCERT publications may be explored but that is
available only at a few points of time. A variety of information relating to both general and
educational scenario need 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 infrastructure 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 need to be first collected. Apart from the 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 a few
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 literate and illiterates in
different age groups is required which should be linked to population in
different age groups . 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 its objectives, strategies and major achievements.
It would be useful, if similar programmes are undertaken in future. (Mehta,
1997a). Generally, these programmes are
related to promotion of education of Scheduled Caste and Scheduled Tribe, Girls
and Total Literacy Campaigns. 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 the targets on different
indicators. The variables identified for both general and educational
scenarios cannot be used in its original form to draw inferences. Therefore, once the basic set of information
is collected and complied, the next important step is to analyse data so as to
derive meaningful indicators. The derived indicators are used to analyse
different aspects of educational planning with particular reference to goal of ‘Education for All’ and can also serve
as a decision support tool. Therefore,
in the present article, the concept of an indicator and the methodology on
which it is constructed is demonstrated by taking actual data at the all‑India
level. If information on a particular
variable is not available from the official sources, other agencies, like NCERT
are explored and indicators computed.
The indicators obtained are interpreted and its implications on the goal
of ‘Education For All’ are also
examined. In addition, the concept of
an indicator and different types of statistics, such as, primary and secondary
data, cross‑section and time‑series data and institution and stage‑wise
data has also been discussed in length. More specifically, indicators on the
following aspects of planning is constructed, developed and analysed : (a) Coverage of Educational System (b) Internal
Efficiency of Education System and (c) Quality of
Services and its Utilisation. Indicators on the above aspects can answer a variety of
questions. System's level of
development, accessibility and children taking advantage of educational
facilities are some of the questions, which relate to coverage of an education
system. Thus, simple indicators like,
enrolment ratio, entry rate, out‑of‑school and additional children
need to enrol have been discussed. The next set of questions relates to
internal efficiency of education system.
Information on number of children who enter into the system and complete
an education cycle, those who dropout from the system in between and number of
children who reach to the next higher level can be obtained, if indicators of
efficiency are computed. For this
purpose, methods like, Apparent Cohort Method, Reconstructed Cohort Method and
True Cohort Method have been discussed and indicators computed at the state and
all‑India level. Similarly
inequalities in the system, if any, can be detected and disadvantage group(s)
be identified with the help of indicators of efficiency. The last set of questions relates to
resources provided to education and how they contribute to the quality of
educational services and whether resources being used in the most effective way
possible, all of which answered efficiently, if indicators for disaggregated
target groups are available. Time Utilisation Rate, Space Utilisation Rate,
indicator of average audience in a class etc. are discussed under the group of
quality of educational services and utilisation indicators. To understand
what an indicator is and other questions of similar nature, let us first define
an indicator itself. An indicator is
that which points out or directs attention to something (Oxford
Dictionary). According to Jonstone
(1981), indicator should be something giving a broad indication of the state of
the situation being investigated. The
most common use of indicators is to examine the relative state of development
of different systems accomplished over a period of time in a specified field of
human concern (Prakash, Mehta and Zaidi, 1995). For example, primary enrolment of two districts do not produce
any information but the same, if linked to corresponding age‑specific
population, can be used to compare the status of primary education. In our day‑to‑day
life we also come across various indicators which can be classified into three
broad categories, namely, input, process and output indicators. Various process control machines, such as, videocassette
recorder, automatic milk booths and automatic weighing machines are some of the
examples of these indicators. However,
in the field of education, the classification of indicators under different
categories is not an easy task. Generally, we view education as a system, which
receives inputs in the form of new entrants, transforms these inputs through
certain internal processes, and finally yields certain outputs in the form of
graduates. The output from a given cycle of education is defined as those
students who complete the cycle successfully and the input used up in the
processes of education are measured in terms of student years. These indicators can further be classified
into four categories, namely, indicators of Size or Quantity, Equity,
Efficiency and Quality, some of which are presented in Box 1. Before the concept and definition of a variety of
indicators is presented, first the basic terms like, primary and secondary
data, stage and institution‑wise data and stock and flow statistics is
differentiated. (i) Primary and Secondary Data When information is first time collected, it is termed as
primary data otherwise it is known as secondary data. Primary data is generally
scattered in files, registers and
records so as to collect it either
from the concerned institutions or
even can be collected from
the sampling unit, such as,
a teacher, school and student. The
primary data is generally termed as raw which has no use to planners and
decision making authorities, as it do not serve as a tool of decision support system. The information thus collected is processed,
analysed and tabulated with the help of statistical indicators, so that it
becomes derived information. Simple
statistics, such as, averages, index numbers and growth rates can be used to
generate derived data. The derived information
in the form of indicators can also be used to analyse present status of
educational facilities and its utilisation.
At the micro level, just before beginning of an academic session,
village survey is conducted. Generally,
primary information on number of children in a specific age group and those who
are out‑of‑school is collected which is an example of primary data.
