School Community Integration Pilot Project - Department of Education

Province of the 

EASTERN CAPE 

DEPARTMENT OF EDUCATION 

A Comparative Analysis of Education 

Expenditure in Eastern Cape Schools 

Research Report commissioned by the Corporate Support 

Branch of the Eastern Cape Department of Education 

November 2004 

The DFID funded Imbewu Programme of the ECED wishes to place on 

record gratitude to Philip Cole for providing a quality product: 

A Comparative Analysis of Education Expenditure in Eastern Cape 

Schools

A COMPARATIVE ANALYSIS OF 

EDUCATION EXPENDITURE IN 

EASTERN CAPE SCHOOLS 

Prepared for 

THE EASTERN CAPE DEPARTMENT OF 

EDUCATION 

And 

THE IMBEWU PROGRAMME 

By 

PHILIP COLE 

November 2004

CONTENTS 

SUMMARY 

i 

1. INTRODUCTION 1 

2. NATIONAL AND PROVINCIAL FUNDING FOR EDUCATION 1 

2.1. The national funding framework for education 1 

2.1.1. The Equitable Share Formula 1 

2.1.2. The education component of the ESF 3 

2.1.3. Population trends from the census 3 

2.1.4. Conclusions from the national funding framework 4 

2.2. Provincial trends in education expenditure 5 

2.2.1. Overall provincial funding issues 5 

2.2.2. Trends in provincial education expenditure 7 

2.2.3. Conclusions from provincial trends in education expenditure 12 

3. ANALYSING PUBLIC SCHOOL EDUCATION 13 

3.1. Comparing public school education between provinces 13 

3.2. Public school education in the Eastern Cape 16 

3.2.1. Levels of public schools in the Eastern Cape 16 

3.2.2. Types of public schools in the Eastern Cape 17 

3.2.3. Public schools by education district 21 

3.2.4. Public schools by size 22 

3.2.5. Out-of-age learners and efficiency 24 

3.2.6. Conclusions on public school education in the Eastern Cape 26 

4. PUBLIC SCHOOL EXPENDITURE IN THE EASTERN CAPE 27 

4.1. Public school expenditure – recent performance 27 

4.2. Personnel expenditure 28 

4.2.1. The post-distribution model for educators 29 

4.2.2. Impact of educator post distribution in the Eastern Cape 30 

4.2.3. Non-educator personnel in public schools 31 

4.3. Non-personnel non-capital expenditure 32 

4.3.1. Learner support materials 32 

4.3.2. Other recurrent support to schools 33

4.4. School Infrastructure 34 

4.4.1. Infrastructure backlogs 34 

4.4.2. Norms and standards for school planning 35 

5. IMPROVING QUALITY IN EASTERN CAPE SCHOOLS 36 

5.1. Realignment and quality 36 

5.2. Potential criteria for realignment 40 

6. SCENARIOS FOR POST PROVISIONING 41 

6.1. Scenario 1: No Combined Schools or Small Secondary Schools 42 

6.2. Scenario 2: The Current Establishment Of 67,074 44 

6.3. Scenario 3: A New Establishment Of 61,431 46 

7. CONCLUSIONS AND RECOMMENDATIONS 48 

7.1. Conclusions 48 

7.2. Recommendations 51 

REFERENCES 53 

APPENDIX 1: TERMS OF REFERENCE 54 

APPENDIX 2: POST DISTRIBUTION MODEL 56

A comparative analysis of education expenditure in Eastern Cape schools – November 2004 

SUMMARY 

A rapid review of education spending completed in March 2004 found that the 

Department had been able to devote increased funding to school education. This 

comparative study of education expenditure in schools conducts a more detailed 

analysis examining the main factors driving and affecting spending, especially 

personnel expenditure. Findings from the study are set out in a number of areas. 

National funding for education 

The Equitable Share Formula (ESF) determines the bulk of national allocations to 

the provinces, including allocations to education. Trends in population and related 

factors, such as school enrolment, are the main drivers behind the allocation of 85% 

of funding through the ESF. The gradually declining share of the Eastern Cape in 

total population is therefore leading to a steadily declining share in the national 

allocation to provinces. If the 1999/00 equitable share had still been in place the 

province would be receiving R32,8 billion in 2006/07, an increase of R1,9 billion (6%) 

on projected total national funding. 

The education component of the ESF gives a high weighting to school age 

population. The high proportions of out-of-age learners in the Eastern Cape (70%) 

caused by high rates of repetition are reducing the share of education funding in the 

ESF even more rapidly than for total national allocations under the formula. The 

Eastern Cape’s share in the education component is projected to fall from 18,4% to 

17,3% from 2003/04 to 2006/07. 

The province must engage more vigorously and proactively with debates over 

national funding and the equitable share to make the case for a greater allocation of 

resources to poorer provinces. Stronger capacity is also needed in provincial fiscal 

policy and planning to engage with these issues. 

Provincial funding for education 

Provinces are responsible for their own budget allocations and can prioritise funds 

where they wish. Factors such as lack of access to own revenue, inherited large 

establishments of personnel and the persistence of large infrastructure backlogs 

however effectively limit the flexibility of poorer provinces to prioritise funds. 

Education expenditure in the Eastern Cape fell in real terms in the period 1997/98 to 

2000/01 as limited funding was devoted to repaying debt and personnel backlogs. 

Non-personnel resources were especially limited during this period leading to very 

limited expenditure on teaching and learning materials in schools. Expenditure 

increased rapidly in real terms from 2000/01 onwards enabling the province to 

recover from the crisis of the late 1990s and to increase the share of its budget 

devoted to non-personnel. There is however pressure on the education budget from: 

• Growth in expenditure on social grants has been even higher than in 

education over the same period. This trend will continue for the medium term 

and is limiting the scope of the province to continue the growth in allocations 

to education of recent years. 

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• Even allowing for this factor, the province has responded with a sharp 

reduction in the relative allocation to education over the last three years, 

greater than in any other province. 

• While education expenditure has grown in all provinces at rates significantly 

higher than inflation in recent years, this rate of growth is not expected to 

continue. The Eastern Cape is projecting only small real increases in the 

education budget over the current MTEF period 2004/05 to 2006/07. 

High real growth in education expenditure since 2000/01 has enabled release of 

funding for non-personnel items vital to education. This growth is however relatively 

recent and follows a period of financial crisis from 1997/98 to 2000/01 when nonpersonnel 

funding was virtually non-existent. The crucial area of non-personnel noncapital 

(NPNC) expenditure that is used for learner materials and school services is 

still below average and well below the draft national per learner target of R500 per 

learner, although NPNC funding has been increasing in recent years. The province 

however faces the challenge of keeping and developing these gains in an 

environment of far greater funding pressures, currently and over the next few years. 

COMPARING PUBLIC SCHOOL EDUCATION BETWEEN THE PROVINCES 

The table below compares public school education between the various provinces. 

Table: Public school education indicators by province 2000 and 2001 

Province Learners Educators Schools LER LSR LCR 

Eastern Cape 2,027,791 60,882 6,056 33.3 335 43 

Free State 703,912 22,403 2,396 31.4 294 33 

Gauteng 1,444,861 43,761 1,900 33.0 760 33 

Kwazulu-Natal 2,661,508 71,628 5,608 37.2 475 40 

Limpopo 1,793,788 56,491 4,446 31.8 403 40 

Mpumalanga 894,284 24,245 1,864 36.9 480 48 

Northern Cape 194,377 6,183 459 31.4 423 26 

North West 883,567 28,743 2,271 30.7 389 34 

Western Cape 888,888 25,008 1,474 35.5 603 31 

SOUTH AFRICA 11,492,976 339,344 26,474 33.9 434 38 

Note: Learner:educator ratio (LER), learner:school ratio (LSR) and learner:classroom ratio (LCR). 

A good school system should balance the different inputs into the education process. 

A good target for resource provision is one educator teaching one class in one 

classroom, recognising that actual practice is far from this in many schools. The LER 

ideally should be no more than 20% lower than the LCR. Variation between the LER 

and LCR greater than this shows either lack of classrooms, or relative overprovision 

of educators in relation to other resources, or in some cases the existence of both 

problems. This is clearly the case in the Eastern Cape and other poorer provinces. 

The indicators show that many provinces have large numbers of small schools, 

especially the Free State and the Eastern Cape. Small schools have advantages of a 

generally low LER and a more ‘human’ scale. They are also unavoidable in many 

communities, especially in sparsely populated rural areas. Large numbers of small 

schools however represent an unbalanced use of resources by concentrating school 

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infrastructure and educators on relatively small numbers of learners. Larger schools 

‘cluster’ educators, classrooms and learners more effectively, achieving economies 

of scale, enabling better allocation of resources, and managing educator utilisation to 

maximise the time spent teaching in the classroom. This is especially true for 

secondary schools where the number of learning areas increases and the complexity 

of arranging the school timetable follows correspondingly. 

While average school size and classroom provision is strongly related to the relative 

poverty of a province, there is no clear relationship between relative poverty and 

educator provision. The poorer provinces have a higher LCR indicating backlogs in 

classroom provision. The two wealthiest provinces of Gauteng and Western Cape 

have the largest average school size due to the highly urban nature of their 

schooling systems. Many of the poorer provinces with former homeland areas have 

low LSRs due to large numbers of relatively small rural schools. The LER seems 

however to have no clear correlation to relative wealth or poverty. The Department of 

Education has noted that the ‘LER does not appear to be strongly linked to the fiscal 

advantage enjoyed by the province. The Western Cape, for example, is an 

advantaged province, yet its overall LER is higher than that of the Eastern Cape’. 

There is also clearly a strong correlation between school size and educator 

provisioning. Generally the provinces with a low average school size, indicating 

relatively larger numbers of small schools, have a lower LER. This is because the 

1998 post provisioning policy favours small schools somewhat. The LER for nonsmall, 

or large, schools will logically be somewhat higher than the overall ratio. 

Provinces have clearly made very different decisions in post provisioning, with some 

provinces have made a strategic choice to allow a slightly higher overall 

learner:educator ratio and to devote resources to other priorities in education. 

