5.1 The EFA indicators
Within the dakar Framework of Action, the six global EFA goals are:
- Expanding and improving comprehensive early childhood care and education, especially for the most vulnerable and disadvantaged children.
- Ensuring that by 2015 all children, particularly girls, children in difficult circumstances and those belonging to ethnic minorities, have access to and complete free and compulsory primary education of good quality.
- Ensuring that the learning needs of all young people and adults are met through equitable access to appropriate learning and life skills programs.
- Achieving a 50 per cent improvement in levels of adult literacy by 2015, especially for women, and equitable access to basic and continuing education for all adults.
- Eliminating gender disparities in primary and secondary education by 2005, and achieving gender equality in education by 2015, with a focus on ensuring girls’ full and equal access to and achievement in basic education of good quality.
- Improving all aspects of the quality of education and ensuring excellence of all so that recognized and measurable learning outcomes are achieved by all, especially in literacy, numeracy and essential life skills.
The six EFA goals are about ensuring all persons have full access and opportunity to participate in basic education of good quality, so they can acquire the literacy and life skills they need for a decent living and learning throughout life. The EFA goals place special emphasis on helping disadvantaged population groups such as girls and children of poor families, ethnic, linguistic and cultural minorities, those who live in remote areas, with disabilities, and people from other vulnerable population groups to fully participate in and benefit from education. This is called ‘Reaching the unreached’.
This Module: Module A3, mainly covers those EFA indicators that are of particular relevance to school managers and education officers in districts and local areas, and indicators that can be used at provincial and central levels. The main purpose is to help all of them to effectively monitor EFA and man- age education at all levels of the education administration, by making maximum use of the data and information available in the school records and school census questionnaire as described in Modules A1 and A2. Such use will also contribute to informing key education stakeholders in the local areas and strengthening informed decision-making and accountability.
5.2 Key EFA indicators
As can be seen in the list of key EFA indicators in Annex i, and in the UNESCO institute for Statistics website, there are many internationally recommended EFA indicators. A summary of key EFA indicators for monitoring each of the six EFA goals is provided in Table 1. Those indicators marked with an ‘*’ relate to data which are available in school records and data reported in the school census questionnaire. These are described in Modules A1 and A2.
example 3 presents a typical methodological description of EFA indicators. This helps the reader to understand, correctly calculate and interpret each indicator. More complete methodological descriptions of each of these indicators can be found on the UIS website (See http://www.uis.unesco.org) and the ‘Guidelines for EFA Monitoring, Evaluation and Assessment: Identifying and Reaching the Unreached’.
As shown in example 3, these descriptions provide essential information about each indicator’s:
- Method and formula of calculation
- Required data
- Possible data sources
- Disaggregation for analysis of disparities
- Quality standards
- Limitations and constraints
The reader may notice that besides primary education, the six EFA goals also cover other levels and forms of education, plus gender equality and quality of education. Many of the concepts and monitoring approaches presented in this series of training modules, may be applied to other types of educational institutions and programmes. For example, a number of the indicators listed above for each of the six EFA goals, such as PTR, dropout rate, and completion rate can also be applied to early child- hood care and education centres, secondary schools, technical/vocational training, and adult literacy/ continuing education/lifelong learning centres and programmes.
Note that most of the EFA listed indicators marked with an ‘*’ in Table 1 can be used for comparisons between schools, local areas, districts, provinces and regions within a country, besides international comparisons for global monitoring of EFA. Appropriate adjustments and modifications may be needed to adapt some of these indicators to different country or local context, while maintaining the concepts and classifications of education indicators above and drawing on the UNESCO methodological descriptions.
Example 3. An example of methodological description of EFA indicators
Besides the indicators listed in Table 1, the data and information that are contained in the example school records described in Module A1 and gathered through the example school census questionnaire given in Module A2, can be used to produce many other indicators for monitoring eFA and informing decision-making at the local and school level. For example, average student attendance rate can be calculated based on completed monthly class attendance sheets to compare the regularity of student participation in class. Student performance records can be analysed by class and by grade to compare learning achievement. Teacher performance evaluation reports can complement teacher qualification in appraising the quality of education by school.
In practice, the school manager or district education officer must first review the data they have available, and then review the list of EFA indicators in Table 1, to identify relevant education indicators that can be reliably calculated, interpreted and used, before proceeding to produce and use such indicators. The UNESCO methodological descriptions should be studied carefully, and accompanied by actual calculation and interpretation of the indicators so as to determine if the selected indicator can reliably and meaningfully help to monitor EFA and inform decision making at the school and local level.