On the other hand secondary data generally lie in publications, which is
readily available for use. Literacy
rates during 1901‑91 that can be obtained from the Census publications is
an example of secondary data. (ii) Cross-sectional and Time‑Series Data Generally two types of statistics, namely cross‑section
and time‑series information is available. If information is available at a single point of time, it is
known as cross‑sectional data.
For example, state‑wise literacy rates and its male and female
distribution in 1991 is an example of cross‑sectional data. Cross‑sectional
data is also known as stock statistics.
Stock statistics do not have flow of information and whatever is
available that restrict to only a single point of time. On the other hand, information available on
more than two points of time is known as time‑series information, which
is also known as flow statistics. In
flow statistics, there is a flow of information from one time period to another
time period. State‑wise number of teachers during 1984‑85 to 1994‑95
is an example of time‑series data.
Similarly, grade‑wise enrolment in 1991 is an example of stock
statistics but if the same is also available for 1992, it becomes flow
statistics. While analysing educational
development, both types of statistics is needed. For projecting enrolment, we need enrolment over a period of time
whereas for analysing present status of educational development, cross‑sectional
data is required. (iii) Institution and Stage‑wise Data The third type of statistics generally we deal with is
institution‑wise and stage‑wise information both of which can be
cross‑sectional and/or time‑series in nature. For example, stage‑wise enrolment at
the primary level includes all children those who are currently in primary
classes irrespective of schools. Thus, while collecting stage‑wise
information, enrolment irrespective of schools is considered. This means that
primary stage enrolment includes enrolment in primary, middle, high and
secondary schools. Otherwise, if
consider enrolment in a particular type of school, it is termed as institution‑wise
enrolment. Thus, enrolment in primary
classes in primary schools is an example of institution‑wise data. In fact, a large number of children are in
primary classes who are otherwise not in primary schools but are in middle and
other higher levels of school education. Box 2 presents educational pattern in
different States & UTs, which reveals that two types of patterns are in
existence. In some states, primary level consists of Grades I‑V but in
other states, it is Grades I‑IV.
Similar is the case with middle and secondary levels of education. However irrespective of state patterns, the
data disseminated in case of most of the publications covered Grades I‑V
at the primary and VI‑VIII at the middle level.
Note :
All other States & UTs have Grades I‑V and VI‑VIII corresponding to Primary and Middle levels
of education. Source : Annual Report: 1994‑95, MHRD, New
Delhi. INDICATORS OF ACCESS (COVERAGE) In order to know whether the existing schooling
facilities are equally available to
clientele population/area/region or not, indicators of access are
used. These indicators are also used to
know whether schooling facilities are adequately utilised or not, because
availability of school within a habitation or a walking distance need not
guarantee that the entire clientele is utilising the facilities. While analysing accessibility, a number of
indicators, such as, distance from the house, mode of travel and time need to
reach schools are generally been used.
While analysing, distance to travel to reach school, norms prescribed in
policy can always be used. Generally, a
primary school is supposed to be available within one kilometer from the
habitation and a middle school within three kilometers. In India, habitations are treated as lowest
unit of planning where schooling facilities should be available. Habitations are also known as cluster, which
are below village level consisting of about ten houses. Thus, number of habitations having primary
schooling facilities within a habitation and/or a walking distance is
considered as an indicator of access, which if links to rural population, may
generate more meaningful information.
Thus, the second indicator of access one should consider is percentage
of rural population served by the schooling facilities. For example about 94 percent of the total
habitations in the country had schooling facilities either within the
habitation or a walking distance of one kilometer which means that only six
percent habitations were out of reach of schooling facilities. Similarly, about 95 per cent of the total
population is being served by the schooling facilities which means that only a
small segment of population is not accessible to schooling facilities. While developing plans at the micro level,
the two indicators presented above should be computed separately for all of its
sub-units. The identification of a
habitation where schooling facilities are yet to be provided should be based on
school mapping exercises referred above. MEASURING THE EDUCATIONAL ACCESS
By measuring educational
access, we mean interaction between demand and supply. Demand and supply in education means
children of a specific age group utilising the educational facilities, which is
termed as supply. Broadly, indicators
of measuring educational access are the indicators of coverage. The following indicators of access are
discussed in the present article: (i) Admission Rate (ii) Enrolment Ratio and (iii) Transition Rate. (i) Admission Rate The first important indicator of educational access is
Admission Rate which is also known as Entry or Intake Rate. Admission rate plays an important role to
know coverage of child population (age 6’) in an education system, which is
important to both policy makers and planners.
When enrolment is analysed, we notice two types of children in Grade I
i.e. new entrants and repeaters. But while
computing the admission rate, only present members of cohort (new entrants, in
Grade I are considered and repeaters are ignored, as they are members of some
previous cohort. A cohort is simply a
group element (children) moving together from one grade to another and from one
time period to another. In some cases
we may also have new entrants in other grades too, in situation like this we
assume that their number is negligible.