PUBLIC SCHOOL EDUCATION IN THE EASTERN CAPE 

The Eastern Cape has inherited different schooling systems from the apartheid era 

education departments. Many of the challenges created by these systems have still 

to be effectively addressed. Specific issues that need to be highlighted are: 

• Combined schools and associated secondary schools form the largest single 

sub-system in the province. One of the defining features of this sub-system is 

mismatched levels of provisioning. While educator provisioning is adequate in 

most districts, with the possible exception of Pondoland, classroom backlogs 

are pervasive in the former Transkei. 

• The greatest numbers of educators in small schools is, in declining order of 

size, in combined schools, full primary schools, senior secondary schools, 

junior primary schools and farm schools. Large numbers of small schools in 

these types of schools create pressure for a large establishment through the 

prevalent low learner:educator ratios. 

• There is a wide variation in educator provisioning between small and large 

schools. Small schools typically show LERs in the range 20 to 25. The 

province needs to find ways to increase the average LER in small schools to 

avoid pressure to increase the educator establishment. 

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• Out-of age enrolment and repetition is very high, especially in the former 

Transkei. Out of age enrolment has a detrimental effect on national funding 

through the ESF. High repetition is also a waste of scarce resources and 

inhibits teaching and learning in the classroom through large class sizes. 

The province has chosen to target a relatively favourable LER in its educator 

provisioning over the last few years. The 2004 declared educator establishment is 

67,124, which would give an LER of 31:1 if implemented, significantly below many 

other provinces. Person-to-post matching for this establishment is currently being 

completed. A number of points need to be made in relation to educator provisioning: 

• Educator provisioning has improved greatly in many districts and is at broadly 

acceptable levels in most of the province. 

• At the same time many districts in the former Transkei continue to have 

significant classroom backlogs with LCRs greater than 40 in most districts. 

• Non-personnel non-capital (NPNC) in the Eastern Cape is below average and 

well below the draft national target of R500 per capita. 

The Eastern Cape has attached a lower priority to addressing the classroom backlog 

or to providing learner materials in the classroom and school services, in comparison 

to relatively favourable levels of educator provisioning. Most of the districts in the 

former Transkei have a more favourable learner:educator ratio than the Western 

Cape. With relative cuts in the provincial allocation to education and the current and 

future funding pressures, there is a clear case for reprioritising resources. 

PERSONNEL EXPENDITURE AND THE POST DISTRIBUTION MODEL 

The educator establishment is distributed using a computerised model, which 

calculates the number of ‘weighted learners’ in each school. The report sets out how 

weighted learner numbers are calculated. A number of the characteristics of the 

Eastern Cape schooling system combine to increase the number of weighted 

learners calculated by the model: 

• The large number of small schools in the province each of which receives 

additional weighted learners. 

• The high number of grades covered by many schools, which endows a school 

with further additional weighted learners, and; 

• The prevalence of combined schools, which are given a further allocation of 

weighted learners. 

• Small secondary schools offering a large number of subjects produce a high 

weighted enrolment in comparison to actual enrolment. This characteristic is 

exacerbated in senior secondary schools, which are more likely to be small 

and which only cover grades 10 to 12 where the number of learning areas is 

important in determining the calculation of weighted learners. Simply put, 

small secondary schools have a small number of learners taking a large 

number of subjects producing a high weighted learner enrolment. 

It is important to realise that although the schooling system in the province produces 

a large number of weighted learners, this does not automatically lead to declaration 

of a large establishment. The size of the educator post establishment is driven by 

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both budget and the target for the overall LER. The characteristics of the schooling 

system do however lead to redistribution of posts towards small schools, combined 

schools and senior secondary schools. 

It must also be noted that a combination of significant post redistribution towards 

small schools and a post allocation often driven by a target LER means that the LER 

in large schools will always be above the average LER for the province as a whole. 

The combination of a relatively favourable LER for the province overall, the features 

of the post distribution model, and the special characteristics of the Eastern Cape 

schooling system have clearly led to significant redistribution of educator posts in 

favour of small schools and the poorer ex-homeland areas. The operation of the post 

distribution model has therefore led to greater equity in educator allocation in the 

province. The time has come however to ask if the manner in which educator post 

provisioning has been applied in practice is not now impeding the allocation of 

limited resources to equally vital priorities. 

NON-PERSONNEL NON-CAPITAL EXPENDITURE (NPNC) 

Learner support materials (LSM) are one of the most vital components of educational 

resourcing in the classroom, and often one of the most neglected areas. The Eastern 

Cape is however now meeting the norm of R100 per learner for LSM set in the 

norms and standards for schools funding (NSSF) for 2000. By 2002/03 the norm was 

met, and was exceeded by between 25% to 50% in the former Transkei districts. 

Performance is less favourable when turning to other items of recurrent support to 

schools. The province has prioritised most NPNC expenditure on LSM provision. 

Other expenditure has been directed, in order of priority, to maintenance and 

adaptation of buildings, water and electricity, catering services and school furniture, 

which received significant funding in 2003/04 for the first time in recent years. Very 

little was spent on learning and teaching equipment, a vital area in the classroom. 

There are wide variations between provinces in school allocations under the NSSF, 

with far lower allocations in the poorer provinces. The Department of Education has 

proposed a single national school allocation for each quintile of schools, ranked by 

poverty. The average targets are R475 for 2005, R499 for 2006 and R524 for 2007. 

The Eastern Cape, and probably many provinces, is well below these targets. NPNC 

expenditure per capita in 2003/04 was R224. With a learner enrolment of close to 

two million the province will need to target a NPNC budget of close to R1 billion in 

the next few years to provide adequate recurrent school funding. The province will 

also need to move beyond LSM to target other recurrent support to schools. 

SCHOOL INFRASTRUCTURE 

The Physical Planning Directorate are targeting the elimination of all backlogs by 

2010 and have recently drafted a five year Infrastructure Implementation Plan 2005- 

10 to meet this target. The plan targets total capital expenditure in all education 

institutions of between R600 to R650 million a year from 2005/06 to 2008/09, falling 

to R283 million in 2009/10 as backlogs are eliminated. 

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The report sets out a rough estimate of the cost of eliminating the backlogs at current 

prices, totalling R2,443 million. This does not include the cost of building laboratories 

and media centres. Eliminating the backlog over a longer ten year period would 

therefore cost perhaps R300 million a year at current prices. 

Expenditure on school infrastructure has risen rapidly in recent years to exceed 

these levels, from R187 million in 2001/02 to R400 million in 2003/04. The Eastern 

Cape has access to further off-budget funding from donors that supplements these 

resources. A maintenance and adaptation budget has reached significant levels for 

the first time with expenditure rising from R11 million in 2001/02 to R37 million in 

2003/04, and projected to rise to R53 million by 2006/07. 

It is vital to have clearly defined criteria for school infrastructure and strong 

processes for school opening, closure and amalgamation. Communities 

understandably want a school close by, preferably in their immediate locality. In the 

context of the former homeland areas, with large numbers of small villages, the 

tendency for each community to have a school is one of the main pressures in the 

province creating small schools. 

IMPROVING QUALITY IN EASTERN CAPE SCHOOLS 

There is a strong case for realigning the public school system to improve quality by 

implementing a full primary (grades R to 7) and full secondary (grades 8 to 12) 

system throughout the province. A number of educational benefits would result from 

this realignment of the schooling system. 

• The change of combined schools to primary schools would reduce the very 

wide age spread within these schools, an especially important consideration 

with the continued high prevalence of over aged learners in schools. This 

would make management of these schools easier and contribute to social 

cohesion within the school. The quality of education in the new full primary 

schools in Transkei would increase over time. 

• The change of combined schools to secondary schools would also reduce 

pressure on classroom space in a system that already suffers from acute 

over-crowding and backlogs. 7 rather than 9 grades would be using the same 

number of classrooms. 

• In senior secondary schools currently, educators are teaching 10 to 12 

subjects over only three grades in schools of acute classroom shortage. The 

practical result is often that each grade is taught one subject at a time in an 

overcrowded classroom, especially in small schools, with the educator moving 

between classrooms for different subjects. As the educator is only teaching a 

subject to three grades, high proportions of educator time are wasted through 

a low period load. This explains the seemingly paradoxical findings that LERs 

in senior secondary schools are very low, while educators report teaching 

very large class sizes of 50 or more in secondary schools. 

• Moving to a full secondary school system would therefore enable much better 

utilisation of educators in the former Transkei. Larger secondary schools 

would be able to ‘cluster’ resources, offering a wider subject choice and 

achieving economies of scale in providing much needed education resources 

such as computer labs, laboratories and media centres. Educators would be 

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more effective and able to spend higher proportions of their time in the 

classroom. The quality of education in former Transkei secondary schools 

would, over time, increase tremendously. 

• Clustering resources in larger high schools will also support a number of 

major policy initiatives. The introduction of the FET curriculum from 2006 in 

grades 10 to 12, geared to modern social and economic needs, requires 

effective resourcing with teaching and learning materials and equipment. 

Similarly, the e-Education policy will require all schools to be using information 

and communication technologies (ICT) for learning by 2013. Resources for 

the implementation of both of these policies, which will especially impact high 

schools, can be provided and used more effectively in larger high schools. 

Realignment of the schooling system along these lines would also greatly reduce the 

pressures towards a large establishment with the following results: 

• A reduction in the required educator establishment from the current numbers 

of 64,667 in post (EMIS 10 th day return survey 2004) to 62,334 with a saving 

of 2,333 posts. Annual savings from this lower educator establishment would 

be R290 million at present, equivalent to a 44% increase in the 2004/05 nonpersonnel 

budget. These funds could be reprioritised to teaching and learning 

materials, school services or building improvements. 

• Only a minor increase would result in the overall LER for the province from 

32.2 to 33.4, as small and large schools harmonise around agree space and 

post provisioning norms. 

The classroom backlog would increase from 5,954 to 8,023 in the proposed 

realigned schooling system, due to the need to build classrooms in the expanded full 

secondary schools. An increase of 2,069 classrooms would be needed at a cost of 

R259 million. There would also be an associated though smaller infrastructure 

requirement for hostels, toilets and other buildings. This would however be a once off 

construction cost whereas post savings would be larger and would continue to 

accrue in each year. The additional cost of classroom construction would also be 

spread over multiple years and accommodated by reprioritising funding towards high 

schools within the existing rising capital budget. 