Review the key EFA indicators listed above in Table 1, compare them with the indicators you normally use to monitor education in your school, district, province, or country, and talk to some key stakeholders about their experiences. Then, answer the following questions:
- How closely do the EFA indicators listed in Table 1 correspond to the education indicators you use? Which indicator(s) are in common? Which indicator(s) are different? Why?
- Which other education indicators do you think should be included in the list? Why?
- Is the format of the methodological description of indicators clear and easy to understand? What other information should be given in this format? in what way can they be improved?
5.2.1 Identifying EFA indicators based on school records and census questionnaire
The example school records and school census questionnaire presented in respectively Modules A1 and A2 offer a wide range of data that can be used either directly as indicators, or to derive other education indicators including the EFA indicators for primary education and quality of education marked with an ‘*’ in Table 1 in Section 5.2.
The structure of data in the example school records (Module A1) and school census questionnaire (Module A2) cover essentially the following four aspects of schools:
- School characteristics, school facilities and environment
School records and the school census questionnaire can be used as data sources from which we can derive a number of education indicators as described below. indicators can also be derived by combining data from the four aspects above. For example, we can review the organization of teaching- learning in school in terms of student-class ratios and percentage of students without textbooks, or the sharing of school resources among the students and teachers such as education expenditure per student, pupil-teacher ratio, classroom area per student, student-latrine ratio, etc.
5.2.2 School characteristics, school facilities and environment
In the first part of a school census, the questionnaire usually collects information about the characteristics of the school such as its ownership, school facilities, and the kind of services offered.
The data about school ownership can be used to calculate the percentage distribution of different types of schools such as government, private, community or religious schools. This information can be used to produce a table like in example 4 below, which shows the percentage distribution of schools, students and teachers by type of school.
In example 4, more than 70 per cent of schools, students and teachers belong to the category of ‘Government schools’. ‘Government-aided private schools’ are relatively smaller in proportion (i.e. 5.5 per cent of schools) but account for almost 10 per cent of the student and teacher population, and hence are bigger schools. ‘community schools’ and ‘Religious schools’ together represent about one- fifth (i.e. 19.3 per cent) of the total number of schools, but only about 10 per cent of students and teachers, so are relatively smaller in size. These summaries give an overview of the relative sizes of different types of school, and can highlight policy issues and measures to rationalize the size of different types of schools.
Additional indicators about schools that operate shifts, multigrade classes, teaching/learning in moth- er-tongue, school meal programmes, boarding, school transportation and other affirmative actions in favour of disadvantaged or disabled children can help to understand the level and adequacy of special efforts to ‘reach the unreached’.
Example 5 below tabulates the percentage of schools that offer these services. As highlighted in the table, a higher percentage of schools offer school shifts, multi-grade classes and transportation in Regions 3 and 4. Relatively more schools in Region 4 can be seen to also provide teaching/learning in mother-tongue and boarding facilities, whereas a higher proportion of schools in Regions 1 and 5 offer school meals. Such findings may lead to further enquiries about the local demographic, geographic, economic and cultural conditions to see to what extent the children have difficulties accessing the schools, and whether the services provided are sufficient to improve their access to education. The prevalence of school meal programmes in Regions 1 and 5, for example, deserve in-depth investigation to evaluate their impact on student participation and quality of learning in school.
Data about school facilities may include information about their condition, for use to plan and organize repair work, new construction or new acquisitions at school. This information has two purposes: (a) to determine the operational capacity of the school to accommodate students and teachers; and (b) to examine if these facilities are in a condition to support present and future educational activities. in Section 7 of Module A4, there are additional concrete examples of how data about school facilities in the school records and school census questionnaire can be used to derive meaningful indicators and analysis.
Example 6 provides an overview of the state-of-repair of a school’s buildings, rooms and amenities, and the number of these facilities that are not being utilized. Similar tables can be produced at the district and higher levels by aggregating data from the schools within the area covered. Such tables can inform decisions at these higher levels to allocate budget and support the improvement of various school facilities and capacities so as to accommodate all eligible children in the local areas.
in example 6, the circled percentage distributions of facilities such as ‘% in good condition’,‘% to repair’, ‘% to replace’, and ‘% not used’ highlight problems with specific school’s facilities. They can inform decisions to prioritize and plan repair and replacement work, as well as actions the school’s managers can take to improve the utilization of school facilities. in addition, Graphs 5 and 7 in Module A4 show how such indicators can be presented in graphic form to make it easier to understand them and to make decisions.
Data about school income by source, and expenditure by type, are used to gauge the financial health of a school. Such financial data can indicate firstly the financial balance and secondly the detailed patterns of income by source and expenditure by type when calculating and analyzing their respective percentage distributions (see example 7 below).