The admission rate plays an important role to know status of a district
with respect to other districts of the state and can also be computed separately
for boys & girls, rural and urban areas and Scheduled Castes &
Scheduled Tribes population. The
admission rate can be used to identify educationally backward blocks &
districts, so that specific strategies are formed. As mentioned, admission rate
also plays a significant role in enrolment projections and forms the basis of
future enrolment in Grade II to VIII in subsequent years. The computation procedure of Admission Rate is presented
below: New
Entrants in Grade “I” Apparent
Admission Rate = X
100 (1) Population
of Age “6” Year New
Entrants of Age `6' in Grade "I" Age‑specific
Admission Rate = X
100 (2) Population
of Age "6" Year The admission rate presented above indicate that Apparent
Admission Rate consider new entrants in Grade I irrespective of ages which
means children above and below age `6' are
included in enrolment which may in some cases resulted into rate more
than hundred. That is why the rate is known as Gross Admission Rate which is
considered a crude indicator of access and may not present the true picture of
the coverage. If considered total
enrolment (Grade I) instead of new entrants, the corresponding rate is known is
Gross Admission Rate which again is a crude indicator. Therefore, Age‑specific Admission
Rate is computed which is considered better than the gross entry rate. Age‑specific admission rate cannot
cross hundred because of its consideration of new entrants of age `6' in Grade
I which means children of below and above age `6' are excluded from Grade I
enrolment. This rate has serious policy
implications and unless brought to hundred, the goal of UPE cannot be
realised. Apart from the admission rate
presented above, Cohort Admission Rate is last in the series which watch
movement of a particular members of a cohort over several consecutive years and
account for the member of cohort who successfully sooner or later enter school
(Kapoor, n.d.) but due to limited data
which is available on Grade I enrolment, the same cannot be computed at any
level. In 1990‑91, total enrolment in Grade I was reported
27.06 million including those of 1.23 million repeaters of previous
cohort. The population of age `6’
officially entitled to get admission in Grade I was 20.98 million. Let us first compute Gross Admission Rate by
using the following formula: Total Grade "I"
Enrolment G.A.R = X 100
(3) Population of Age "6" 27.06 million = X 100 20.98 million = 128.98
% The computation of Apparent
Admission Rate needs new entrants in Grade I which can be obtained by
subtracting repeaters from the enrolment i.e. 27.06 ‑ 1.23 = 25.83 million. 25.83
million Thus, Apparent
Admission Rate = X
100 20.98
million = 123.10 % . The next rate, we compute
below is Age‑specific Admission Rate which requires new entrants of age
`6' in Grade I which is readily not available from any of the regular
sources. If we assume, 19.23 million
children in Grade I of age `6', then
the Age‑specific Admission Rate is computed as follows: 19.23 = X 100 20.98 = 91.66
% which indicates that about
92 per cent population of age‑6 were admitted in schools or a little more
than 8 per cent were otherwise out‑of‑school in the year 1990‑91. For some of the other cohorts, admission
rate at the all‑India level is computed which is presented in Table 1
(Mehta 1993a & 1995a). The table
reveals that a large number of children enter education system every year but
it remains to see how many of them retain in the system. Further, it has been noticed that a large
number of over‑age and under‑age children are also included in
Grade I enrolment which makes the statistic more than hundred. Due to limitations in data, the net
admission rate presented above couldn't be computed. Enrolment Ratio is the next
indicator of coverage that is presented below. Table 1 Apparent Admission Rate: All India (1984‑85 to 1990‑91)
(Figures in Percentage)
Note :
Due to over‑age and under‑age children, the rate comes
out more than 100 per cent. Source :
Mehta, Arun C. (1995a). (ii)
Enrolment Ratio: Concept, Definitions and Limitations Enrolment Ratio is simply division of enrolment by population, which gives extent to which the education system is meeting the needs of child population. Two questions may crop‑up, first enrolment of which level and second, population of what age group. Before we present definition of enrolment ratio, let us first examine the position of different States & UTs with reference to enrolment ratio at primary and middle levels of education. It has been observed that in many of our states, the enrolment ratio at the primary level is more than 100 per cent (currently 105 per cent at the national level, Table 2) and on the other hand in some states like Bihar (76%), Rajasthan (91%) and Uttar Pradesh (89%); the enrolment ratio is less than hundred. Further, it has been observed that at the middle level, except for Himachal Pradesh, Kerala, Mizoram, Lakshadweep, Pondicherry and Tamil Nadu, none of the states have enrolment ratio more than hundred per cent which shows the quantum of drop‑outs from one stage to another and incidence of over‑age and under‑age children. It has also been noticed that in some of the smaller States & UTs, such as, Goa, Dadar and Nagar Haveli, Manipur, Mizoram, Sikkim, Lakshadweep and Pondicherry where the base population (age‑specific) is small, only slight over‑reporting of enrolment and over‑age and under‑age children dramatically change the enrolment ratio (Table 3). In orde | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||