EMIS has recently prepared a study on the reorganisation of very small schools with 

enrolment less than 100, finding that 57% of schools had an adjacent school within 

5km that could provide a place to transfer learners. Clearly there is significant scope 

for better use of resources by the realignment of small schools. The study suggests 

a series of criteria for realignment of small schools: 

• Are there schools within 5km that can accommodate the small school? 

• Does the school have sufficient classrooms to accommodate new learners? 

• In what condition is the neighbouring school? 

• Can transport be provided for the learners, and if so – what will the costs be? 

• What will the social costs be when the small school closes? Will the closing of 

the school have a detrimental effect on the community at large? 

• Can the community afford not to have a school? 

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• Although there might be a school within a 5km radius, is there a physical 

boundary that prevents learners from going to school? 

The information base is increasingly in place in the Department for a systematic 

review of school location, size, infrastructure and educator provision that would 

prioritise scarce resources in viable schools to build up quality education. 

SCENARIOS FOR RESOURCE PRIORITISATION 

Three scenarios for post provisioning have been prepared calculating the cost of the 

educator establishment, and calculating available resources for NPNC and capital, 

using a computerised simulation of the post provisioning model. 

Scenario 1 simulates the impact of the proposed three year phased introduction of 

grade R-7 primary schools and grade 8-12 secondary schools, coupled with the 

closure of small secondary schools of that cannot reach an enrolment of 300 or 

more. Small primary schools are not closed, but their LER and LCR are targeted to 

rise to the space and class norms set out. The average LER would rise slightly from 

32.2 to 33.4 and the LCR would fall slightly from 39.0 to 38.4 over the three year 

period. Permanent educator numbers fall gradually from the current in post numbers 

of 64,845 in 2004/05 to a filled establishment of 62,505 in 2007/08. 

This a relatively favourable scenario, with both the size and relative proportion of the 

non-personnel non-capital budget rising to R943 million by 2007/08 and stabilizing at 

between 8% to 9% of the total public school budget. At R450, NPNC per capita rises 

to close to the national target by 2006/07. Capital expenditure would stabilise at 

R306 million in 2007/08, close to the figure needed to eliminate the backlog over a 

ten year period. 

Scenario 2 simulates the impact of a three year phased introduction of the 2004 

agreed establishment of 67,074, to which person to post matching is currently being 

completed. The average LER would fall from 32.2 to 31.0 over the three year period. 

Permanent educator numbers rise gradually from the current in post numbers of 

64,845 in 2004/05 to a filled establishment of 67,124 in 2007/08. 

This would be a damaging scenario for education over the medium term, with both 

the size and relative proportion of the non-personnel non-capital budget falling after 

2005/06 to R429 million by 2007/08, 4% of the total public school budget. Such a 

non-personnel non-capital budget would be completely insufficient to support quality 

education in the classroom through adequate provision of learner materials. NPNC 

per capita would fall to an unacceptable R206. Capital expenditure would fall to 

R139 million, insufficient to eliminate the backlog over an acceptable period. 

Scenario 3 simulates the impact of a three year phased introduction of the proposed 

2005 establishment of 61,431. The average LER would rise from 32.2 to 35.0 over 

the three year period. There would be a similar, although greater impact, to the 

structural changes proposed in scenario 1. Permanent educator numbers fall 

gradually from the current in post numbers of 64,845 in 2004/05 to a filled 

establishment of 61,431 in 2007/08. 

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This is also a favourable scenario, with both the size and relative proportion of the 

non-personnel non-capital budget rising to R1,063 million by 2007/08 and to 10% of 

the total public school budget. By 2007/08 NPNC per capita would have risen above 

the NSSF target of R500 per learner. Capital expenditure would rise to R345 million 

by 2007/08, sufficient to eliminate the backlogs over ten years. 

RECOMMENDATIONS 

Resource planning and prioritisation 

The Eastern Cape needs to take a stronger and more proactive role in discussions 

over the national funding framework and the equitable share formula, or face a 

steadily declining relative allocation of national resources to the province. This 

requires developing fiscal planning and negotiation capacity in both the provincial 

Treasury and the Department of Education. 

Under the pressure of increasing expenditure on social grants the province has 

sharply reduced relative allocations to education over the last three years, more 

rapidly than in any other province. The province needs to find ways to increase the 

proportion of expenditure on education over the next MTEF period. 

The Eastern Cape Department of Education needs to target a better balance of 

funding between personnel, capital and non-personnel non-capital funding of 

learning materials and school services. Over the next MTEF period should 

progressively implement the third scenario set out in this report, which would result 

by the end of this period 2007/08 in: 

• An educator establishment of 61,431 giving an average learner educator ratio 

of 35:1 and 83% of total expenditure on personnel. 

• A non-personnel non-capital budget of R1 063 billion meeting draft norms and 

standards targets for recurrent school funding of R500 per learner. 

• A capital budget of R345 million giving sufficient funding to eliminate school 

infrastructure backlogs by 2013 and to build additional classrooms in 

realigned full secondary schools. 

In the current climate of overdrafts and limited financial resources this requires 

significant reprioritisation of funds within the province or access to new sources of 

funding. 

Post provisioning 

The Department of Education should declare an educator post establishment of 

61,431 for 2005 based on an overall LER of 35. The new establishment should 

however be phased in over the three years 2005-07 allowing for parallel 

implementation of recommended structural changes in the public school system. 

Realignment of schools for quality education 

One of the chief goals in this realignment of schools should be to release and 

reprioritise resources for quality education. The objective should be to bring and 

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retain primary schools close to the learner, while at the same time bringing older 

learners to larger high schools, to board if necessary, and clustering resources to 

support the introduction of a high quality FET curriculum. Funding would be released 

for the learning materials necessary for quality education. 

Over the three year period 2006-08 combined, senior secondary and small 

secondary schools (less than 300 enrolment) should therefore be realigned from 

2006 onwards. Schools would realign to a full primary (grades R to 7) and full 

secondary (grades 8 to 12) system. This will entail the transfer of grade 8 and 9 

learners from combined schools to senior secondary schools during this period 

within their district. Secondary schools would be encouraged to increase their 

enrolment to at least 300 or face closure. The Department will need to prioritise the 

construction of just over 2,000 classrooms to convert senior secondary schools to full 

secondary schools during these 3 years. This can however be accommodated within 

the existing capital programme with reprioritisation of existing construction to the 

targeted schools. 

Finalise school planning criteria 

The information is present to finalise clear criteria to open new schools, close old 

schools and to amalgamate schools in the draft physical planning manual. Analysis 

of population growth or decline in communities, and the distance of learners from 

schools, is required to complete the picture. The Department should complete its 

school planning criteria in 2005 by investigating these areas. 

Learner to school matching 

In an analogous process to person to post matching the Department should conduct 

a ‘learner to school matching’ during 2005 to examine school planning and 

realignment. Building on existing EMIS work and school planning criteria a clear 

picture should be built up of: 

• Where small schools are and what are their characteristics 

• Where community populations are growing or declining and hence where 

communities are under-served or over-provided 

One of the key goals should be to identify small schools that will need to be retained, 

schools that can be amalgamated, and schools that are clearly non-viable and which 

need to be closed. The matching should be conducted in each district. 

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1. INTRODUCTION 

Since 2000/01 the Eastern Cape Department of Education has received 

progressively increasing budgets. A rapid review of education spending completed in 

March 2004 found that the Department has been able to devote increased funding to 

school education. The Department now wishes to conduct a detailed analysis of 

education spending in schools examining the main factors driving and affecting 

education spending, especially personnel expenditure. This study is the main output 

from this analysis. The terms of reference for the study are given in Appendix 1. 

2. NATIONAL AND PROVINCIAL FUNDING FOR EDUCATION 

Before analysing public school education expenditure in the Eastern Cape it is 

important to place the province in the national and provincial context. This first 

section reviews three areas in education funding: 

• the national funding framework for education driven by the equitable share 

formula. 

• A comparison of education funding and expenditure between the provinces. 

• A comparison of the main education variables between the provinces. 

2.1. The national funding framework for education 

National revenue is shared each year in the state budget between the three spheres 

of government; national, provincial and local, with provincial government receiving 

the largest share reflecting its major role in service delivery. In 2004/05 provincial 

government is receiving R181,1 billion from national, 57,3% of total government 

expenditure. National funding to the provinces is channelled through two 

mechanisms: 

• The equitable share is divided between the nine provinces by formula. It is 

unconditional and provinces can allocate it at their own discretion. It is R160,0 

billion in 2004/05 (88,3% of national funding to provinces). 

• Conditional grants are allocated for directed purposes and functions with 

provinces having no discretion on their use. Conditional grant funding is R21,2 

billion in 2004/05 (11,7% of national funding to provinces). 

2.1.1. The Equitable Share Formula 

Most national funding to the provinces is therefore allocated through the equitable 

share, which is divided between the provinces by formula. The equitable share 

formula (ESF) currently comprises seven components as follows: 

• An education component (41 per cent) based on the size of the school-age 

population (ages 5-17) and the average number of learners enrolled in 

ordinary public schools for the past three years. 

1


• A health component (19 per cent) based on the proportion of the population 

with and without access to medical aid. 

• A social security component (18 per cent) based on the estimated number of 

people entitled to social security grants weighted by a poverty index. 

• A basic component (7 per cent) derived from each province’s share of the 

total population of the country. 

• A backlog component (3 per cent) based on the distribution of infrastructure 

needs as captured in the schools register of needs, the audit of hospital 

facilities and the distribution of the rural population. 

• An economic output component (7 per cent) based on the distribution of total 

remuneration in the country. 

• An institutional component (5 per cent) divided equally among the provinces. 

As one of the poorest provinces, the Eastern Cape receives a larger share of the 

three social sector components and the backlog component, and a smaller share of 

the economic activity component. Overall the Eastern Cape is targeted to receive 

16,6% of the equitable share. The current distribution of each component and the 

target shares for each province is set out in the table below. 