Such analysis can point out existing gaps between school income and expenditure. The encircled percentages in example 7 highlight predominantly government funding (93 per cent of income) and 0 per cent local community contributions. Appropriate measures will also have to be taken to control major school expenditure such as construction costs and staff salaries. The overall financial deficit may help the school management board to realize the need to raise funds from the local community in order to cover the school’s funding gap.
The indicator: ‘Education expenditure per student’ is often used in education finance. it is obtained by dividing the total (or current) school expenditure by the total number of students enrolled during the same fiscal year. This indicator can be used to verify if a school has adequate finances for the number of students enrolled. By comparing education expenditure per student between schools, districts and regions, we can understand the situation and prospects with regard to education finance and existing funding gaps and anomalies. it can also be used to compare costing levels among different regions and local areas, and to highlight changes in expenditure patterns over time. Governments can use comparisons based on this indicator to take actions to ensure all schools have adequate financing to achieve local EFA goals.
Example 8 demonstrates how the indicator ‘education expenditure per student’ can be used to com- pare education expenditure in five primary schools for a period of nine years between 2000 and 2009. The figures for the year 2000 range from a low of 255 rupees in charati School to a high of 415 rupees in Patgaon School, with an average of 329 rupees. This average rose by an average of 4.1 per cent per year to 472 rupees in 2009, and the education expenditure per student changed to a low of 335 rupees in Ramdia School and a high of 610 rupees in Savar School. during the same period from the year 2000 to 2009, we can see the education expenditure per student increased by only 0.9 per cent per year in Patgaon School, whereas the Savar School almost doubled its per student expenditure to 610, with an average increase of 7.1 per cent per year.
When financial data from the schools are combined with those from the central, provincial, district and local education administrations, as well as from other educational institutions and programmes, the resulting information about national public expenditure on education can allow us to derive the EFA indicators no. 5, 21 and 46 listed in Section 4.1 above.
The quality and number of teachers influence how children participate in school and affect their learn- ing outcomes. The data about teachers and students in school records and those given in response to the school census questionnaire can in the first place be used to calculate pupil-teacher ratios (PTR), not only for the school as a whole but also by class and by grade so as to identify classes with dis- proportionate PTR. These PTRs can then be compared with national norms so as to identify schools, grades and classes that need more teachers to serve the existing student population.202
Indicators about teachers’ academic qualifications and teacher training can be derived from information in individual teacher records. Indicators about the quality of teachers can include: the percentage distribution of teachers by highest academic qualification; and percentage of teachers who have received pre-service and/or in-service teacher training. When compared against existing national norms which define the minimum qualification required of teachers, these indicators can inform about the share of under-qualified and untrained teachers so that measures can be taken to upgrade their competencies and to train and recruit more qualified teachers.
Employment status of teachers by type of contract (e.g. permanent, contractual or temporary) may affect the motivation of teachers and the quality of teaching they provide. By calculating the percentage distribution of teachers by contract type, we can study their likely impact upon quality of education. Of the 119 teachers in Banpong district in example 9, 60.9 per cent of female teachers are permanent teaching staff compared to only 49.1 per cent of male teachers. example 9 also shows high proportions of teachers are employed on contractual, probationary or temporary contracts, with noticeable gender differences. These indicate a number of issues in school personnel management in this district which need to be addressed by means of appropriate policies and actions such as increasing the share of permanent teachers and improving the gender balance.
Additional indicators of teacher quality can be derived from their performance evaluation results. This indicator can be produced if such performance evaluation is organized systematically for each teacher in the schools. example 21 in Module A5 shows how the scores obtained for individual teacher performance attributes can be used in practice to indicate teacher quality.
Students are the direct beneficiaries of education. data about students in school records or gathered through the school census questionnaire can be used to calculate many key indicators relating to students’ access, participation, completion, learning achievement and gender equality in education.
Percentage of students by gender, age and grade
A first step in producing indicators about students is getting to know the characteristics of the student population in school. information about students’ age, grade and sex, which is collected in the school census questionnaire, can be used to calculate the percentage distributions of students by gender, age (or age-group) and grade.27 Similar to example 14 in Module A1, the age distribution of enrolment for a specific grade can be calculated by sex as shown in example 10 below.
The above example illustrates how we can use simple data about enrolment by age in a specific grade in school to calculate percentages which help us to understand the situation in new ways. in example 10, if the official age for students in Grade 4 is nine years old (see shaded column in the middle), we can see that 53.8 per cent of the students in Grade 4 at Baan Yai Primary School are girls and hence by deduction 46.2 per cent are boys. Out of the girls, two thirds (66.7%) are of the official age for Grade 4, while only half of the boys (50%) are of the official age. Of the 21 girls in Grade 4, 3 girls (14.3% among girls) are under-aged at eight years old, as compared to 1 boy (5.6% among boys). Out of 18 boys in Grade 4, eight boys (44.4%) were older than nine years of age, compared to four girls out of a total of 21 girls (19.1%).