TTable 1: Distributing the equitable share, percentages by province 

Education Health Social Basic Economic Institu- Backlog Target 

welfare share activity tional shares 

Weighting 41.0 19.0 18.0 7.0 7.0 5.0 3.0 100.0 

Eastern Cape 17.3 17.0 19.6 14.4 8.1 11.1 20.7 16.6 

Free State 6.0 6.5 7.1 6.0 5.4 11.1 5.6 6.5 

Gauteng 13.6 14.7 13.9 19.7 33.4 11.1 5.0 15.3 

KwaZulu-Natal 22.8 21.7 19.6 21.0 16.5 11.1 23.0 20.9 

Limpopo 15.0 13.3 13.7 11.8 6.6 11.1 22.9 13.7 

Mpumalanga 7.6 7.2 6.5 7.0 6.9 11.1 8.5 7.4 

Northern Cape 1.7 2.0 2.2 1.8 2.0 11.1 1.3 2.3 

North West 7.8 8.6 8.7 8.2 6.7 11.1 9.5 8.3 

Western Cape 8.2 8.9 8.8 10.1 14.2 11.1 3.6 9.0 

Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 

The formula has been used to distribute the equitable share since the 1997/98 

budget. It has been updated and revised twice as new data has become available, 

mostly from the 1996 and 2001 censuses. At each revision the target share of the 

Eastern Cape has fallen due to a gradually falling share of national population. The 

impact on the equitable share from each revision of the formula has been phased in, 

but the provinces’ share has gradually fallen from 17,6% in 1999/00 to 17% in 

2003/04 and the 16,6% targeted for 2006/07. The 1% reduction in the equitable 

share since 1999/00 may seem small. However, the Eastern Cape is projected to 

receive R30,9 billion from the equitable share in 2006/07. If the 1999/00 equitable 

share had still been in place the province would be receiving R32,8 billion, an 

increase of R1,9 billion (6%). 

The ESF is currently being comprehensively reviewed as part of the 2005/06 budget 

process, including consideration of issues of weighting, population and poverty 

levels. It is recognised that the formula is a relatively blunt instrument for allocating 

resources and that it should support national policy imperatives, especially in the 

social sectors. 

2


2.1.2. The education component of the ESF 

The education component of the ESF is calculated from two drivers: 

• Enrolment in public ordinary schools grades R-12, averaged for the last three 

years. 

• The size of the school age population ages 5 to 17 taken and projected from 

census data. 

The school age population is double weighted in the formula, reflecting governments’ 

desire to reduce out-of-age enrolment. The Eastern Cape’s proportion of the 

education component has fallen significantly under the impact of both a falling 

proportion of national population from the census and a relatively high proportion of 

over-aged learners. Section 3.2.5 below gives figures for out-of-age enrolment in the 

province and discusses the impact on educational efficiency. The table below shows 

the target shares used for the 2003/04 budget and the target share for 2006/07 after 

updating from the 2001 census. The Eastern Cape’s share in the education 

component is projected to fall from 18,4% to 17,3% from 2003/04 to 2006/07. 

TTable 2: Calculation of the education component 

Thousands 

2003/04 

2004 Medium-term estimates 

Weighted share Enrolment School-age Weighted target 

share 

(%) (5-17) (%) 

Weighting 1 2 

Eastern Cape 18.4 2,083 2,219 17.3 

Free State 6.3 729 760 6.0 

Gauteng 12.6 1,577 1,786 13.6 

KwaZulu-Natal 22.0 2,706 2,946 22.8 

Limpopo 15.4 1,834 1,915 15.0 

Mpumalanga 7.3 910 969 7.6 

Northern Cape 1.9 198 222 1.7 

North West 8.0 907 1,021 7.8 

Western Cape 8.0 927 1,095 8.2 

Total 100.0 11,870 12,933 100.0 

It can also be seen that the three ‘urban' provinces of Gauteng, Kwazulu-Natal and 

Western Cape are projected to benefit significantly from the revision due to new 

census data. This reflects the increasing share of the population and hence school 

enrolment in these three provinces. Issues being considered in the education 

component as part of the current ESF comprehensive review include the weighting 

between population and enrolment, whether the problem of out-of-age enrolment 

should be addressed in the formula, and ways to reflect the barriers to education 

caused by poverty and backlogs. 

2.1.3. Population trends from the census 

Census figures support the conclusion that the Eastern Cape’s share of population is 

decreasing. Census 2001 figures have now been published after adjustment for 

undercount and can be compared with the earlier 1996 census. Caution must still be 

3


used in comparing disaggregated data. Nevertheless, comparison of the two 

censuses between the provinces reveals some very firm trends. 

Table 3: Population census figures by province, 1996 & 2001 1 

Province 1996 2001 % p.a. 

Eastern Cape 6,302,525 6,436,763 0.4% 

Free State 2,633,504 2,706,775 0.6% 

Gauteng 7,348,423 8,837,178 3.8% 

Kwazulu-Natal 8,417,021 9,426,017 2.3% 

Limpopo 4,929,368 5,273,642 1.4% 

Mpumalanga 2,800,711 3,122,990 2.2% 

Northern Cape 840,321 822,727 -0.4% 

North West 3,354,825 3,669,349 1.8% 

Western Cape 3,956,875 4,524,335 2.7% 

SOUTH AFRICA 40,583,573 44,819,776 2.0% 

The Eastern Cape has the second lowest population growth rate at 0,4% per annum 

and is growing at a far lower rate than the 2,0% for South Africa as a whole. The 

population in the three provinces of Gauteng, Kwazulu-Natal and Western Cape that 

house South Africa’s main cities is growing at significantly higher rates. 

These figures reflect the often reported high migration from poorer provinces to the 

main urban conurbations. This trend is expected to continue in the medium term. 

The Statistics South Africa population model for projections between the censuses 

expects a net outward migration from the Eastern Cape of 315 970 in the period 

2001-06 2 . This is the largest absolute outward migration from any province. Outward 

migration at this level will also have an impact on the numbers of learners enrolled in 

the public school system. 

2.1.4. Conclusions from the national funding framework 

Trends in population and related factors, such as school enrolment, are the main 

drivers behind the allocation of 85% of funding through the ESF. The gradually 

declining share of the Eastern Cape in total population is therefore leading to a 

gradually declining share in the national allocation to provinces. These population 

trends will continue for the foreseeable future. 

Debate around the review of the ESF recognises that the population factors 

underlying the formula are leading to progressively smaller shares of total revenue to 

the poorer provinces. Mechanisms proposed to rectify this include greater use of 

poverty weighting, costed funding norms and allocations for constitutionally 

mandated basic services. The outcome of this debate is however not known at this 

point. It is by no means certain that any revision to the ESF will lead to a higher 

share for the Eastern Cape. 

1 Statistics South Africa: Census 2001: Primary Tables Eastern Cape – Census 1996 and 2001 

compared, 2003. 

2 Statistics South Africa: Mid-year population estimates for South Africa, July 2004. 

4


The province must engage more vigorously and proactively with debates over 

national funding and the equitable share to make the case for a greater allocation of 

resources to poorer provinces. Until this debate is won funding from the national 

government to the province will continue to grow at a slower rate than in many other 

provinces. Stronger capacity is needed in provincial fiscal policy and planning to 

engage with these issues. 

2.2. Provincial trends in education expenditure 

This section compares the allocations made to education between the provinces and 

discusses some of the main factors underlying these allocations. It must be 

emphasised that the equitable share is an unconditional allocation from national 

government. Provinces are responsible for their own budget allocations between 

functions and departments and can prioritise funds where they wish. A series of 

factors however affect their flexibility and ability to prioritise funds. 

2.2.1. Overall provincial funding issues 

Revenue raising 

The revenue raising instruments available to provinces are limited, although 

legislation has been passed to enable provinces to levy taxes, subject to an 

extensive consultation process and the approval of the national Minister of Finance. 

Own revenue raising capacity however varies tremendously between provinces. 

Poorer provinces have lower own revenue due to a smaller tax base, the reduced 

ability of a relatively poor population to pay user fees for services, and weaker 

administrative capacity to collect fees for public services. 

Table 4: Provincial total and own revenue 2003/04 3 

2003/04 - R mill 

Province Total Revenue Own Revenue % OR 

Eastern Cape 27,449 625 2.3% 

Free State 11,634 759 6.5% 

Gauteng 27,730 1,542 5.6% 

Kwazulu-Natal 33,806 1,110 3.3% 

Limpopo 21,902 493 2.3% 

Mpumalanga 11,647 321 2.8% 

Northern Cape 4,004 99 2.5% 

North West 13,436 345 2.6% 

Western Cape 16,538 1,320 8.0% 

SOUTH AFRICA 168,146 6,614 3.9% 

The table above shows both the great variation in revenue raising capacity between 

the provinces and the far proportions of own revenue raised in the poorer provinces. 

In 2003/04 the Eastern Cape and Limpopo had the lowest proportion of own 

revenue. The Western Cape was able to raise 8% of own revenue. 

3 National Treasury: Trends in inter-governmental finance - 2000/01 to 2006/07, September 2004. 

5


Personnel expenditure 

Personnel expenditure has historically taken a greater relative share of expenditure 

in the poorer provinces that have inherited large civil service staff complements from 

the former homeland administrations. The table below shows the proportions of total 

provincial expenditure on personnel for each province over the last three financial 

years. 

Table 5: Personnel as a proportion of total expenditure by province 

2001/02 to 2003/04 4 

2001/02 2002/03 2003/04 

Province % % % 

Eastern Cape 57.1% 49.4% 45.1% 

Free State 57.8% 53.5% 49.6% 

Gauteng 52.2% 46.9% 44.4% 

Kwazulu-Natal 54.3% 51.5% 47.4% 

Limpopo 60.6% 55.6% 52.5% 

Mpumalanga 52.5% 50.7% 47.3% 

Northern Cape 47.4% 44.3% 41.7% 

North West 57.9% 53.9% 51.1% 

Western Cape 52.0% 48.2% 46.4% 

SOUTH AFRICA 55.2% 50.7% 47.3% 

The table reflects the emphasis of both national and provincial government on 

limiting personnel expenditure and releasing resources for goods, services and 

capital. All provinces have greatly reduced the proportion of their expenditure on 

personnel due to: 

• The impact of personnel expenditure control in many provinces, especially 

after the provincial budget crises of the late 1990s. 

• Growing real allocations by national government to provinces from 2000/01 

onwards that have enabled provinces to devote more funding to nonpersonnel. 

• An increased emphasis by national and provincial government on 

infrastructure development and increased capital spending, especially 

apparent from 2001/02 onwards. 

The three provinces without a homeland inheritance: Northern Cape, Western Cape 

and Gauteng, consistently spend a low proportion of their budget on personnel. It is 

noticeable however that the Eastern Cape has rapidly reduced the proportion of their 

budget spent on personnel in recent years due to the factors listed above. 

Capital expenditure 

Infrastructure backlogs, primarily in schools, clinics and hospitals, are concentrated 

in the former homelands. The imperative of reducing backlogs requires relatively 


6


large and long term financial commitments from capital budgets in poorer provinces, 

putting further pressure on limited resources. 

The table below reflects rapidly rising relative allocations to capital in many of the 

poorer provinces over the last three financial years. This reflects both the greater 

emphasis of government on addressing infrastructure backlogs, and the ability of 

provinces to allocate greater funding to capital due to the real increase in national 

funding already noted. 

Table 6: Capital as a proportion of total expenditure by province 

2001/02 to 2003/04 5 

2001/02 2002/03 2003/04 


Eastern Cape 2.1% 4.0% 5.9% 

Free State 4.6% 4.7% 5.0% 

Gauteng 5.9% 6.7% 7.4% 

Kwazulu-Natal 7.7% 6.4% 7.0% 

Limpopo 2.5% 3.5% 4.1% 

Mpumalanga 5.9% 6.2% 6.1% 

Northern Cape 6.2% 7.2% 4.5% 

North West 4.1% 5.4% 4.8% 

Western Cape 5.8% 5.7% 5.6% 

SOUTH AFRICA 5.0% 5.4% 5.9% 

2.2.2. Trends in provincial education expenditure 

Proportion of expenditure on education 

The 1998/99 Medium Term Expenditure Review (MTER) review process between 

national and provincial government concluded that the proportion of provincial 

spending on education was likely to stabilise in the medium term at 40%. In the 

same year a number of financial management conditions were set for the Eastern 

Cape by national Treasury as part of the programme to stabilise provincial finance 

and eliminate debt. One of these conditions was that the province should allocate 

funds in its three core service delivery areas of education, health and social 

development in the ratio 40:20:20. The recent proportions of provincial expenditure 

on education, health and social development is shown for all provinces in the table 

below. 

The figures show that relative allocations to education were close to 40% in many 

provinces in 2001/02 and the Eastern Cape met this target. Since then however 

relative allocations to education and health have fallen significantly in almost all 

provinces, with equally significant increases in the relative proportion going to social 

development. 


7


Table 7: Education, Health and Social Development as a proportion of total 

expenditure by province - 2001/02 to 2003/04 6 

Education Health Social Development 

2001/02 2002/03 2003/04 2001/02 2002/03 2003/04 2001/02 2002/03 2003/04 

Province % % % % % % % % % 

Eastern Cape 40.6% 37.5% 34.7% 19.4% 17.7% 17.1% 23.8% 26.0% 28.5% 

Free State 38.9% 36.7% 35.3% 23.4% 22.4% 21.8% 18.0% 21.7% 25.2% 

Gauteng 36.0% 33.2% 33.6% 33.5% 31.2% 28.7% 14.9% 16.2% 18.8% 

Kwazulu-Natal 37.3% 36.4% 35.5% 27.4% 25.5% 23.6% 20.0% 23.7% 26.8% 

Limpopo 43.0% 39.7% 37.9% 16.6% 16.3% 16.6% 19.0% 22.8% 25.0% 

Mpumalanga 39.9% 40.1% 39.2% 16.9% 16.9% 16.9% 18.1% 20.9% 23.3% 

Northern Cape 34.7% 34.0% 31.4% 17.1% 17.3% 19.7% 23.5% 26.3% 27.6% 

North West 40.4% 38.3% 36.6% 16.9% 17.1% 16.5% 20.6% 23.2% 26.4% 

Western Cape 35.2% 33.2% 32.3% 29.6% 27.3% 27.9% 19.0% 21.6% 23.1% 

SOUTH AFRICA 38.6% 36.5% 35.3% 23.9% 22.5% 21.6% 19.4% 22.2% 24.8% 

A series of points need to be made from these trends: 

• The national fall in the proportion of provincial expenditure on education and 

health almost exactly matches the rise in proportion on social development. 

Growing allocations by provinces to social development reflect rapidly growing 

expenditure on social grants, especially apparent since 2001/02. Provinces 

however must budget for social grants from within their total revenue from the 

equitable share and own resources. 

• The ex-homeland provinces of Eastern Cape, Kwazulu Natal, Limpopo, 

Mpumalanga, North West and Free State have greater numbers of social 

grant beneficiaries. These provinces have seen a greater relative increase in 

the share of the budget given to social development, of between 5% and 7%. 

The three provinces without a homeland inheritance saw a smaller increase of 

around 4%. 

• There was a particularly steep fall in education expenditure as a proportion of 

the total in the Eastern Cape, in fact a greater relative reduction than in any 

other province. While the Eastern Cape devoted 40% of its expenditure to 

education in 2001/02, in 2003/04 it had the lowest proportion devoted to 

education in the ex-homeland provinces. 

• The three provinces without a homeland inheritance again show the lowest 

proportions of expenditure on education. This reflects both generally smaller 

proportions of expenditure on personnel, and a choice of higher expenditure 

in other sectors following from, in many cases, the flexibility available from 

greater budgetary resources. 

Proportion of education expenditure on personnel 

The 1998/99 Medium Term Expenditure Review (MTER) process also established 

the goal of limiting the proportion of provincial education expenditure on personnel to 

85% in order to release funding for learner materials and equipment and school 

infrastructure. The table below shows trends in this proportion in recent years. 


8


Table 8: Personnel as a proportion of education expenditure by province 

2001/02 to 2003/04 7 

2001/02 2002/03 2003/04 


Eastern Cape 90.2% 86.7% 85.0% 

Free State 87.0% 85.1% 83.0% 

Gauteng 83.9% 81.9% 75.1% 

Kwazulu-Natal 87.9% 87.3% 83.2% 

Limpopo 90.9% 88.7% 85.9% 

Mpumalanga 88.0% 82.7% 78.8% 

Northern Cape 83.1% 77.5% 77.6% 

North West 90.3% 88.9% 86.5% 

Western Cape 84.4% 82.3% 81.6% 

SOUTH AFRICA 87.3% 84.6% 81.8% 

The proportion of education expenditure on personnel has been falling across all 

provinces and this goal has now been met in almost all provinces, including the 

Eastern Cape. The main reasons for this have been: 

• The high real growth rate in education expenditure since 2000/01, especially 

in the poorer provinces and in Gauteng and Mpumalanga (see below). 

• The impact of measures to control expenditure on personnel in the period 

from 1998/99, especially in the ex-homeland provinces with an inherited 

legacy of large civil service complements. 

A 2003 review by the National Department of Education of the resourcing of 

education in public schools has highlighted the importance of non-personnel 

expenditure in ensuring quality education by providing learning resources in the 

classroom. The review argued that ‘poorer provinces, which spend less per learner, 

are particularly susceptible to the crowding out of non-personnel expenditure by 

personnel, and particularly educator, expenditure. This is a serious problem, with 

serious consequences for efficiency’. 8 

Growth in provincial education expenditure 

The three years 1997/98 to 2000/01 were a period of financial crisis in most 

provinces. Education expenditure fell in real terms in all provinces as resources were 

devoted to paying off provincial debt and personnel backlogs accrued in the first 

period of provincial administration up to 1997/98. Real cuts in education expenditure 

were especially stark in the Eastern Cape, which ended 1997/98 with close to R2 

billion in debt, outstanding commitments and personnel backlogs. The years to 

2000/01 were used primarily to pay off these debts and backlogs, with no real growth 

in expenditure. 


8 National Department of Education: Review of the financing, resourcing and costs of education in 

public schools, March 2003, p.23 

9


Annual growth in education expenditure from 2000/01 to 2003/04 averaged 11.3% 

for all provinces, above the rate of inflation and allowing provinces to increase 

allocations to non-personnel expenditure. In the Eastern Cape this period was used 

to recover from the financial constraints of the previous four years. Funding for nonpersonnel 

expenditure in schools was available for the first time since 1997/98. 

MTEF budgets project a far lower rate of increase in the forthcoming period 2003/04 

to 2006/07, as set out in the table below. Later sections of this report will examine if 

projected budget growth will be sufficient to enable an adequate non-personnel 

budget in the Eastern Cape. 

Table 9: Growth in provincial education expenditure 1997/98 to 2006/07 9 

1997/98 

to 

2000/01 

2000/01 

to 

2003/04 

2003/04 

to 

2006/07 


Eastern Cape 2.1% 12.3% 7.1% 

Free State 5.6% 10.6% 8.0% 

Gauteng 5.2% 11.6% 3.5% 

Kwazulu-Natal 4.0% 13.5% 7.4% 

Limpopo 6.1% 8.5% 8.0% 

Mpumalanga 4.8% 14.4% 9.7% 

Northern Cape 4.7% 10.2% 8.5% 

North West 4.5% 9.5% 6.8% 

Western Cape 0.9% 8.9% 5.9% 

SOUTH AFRICA 4.0% 11.3% 6.9% 

Table 10: Per capita expenditure on education by province 2001/02 to 2003/04 10 

Per capita expenditure on education 

2001/02 2002/03 2003/04 

Province Rands Rands Rands 

Eastern Cape 3 908 4 461 4 870 

Free State 4 470 5 034 5 871 

Gauteng 4 685 5 037 5 728 

Kwazulu-Natal 3 478 3 820 4 359 

Limpopo 3 711 4 051 4 545 

Mpumalanga 3 721 4 289 4 951 

Northern Cape 5 229 5 954 6 455 

North West 4 474 4 819 5 498 

Western Cape 4 795 5 089 5 532 

SOUTH AFRICA 4 036 4 451 5 011 

The table above compares per capita expenditure on education between provinces. 

It reflects the continuing wide range in expenditure on education for each learner. 

While ex-homeland provinces generally spend less than the national average, the 



10


Eastern Cape is close. It is noticeable that the relatively wealthier provinces still 

generally have a higher per capita expenditure on education. 