In a similar way, we can analyse student enrolments by ethnic, linguistic and religious groupings to reveal patterns of participation and to identify factors that may limit some children’s access to education. By calculating percentage distributions of students by type of disability or by family income, we can identify the proportion of such disadvantaged students to study the extent to which they are included in the school as compared to the proportions they represent in the local population. We can use this information to examine how best to include them in education.
In addition to percentage distributions, we can use the data about students by gender, age and grade to calculate key indicators about access to education and participation in primary school such as:
- Gross enrolment ratio (GER)
- Net enrolment ratio (NER)
- Age-specific enrolment ratios (ASER)
As explained in the UNESCO methodological descriptions and Annex 2 of this Module, we can obtain various enrolment ratios by dividing the number of students who exhibit a certain characteristic by the corresponding school-age population so as to indicate the percentage of the eligible population who have access to and participate in school. The number of school-age children who are not enrolled in school can either be determined by subtracting those enrolled from the corresponding school age population, or estimated from net enrolment ratios or age-specific enrolment ratios. Such numbers can be further verified in the local area through information from students and teachers fol- lowed by home visits to find out about the causes of non-enrolment.
The percentage distribution of students in terms of the amount of time required to travel from home to school canindicate the degree of difficulty for children to attend school. Example17 in Section5.2 of module A4 demonstrates how to present and analyse such data. We can use the findings to rationalize the location of schools in order to ensure there are schools within easy reach of school-age children, and to organize transportation and/or boarding facilities for those students who live far away.
Repeaters and drop-outs
In each grade, there may be students who have been promoted from a lower grade to their present, higher grade, who have dropped out of school, or who are repeating the same grade as the previous year. it is important to know the numbers of each so that the following indicators of internal efficiency can be calculated:
- Percentage of repeaters by grade
- Percentage of drop-outs by grade
- Promotion rate
- Repetition rate
- Dropout rate
The concept behind these indicators, and the method to calculate them are presented in Section 5.4 in Module A4 and Annex 3. We can calculate similar indicators about the percentage of in-transfers from other schools, and students who dropped out the previous year but who have re-entered the school this year. These indicators describe what happened to the children during their studies as they progressed through the grades in school, and the internal efficiency of the school.
We can calculate gross intake rate (GIR) and net intake rate (NIR) indicators about first-time entrants to Grade 1 by gender and age. To calculate these ratios, we use the same method as for the gross enrolment ratios (GER) and net enrolment ratios (neR), but this time for new entrants and school-entrance age population. Before calculating these rates, one must make sure that repeaters in Grade 1 and in-transfers into Grade 1 from other schools are not included in the number of new entrants. The net intake rate (NIR) can be used to estimate the number of children who are of the official school entrance age but who are not enrolled, so that the school can reach them through special enrolment drives.
A useful EFA indicator is the number and percentage of new entrants to Grade 1 who have previously received some kind of organized early childhood care and education (ecce). We can calculate this indicator by extracting data from the student records about new entrants’ previous experiences in childcare programmes, kindergarten or pre-school, then tallying and summarizing their numbers. This indicator can help to assess the level of ecce new students received to prepare them for entering primary school. The percentage of those who have not previously attended ecce can inform deci- sions to provide special assistance to them after they enter primary school, as well as to expand ecce provisions for future new entrants.
Examination pass rates and completion rates
Based on data about the number of students who successfully passed the final examination in the previous school year, we can calculate the indicator of pass rates by grade and gender by divid- ing the number of students who passed by the number of students enrolled in the corresponding grade last year. We can use this indicator to gauge the performance of the students by school, grade and class. For the final grade in primary school, the ‘completion rate’ indicator can be calcu- lated in a similar way.
The score obtained by individual students in different subjects can be presented in a summary list like the one shown in example 12 in Module A1, to rank and compares students’ learning achievement.33 We can apply the same methods to scores obtained during special learning achievement tests.
Using the data in Questions 20 and 21 of the example school census questionnaire in Module A2, average student-class ratios by grade can be calculated to indirectly assess the quality of teaching/ learning and to better manage class-size in the school.
Based on the discussions in Section 5.3, review the data available to you in the school records or in the school census questionnaire, and then answer the following questions:
- Which education indicators do you think can be produced using the data available to you? How do they correspond to the eFA indicators in Table 1?
- What kind of difficulties can occur when trying to produce these indicators?
- What do you think can be done in order to address these difficulties?
- Which do you think are the remaining gaps in indicators for monitoring education in particular eFA?