Non-personnel non-capital (NPNC) expenditure per learner 

Non-personnel non-capital (NPNC) expenditure in public schools is a crucially 

important area for educational performance, as the Department of Education’s 2003 

Review noted. NPNC recurrent funding is used to purchase essential learner 

materials and equipment for the classroom and to run school services. NPNC per 

capita in public schools represents the funding available to each learner for a 

‘package’ of learner materials and support. It is vital that provinces prioritise this area 

for funding. National Treasury has drawn attention to the importance of nonpersonnel 

non-capital (NPNC) expenditure for educational outcomes. The 2003 

Inter-Governmental Fiscal Review (IGFR) notes that ‘the provinces with low nonpersonnel 

non-capital expenditure per learner in public schools also have low senior 

certificate pass rates’ 11 . The table below compares NPNC per capita across the 

provinces in recent years. 

Table 11: Non-personnel non-capital expenditure per public school learner 12 

Province 1999/00 2000/01 2001/02 2002/03 

Eastern Cape 92 123 175 190 

Free State 325 204 206 308 

Gauteng 350 270 240 463 

Kwazulu-Natal 175 55 57 113 

Limpopo 193 116 144 197 

Mpumalanga 153 86 153 355 

Northern Cape 461 574 555 554 

North West 230 182 227 250 

Western Cape 312 273 354 457 

SOUTH AFRICA 210 151 176 259 

In 2002/03 the three provinces of Gauteng, Northern Cape and Western Cape spent 

an average of R468 per public school learner on NPNC. The remaining provinces 

averaged a much lower R155 per learner. NPNC per capita in the Eastern Cape has 

risen rapidly in recent years. The province spent R190 per learner in 2002/03 

reflecting the increasing non-personnel allocations of recent years, up from a low of 

R92 per learner in 1999/00 during the financial crisis of the late 1990s. 

More worryingly, the figures demonstrate wide variation between provinces and over 

time in this crucial area of funding. This variation is much greater than for total 

expenditure per public school learner. The three non-homeland provinces are 

spending an average of three times more than the other provinces per learner on 

learner materials and other essential school recurrent items. 

NPNC has been allocated to public schools under the framework of the national 

norms and standards for schools funding (NSSF) since 1999/00. NPNC has been 

11 National Treasury: Inter-Governmental Fiscal Review (IGFR) 2003, p.59. 

12 IGFR 2003, p. 60. 

11


prioritised towards the poorest schools through five poverty weighted quintiles. As 

the NSSF has been progressively implemented there have been increasing concerns 

about the wide variation in per learner allocations per province reflected in the table 

above. Per learner allocations in the two poorest quintiles, Q1 and Q2, have also 

varied greatly between provinces with the poorer provinces able to allocate far less 

per learner. In 2003 the Department of Education concluded that ‘a basic minimum 

package’ of NPNC inputs should be around R500 per learner in 2002 Rands. 13 The 

table above shows that only the three non-homeland provinces were close to this 

level in 2002/03. 

2.2.3. Conclusions from provincial trends in education expenditure 

Education expenditure in the Eastern Cape fell in real terms in the period 1997/98 to 

2000/01 as limited funding was devoted to repaying debt and personnel backlogs. 

Non-personnel resources were especially limited during this period leading to very 

limited expenditure on teaching and learning materials in schools. Expenditure 

increased rapidly in real terms from 2000/01 onwards due both to increases in 

national funding above the rate of inflation and to real increases in the allocation to 

education within the province. This enabled the province to gradually recover from 

the financial crisis of the late 1990s and to increase the share of its budget devoted 

to non-personnel. At the same time there is pressure on the education budget: 

• Growth in expenditure on social grants has been even higher than in 

education over the same period. This trend will continue for the medium term 

and is limiting the scope of the province to continue the growth in allocations 

to education of recent years. 

• Even allowing for this factor, the province has responded with a sharp 

reduction in the relative allocation to education over the last three years, 

greater than in any other province. The Eastern Cape needs to reverse this 

rapid reduction in the proportion of funding given to education. 

• While education expenditure has grown in all provinces at rates significantly 

higher than inflation in recent years, this rate of growth is not expected to 

continue. The Eastern Cape is projecting only small real increases in the 

education budget over the current MTEF period 2004/05 to 2006/07. 

High real growth in education expenditure since 2000/01 has enabled release of 

funding for non-personnel items vital to education. This growth is however relatively 

recent and follows a period of financial crisis from 1997/98 to 2000/01 when nonpersonnel 

funding was virtually non-existent. The crucial area of non-personnel noncapital 

expenditure is still well below average and certainly well below the national 

per learner target, although progress has been made in reaching a more adequate 

NPNC funding level in recent years. The province however faces the challenge of 

keeping and developing these gains in an environment of far greater funding 

pressures, both currently and over the next few years. 

13 Department of Education: Improving access to free and quality basic education for all, June 2003, 

p.16. 

12


3. ANALYSING PUBLIC SCHOOL EDUCATION 

This section describes and analyses the public school system, firstly for the various 

provinces and secondly in more detail for the Eastern Cape. The main indicators for 

public school education are set out. The factors underlying the main reasons for 

differences are discussed, with emphasis on school type and size and on educator 

provisioning. 

3.1. Comparing public school education between provinces 

The table below compares the main education indicators for each province using 

2000 and 2001 data, the most recent years that are easily available for all provinces. 

Table 12: Public school education indicators by province 2000 and 2001 14 

Province Learners Educators Schools LER LSR LCR 

Eastern Cape 2,027,791 60,882 6,056 33.3 335 43 

Free State 703,912 22,403 2,396 31.4 294 33 

Gauteng 1,444,861 43,761 1,900 33.0 760 33 

Kwazulu-Natal 2,661,508 71,628 5,608 37.2 475 40 

Limpopo 1,793,788 56,491 4,446 31.8 403 40 

Mpumalanga 894,284 24,245 1,864 36.9 480 48 

Northern Cape 194,377 6,183 459 31.4 423 26 

North West 883,567 28,743 2,271 30.7 389 34 

Western Cape 888,888 25,008 1,474 35.5 603 31 

SOUTH AFRICA 11,492,976 339,344 26,474 33.9 434 38 

Note: Learner:educator ratio (LER), learner:school ratio (LSR) and learner:classroom ratio (LCR). 

A number of features of the public schooling system can be seen from comparing 

indicators across the provinces: 

• Distribution and size of the public schooling system: Eastern Cape, 

Kwazulu-Natal and Limpopo have the challenge of managing the largest 

public schooling systems. These three provinces account for 56% of learner 

enrolment and educators, and 61% of schools. The Eastern Cape has the 

largest number of schools to manage in any one province. 

• Learner:educator ratio (LER): The LER measures the average number of 

learners each educator is teaching. It varies significantly between provinces. 

North West, Northern Cape, Free State and Limpopo all had low LERs of less 

than 32:1 in 2001. The Eastern Cape and Gauteng both had ‘mid-range’ LERs 

close to 33:1. Kwazulu-Natal, Mpumalanga and Western Cape all had higher 

LERs above 35:1. 

• Learner:classroom ratio (LCR): The LCR measures the average number of 

learners in each classroom. It also varies significantly between the provinces. 

The Northern Cape, Western Cape, Free State, Gauteng and North West 

14 All data is taken from the EMIS 10 th day returns for 2001 from national Department of Education: 

‘Education statistics in South Africa 2001’, with the exception of learner:classroom ratios taken from 

the ‘School Register of Needs 2000’. 

13


have a lower learner:classroom ratio below 35:1. There is a noticeable 

difference in Kwazulu-Natal, Limpopo, Eastern Cape and Mpumalanga. These 

provinces all have a LCR above 40:1, reflecting the large classroom backlogs 

that persist in these ex-homeland provinces. 

• Learner:school ratio (LSR): School size all varies greatly across the 

provinces. Free State, Eastern Cape, North West, Limpopo, and Northern 

Cape all have relatively small schools with LSRs less than the national 

average of 434. Free State and the Eastern Cape stand out especially as 

having public school systems with small schools. Kwazulu-Natal and 

Mpumalanga have schools that are, on average, slightly larger than nationally. 

Western Cape and Gauteng both have a public school system with large 

schools in comparison to the rest of the country, with LSRs greater than 600. 

The relationship between educator provision, classroom provision and school size 

across the provinces deserves discussion. A well resourced schooling system should 

strive to balance the different inputs into the education process. A good target for 

education resource provision is one educator teaching one class in one classroom at 

a time, while recognising that actual practice is far from this ideal in many schools in 

many provinces. Applying this target and allowing for educator time each day outside 

teaching, the LER ideally should be no more than 20% lower than the LCR 15 . 

Variation between the LER and LCR that is greater than this indicates either a lack of 

classrooms, or a relative overprovision of educators in relation to other education 

resources, or in some cases the existence of both problems. 

The indicators also show that many provinces have large numbers of small schools, 

especially the Free State and the Eastern Cape. Small schools have advantages of a 

generally low LER and a more ‘human’ scale. They are also unavoidable in many 

communities, especially in sparsely populated rural areas. Large numbers of small 

schools however represent an unbalanced use of resources by concentrating school 

infrastructure and educators on relatively small numbers of learners. Larger schools 

‘cluster’ educators, classrooms and learners more effectively, achieving economies 

of scale, enabling better allocation of resources, and managing educator utilisation to 

maximise the time spent teaching in the classroom. This is especially true for 

secondary schools where the number of learning areas increases and the complexity 

of arranging the school timetable follows correspondingly. 

The education indicators in the table above are of course provincial averages, hiding 

significant disparities between individual public schools within each province. Using 

these criteria however only Gauteng and the Western Cape have achieved a broad 

balance in allocating resources to public school education. All other provinces, with 

the possible exception of Kwazulu-Natal, face the challenge of small average school 

size or an imbalance between educator and classroom provision. Both challenges 

are significant in the Eastern Cape, which has the second smallest average school 

size in the country and the second widest variation between the LER and the LCR. 

15 The post distribution model for the allocation of educator posts to schools is analysed later in this 

report. It sets out norms for educator period load (proportion of time spent teaching) of 98% for 

primary schools falling to 84% for the FET phase in secondary schools, noting that these ‘are based 

on average prevailing practices and do not represent workload policy’. In a well-resourced school 

system these norms imply a LER up to 20% lower than the LCR, depending on the learning phase. 

14


One of the most striking features of the data is also that while average school size 

and classroom provision is strongly related to the relative poverty of a province, there 

is no clear relationship between relative poverty and educator provision. The poorer 

provinces have a higher LCR indicating backlogs in classroom provision. The two 

wealthiest provinces of Gauteng and Western Cape have the largest average school 

size due to the highly urban nature of their schooling systems. Many of the poorer 

provinces with former homeland areas have low LSRs due to large numbers of 

relatively small rural schools. The LER seems however to have no clear correlation 

to relative wealth or poverty. The Department of Education has noted that the ‘LER 

does not appear to be strongly linked to the fiscal advantage enjoyed by the 

province. The Western Cape, for example, is an advantaged province, yet its overall 

LER is higher than that of the Eastern Cape’. 16 

There is also clearly a strong correlation between school size and educator 

provisioning. Generally the provinces with a low average school size, indicating 

relatively larger numbers of small schools, have a lower LER. The same recent 

report by the Department of Education analysed the impact of small schools on the 

LER. It noted that ‘the LER for small schools is always somewhat lower than that for 

the province as a whole. This is because the 1998 post provisioning policy favours 

small schools somewhat. The LER for non-small, or large, schools will logically be 

somewhat higher than the overall ratio’. 

The table below, drawn from the same review of education in public schools, sets out 

provincial LERs for small and large public primary schools only, together with the 

proportion of small primary schools in each province. 

Table 13: LER for small and large public primary schools and percentage of 

small schools 17 

LER 

Small 

Schools 

LER 

Large 


LER All 

Primary 


Percent 

Small 


Province 

Eastern Cape 22 30 28 19% 

Free State 21 32 29 36% 

Gauteng 25 38 38 5% 

Kwazulu-Natal 30 37 36 8% 

Limpopo 24 33 32 9% 

Mpumalanga 29 38 36 22% 

Northern Cape 22 31 29 27% 

North West 20 28 27 20% 

Western Cape 28 34 33 17% 

SOUTH AFRICA 24 34 33 17% 

The data shows the far lower learner:educator ratio in small schools across South 

Africa. The provinces with largely rural schooling systems, inherited either from 


public schools, March 2003, p.32 

17 For the purposes of the review small schools were considered to be those with an average ‘grade 

group size’ of less than 30. Total enrolment of a school is not really the issue here, as the focus is on 

smallness from the perspective of educator provisioning. 

15


former homeland areas or through farm schools, tend to have high proportions of 

small schools. Kwazulu-Natal and Limpopo stand out as provinces with an 

unexpectedly low proportion of small schools, despite their homeland inheritance 

and extensive rural areas. It is likely that both provinces have taken a decision to 

move towards a schooling system of larger schools. 

It can also be seen from the data that provinces have made very different decisions 

in post provisioning. The review notes that ‘the LER for small schools varies 

considerably between provinces, from 20 to 30, and this despite the fact that all are 

using the same post provisioning model’. A post establishment based on a relatively 

low overall LER will lead to very low LERs in small schools, especially in provinces 

with high proportions of small schools. Clearly some provinces have made a 

strategic choice to allow a slightly higher overall learner:educator ratio, given the 

pressures to increase the educator establishment that are inherent in a system with 

large numbers of small schools. These pressures will be analysed in a later section. 

3.2. Public school education in the Eastern Cape 

This section analyses the public school system in the province in more detail than for 

the provinces, drawing out some of the factors driving expenditure within the system. 

All data is taken from the EMIS 10 th day return survey for the province for 2004 

unless otherwise stated. 

3.2.1. Levels of public schools in the Eastern Cape 

The Eastern Cape is now unique in South Africa in having a three level public 

schooling system of primary, secondary and combined schools, reflecting the 

complex history of the Department of Education in incorporating six former 

departments from the various apartheid era administrations. Limpopo province is the 

only other province to inherit a combined school system, which was progressively 

phased out from the late 1990s. 

• Primary schools cover grades R to 7 in common with the rest of South 

Africa. Within this level there are also both junior primary schools (grade R to 

3/4) and senior primary schools (grade 4/5 to 7) in operation. 

• Secondary schools cover grades 8 to 12 again in common with the rest of 

South Africa. Within this level there are also both ‘lower’ secondary schools 

(grade 8 to 10) and senior secondary schools (grade 10 to 12) in operation. 

• Combined schools cover grade R to 9, and are also called junior secondary 

schools. They are a sub-system inherited almost entirely from the former 

Transkei education system and can be thought of as ‘extended’ primary 

schools. The secondary school system in the former Transkei as a result 

consists almost entirely of senior secondary schools. 

The table below sets out the main indicators for the three levels in the public school 

system. A number of points can be noted from the indicators: 

• 6,019 public schools were identified on EMIS at the start of 2004, slightly 

down from the 6,056 schools of 2001. 

16


Table 14: Combined, primary and secondary schools in the Eastern Cape 2004 

Level Schools Enrolment Classrooms Educators LCR LER ECR 

Combined Schools 2,553 1,041,853 22,564 30,812 46.2 33.8 1.37 

Primary Schools 2,587 626,995 19,324 19,337 32.4 32.4 1.00 

Secondary Schools 879 413,312 11,534 14,518 35.8 28.5 1.26 

EASTERN CAPE 6,019 2,082,160 53,422 64,667 39.0 32.2 1.21 

• Public school enrolment according to EMIS was slightly up from 2,027,791 in 

2001 to 2,082,160 in 2004, an increase of 2.6%. 

• The number of educators according to EMIS had increased from 60,882 in 

2001 to 64,667 in 2004, an increase of 6.2%. 

• The LER of 32.2 for the public schooling system as whole is lower than the 

2001 LER of 33.3 presented in the provincial data. The secondary school 

level has an especially low LER of 28.5. The LER for all three levels indicates 

a relatively favourable level of educator provisioning in comparison to many 

other provinces. 

• The relatively high LCR of 39 reflects continued classroom backlogs but is an 

improvement on the LCR of 43 in 2001 as the infrastructure programme 

continues to bear fruit. 

• The classroom backlog is concentrated in combined schools as shown by the 

very high LCR of 46.2. 

• The high LCR of 46.2 for combined schools coupled with the relatively 

favourable LER of 33.8 indicates significant over-provisioning of educators in 

comparison to classrooms. 

3.2.2. Types of public schools in the Eastern Cape 

Table 15: Type of school by former department 2004 

TYPE 

CISKEI 

DET 

HOA 

All Grades 2 22 19 1 2 4 12 62 

Combined 27 121 9 24 15 42 2,147 2,385 

Farm 26 243 7 1 95 5 11 61 449 

Full Primary 357 252 83 3 114 61 32 799 1,701 

Full Secondary 164 101 39 1 36 21 7 37 406 

Hospital 1 3 4 8 

Intermediate 3 8 20 31 

Junior Primary 109 61 8 9 59 10 159 415 

‘Lower’ Secondary 24 3 21 1 5 54 

Museum 1 1 

Senior Primary 45 28 3 1 1 2 10 90 

Senior Secondary 8 17 1 81 12 298 417 

EASTERN CAPE 766 859 168 6 282 264 117 3,552 6,019 

HOD 

HOR 

NEW DEPT 

Not available 

TRANSKEI 

E. CAPE 

17


The inheritance of the schooling system from the apartheid era is seen from the table 

above. Over 70% of the public schools in the province are ex-Ciskei and Transkei 

schools. The Department of Education has opened 264 new schools since its 

inception, mostly senior secondary, primary and junior primary schools. 

Important differences should be noted between the former departments that have fed 

through into the schooling system that the Department of Education must manage: 

• The Transkei system consisted mostly of combined schools with consequent 

senior secondary schools, but also with large numbers of primary grade R-7 

schools. There was a significant presence of junior primary schools. A more 

conventional grade R-7 primary school system was therefore not unknown. 

• The Ciskei system consisted overwhelmingly of full primary and full secondary 

schools with very limited numbers of combined and senior secondary schools. 

There was also a significant presence of junior primary schools. 

Table 16: Type of public school by education district 2004 

District 

All Grades 

Combined 

Farm 

Full Primary 

BIZANA 119 58 12 22 211 

BUTTERWORTH 1 246 71 1 3 26 46 394 

COFIMVABA 2 179 58 1 13 32 285 

CRADOCK 1 1 36 27 16 10 2 7 100 

EAST LONDON 11 6 29 109 69 2 50 3 29 4 312 

ENGCOBO 1 130 15 47 1 1 2 11 1 19 228 

FORT BEAUFORT 1 7 52 117 45 33 14 6 275 

GRAAFF-REINET 3 3 52 30 13 3 1 105 

GRAHAMSTOWN 9 3 53 22 11 2 3 103 

IDUTYWA 217 72 24 36 349 

KING WILLIAMS TOWN 8 17 21 226 99 55 26 16 5 473 

LADY FRERE 3 78 10 47 2 6 9 18 173 

LIBODE 1 245 1 98 1 31 40 417 

LUSIKISIKI 2 189 107 1 19 31 349 

MALUTI 126 50 2 14 19 211 

MT FLETCHER 3 92 8 52 3 19 1 17 195 

MT FRERE 165 43 1 15 24 248 

PORT ELIZABETH 1 9 30 124 68 2 3 11 1 1 8 258 

QUEENSTOWN 4 13 34 53 29 5 24 7 11 7 187 

QUMBU 1 151 65 2 1 11 24 255 

STERKSPRUIT 3 54 54 65 12 7 2 14 211 

UITENHAGE 5 11 54 52 29 14 8 1 174 

UMTATA 2 215 69 4 2 7 39 338 

UMZIMKULU 109 39 1 19 168 

EASTERN CAPE 62 2,385 449 1,701 406 8 31 415 54 1 90 417 6,019 

Full Secondary 

Hospital 

Intermediate 

Junior Primary 

‘Lower’ Secondary 

Museum 

Senior Primary 

Senior Secondary 

EASTERN CAPE 

18


• Department of Education and Training (DET) schools followed the 

conventional primary and secondary model, but with significant numbers of 

combined schools. A large number of farm schools also fell under this system. 

• House of Assembly (HOA) schools overwhelmingly followed a primarysecondary 

school model, but with significant numbers of ‘combined’ schools 

covering all grades R-12, mostly primary and secondary schools on the same 

site in the small towns of the province. 

• House of Representatives (HOR) schools also overwhelmingly followed the 

primary-secondary model, but with large numbers of farms schools in the west 

of the province. 

For the purposes of analysis the three levels of the schooling system were further 

sub-divided into the different schooling types in the province, using both EMIS 

classifications of type and the grades offered by the different schools. 12 types of 

public school can be identified in the Eastern Cape. The distribution of the types of 

school across the education districts is set out in table 16 above, with indicators for 

each type set out in table 17 below: 

• Primary and secondary ‘combined’ schools: There are 62 schools 

classified covering all grades R to 12. These are mostly small town schools, 

often with separate primary and secondary schools on the same site. They 

are schools of a higher than average size, with relatively low and similar LER 

and LCR. They are generally well resourced schools. 

• Combined or junior secondary (JSS) schools: 2 385 combined schools 

cover grades 1 to 9 overwhelmingly in the former Transkei as has been 

noted. 18 While the LER is slightly higher than average, the LCR is very high 

due to classroom backlogs. 

• Intermediate schools: 31 intermediate schools cover grades 5 to 9 in both 

the former Transkei and Ciskei. In many cases they are probably ‘higher 

combined’ schools following on from associated junior primary schools. The 

exception is 3 Port Elizabeth schools covering grades 7 to 9 that are true 

intermediate schools. They are all small relatively well resourced schools with 

a low LER and LCR. 

• Farm schools vary in character and often start or finish at ‘unconventional’ 

grades. There are 449 farm schools serving rural farming communities mostly, 

but not exclusively, in the former Cape Province areas. They are very small 

schools with an average enrolment of only 58. LCR and LER are very low with 

small numbers of learners in each grade. With the small numbers of learners 

in most farm schools multi-grade teaching is common. 

• ‘Full’ Primary schools cover grades R to 7. There are 1,701 in all areas of 

the province, including the former Transkei. On average they are well 

resourced schools with low and similar LERs and LCRs. There are clearly 

many small primary schools, shown by the low average enrolment. 

• 415 Junior Primary Schools cover from grades R to 3/4 and are distributed 

throughout the province. They are small schools with low LCR and LER. 

• 90 Senior Primary Schools are mostly in the urban areas of the province. 

They have a higher than average enrolment and have relatively favourable 

18 The number of combined schools differs from the number in the analysis by schooling level. 

Combined schools covering only grades R to 7 have been classified by type as ‘primary’. 

19


LCRs and LERs. Many are well resourced schools associated with 

‘preparatory’ junior primary schools. 

• There are 8 small Hospital Schools in the province. 

• ‘Full’ Secondary Schools are distributed throughout the province with the 

exception of the former Transkei where they rarely exist. Average school size 

is high and LCR and LERs are favourable. There are 406 secondary schools. 

Table 17: Indicators by type of public school 2004 

Type Schools Enrolment Classrooms Educators LCR LER ECR 

PRIMARY & SECONDARY COMBINED SCHOOLS: ALL GRADES R-12 

Average 604 17 19 

Total 62 37,454 1,073 1,158 34.9 32.3 1.08 

COMBINED SCHOOLS: GRADES R-9 

Average 410 9 12 

Total 2385 977,679 20,567 28,691 47.5 34.1 1.40 

INTERMEDIATE SCHOOLS: GRADES 5-9 

Average 317 10 11 

Total 31 9,832 304 337 32.3 29.2 1.11 

FARM SCHOOLS: MOSTLY PRIMARY GRADES 


Total 449 25,849 1,325 1,143 19.5 22.6 0.86 

FULL PRIMARY SCHOOLS: GRADES R-7 


Total 1701 505,108 14,564 15,057 34.7 33.5 1.03 

JUNIOR PRIMARY SCHOOLS: GRADES R-3 or 4 


Total 415 75,758 2,810 2,633 27.0 28.8 0.94 

SENIOR PRIMARY SCHOOLS: GRADES 4 or 5-7 

Average 396 13 12 

Total 90 35,624 1,214 1,087 29.3 32.8 0.90 

HOSPITAL SCHOOLS: MOSTLY PRIMARY GRADES 


Total 8 578 15 16 38.5 36.1 1.07 

FULL SECONDARY SCHOOLS: GRADES 8-12 

Average 603 17 21 

Total 406 244,707 7,084 8,472 34.5 28.9 1.20 

‘LOWER’ SECONDARY SCHOOLS: GRADES 8-10 


Total 54 7,278 284 314 25.6 23.2 1.11 

SENIOR SECONDARY SCHOOLS: GRADES 10-12 

Average 389 10 14 

Total 417 162,292 4,181 5,756 38.8 28.2 1.38 

MUSEUM SCHOOL 

Average 1 1 3 

Total 1 1 1 3 1.0 0.3 3.00 

EASTERN CAPE 


Total 6,019 2,082,160 53,422 64,667 39.0 32.2 1.21 

20


• The term ‘Lower’ Secondary Schools has the potential to cause confusion. 

The type of school indicated here exists mostly in the former Ciskei areas of 

the province and covers grades 8 to 10. In the ex-Ciskei these schools are 

called junior secondary schools. They must not however be confused with 

combined or junior secondary schools in the ex-Transkei, which cover grades 

R to 9 and are much greater in number. Hence the term ‘lower’ secondary 

school is used throughout this report. They are small schools with a LSR of 

only 135. There are only 55 and many of these schools may well be phasing 

out or converting progressively to full secondary schools. Typically for small 

schools they have low LCRs and LERs. 

• Senior Secondary Schools exist overwhelmingly in the former Transkei. 

They are a significant part of the secondary system with 417 in total, more 

than the number of secondary schools. They are smaller than average for 

secondary schools. They have a low LER but a relatively high LCR, indicating 

classroom backlogs. 

• There is one Museum School in Port Elizabeth. 

3.2.3. Public schools by education district 

The table below sets out the main indicators by education district. A series of 

conclusions on the geographical differences across the province can be drawn by 

grouping the districts that have similar characteristics: 

• Graaf Reinet, Cradock, Grahamstown, and Uitenhage mostly cover farming 

areas from the former Cape Province. Fort Beaufort, Queenstown and 

Sterkspruit are also mostly rural but also include former homeland areas. The 

defining characteristic of these districts is the prevalence of small rural 

schools. LERs and LCRs are low and similar, generally below 30 in both 

cases, although with LCRs higher in the districts with former homeland areas. 

• Port Elizabeth and East London are mostly urban districts. LERs and LCRs 

are relatively favourable and similar in the range of 32 to 34, indicating a 

good and matching level of both classroom and educator provisioning. 

• Butterworth, Cofimvaba, Lady Frere, Engcobo, Idutywa, Mount Fletcher, 

Qumbu, Maluti, Mount Frere and Umzimkulu cover the south-eastern and 

northern areas of the former Transkei. The defining characteristic of these 

districts is a high LCR due to classroom backlogs, but a relatively favourable 

LER. LCRs range from 33.2 to 44.3 but are generally close to the provincial 

average. LERs range from 28.6 to 34.5 but are mostly below the provincial 

average. Schools in these districts generally have good educator provisioning 

but despite progress still face significant classroom backlogs. 

• Umtata, Libode, Lusikisiki and Bizana are the districts with some of the 

deepest rural poverty in South Africa. Schools in these districts face major 

resource challenges. LCRs range from 50 to 56.5 with LERs ranging from 

34.5 to 38.6. Schools in these districts have to contend with serious 

classroom backlogs. Educator provisioning is worse than for the rest of the 

province but is still at levels that can provide teaching in manageable class 

sizes. 

One of the most significant features of the former Transkei education districts is the 

wide variation between LCR and LER. While the LER is below 35:1 in 11 out of 

21


these 15 districts, the LCR is below 40:1 in only 4 out of these 15 districts. Educator 

provisioning in many districts of the former Transkei is at higher levels than in the 

Western Cape, while classroom backlogs remain amongst the most serious in the 

country. 

Table 18: Public school indicators by education district 2004 

District Schools Enrolment Classrooms Educators LCR LER ECR 

BIZANA 211 100,048 1,811 2,593 55.2 38.6 1.43 

BUTTERWORTH 394 109,729 2,861 3,694 38.4 29.7 1.29 

COFIMVABA 285 78,151 2,065 2,631 37.8 29.7 1.27 

CRADOCK 100 26,206 923 887 28.4 29.5 0.96 

EAST LONDON 312 140,859 4,058 4,266 34.7 33.0 1.05 

ENGCOBO 228 73,464 1,651 2,234 44.5 32.9 1.35 

FORT BEAUFORT 275 47,468 2,074 1,892 22.9 25.1 0.91 

GRAAFF-REINET 105 25,443 1,045 910 24.3 28.0 0.87 

GRAHAMSTOWN 103 29,350 1,052 1,043 27.9 28.1 0.99 

IDUTYWA 349 103,822 2,342 3,140 44.3 33.1 1.34 

KING WILLIAMS TOWN 473 120,060 4,082 4,363 29.4 27.5 1.07 

LADY FRERE 173 46,901 1,411 1,639 33.2 28.6 1.16 

LIBODE 417 163,932 2,904 4,482 56.5 36.6 1.54 

LUSIKISIKI 349 144,201 2,724 3,804 52.9 37.9 1.40 

MALUTI 211 65,451 1,594 2,250 41.1 29.1 1.41 

MT FLETCHER 195 52,229 1,425 1,719 36.7 30.4 1.21 

MT FRERE 248 78,985 1,884 2,486 41.9 31.8 1.32 

PORT ELIZABETH 258 175,661 5,412 5,371 32.5 32.7 0.99 

QUEENSTOWN 187 62,924 1,885 2,091 33.4 30.1 1.11 

QUMBU 255 79,099 1,705 2,449 46.4 32.3 1.44 

STERKSPRUIT 211 63,666 1,799 2,104 35.4 30.3 1.17 

UITENHAGE 174 81,633 2,566 2,584 31.8 31.6 1.01 

UMTATA 338 146,734 2,827 4,117 51.9 35.6 1.46 

UMZIMKULU 168 66,144 1,322 1,918 50.0 34.5 1.45 

EASTERN CAPE 6,019 2,082,160 53,422 64,667 39.0 32.2 1.21 

3.2.4. Public schools by size 

The table below analyses the different types of public school by school size. The 

small school analysis follows the broad thrust of the Department of Educations 

review of education resourcing that was described earlier. Small schools are 

however defined for the purposes of this report as being 300 or below. The rationale 

for this definition is discussed in the section below on infrastructure. Small schools 

across the different types of school exhibit the following characteristics: 

• Primary and Secondary Combined Schools: Only 7 of the grade R to 12 

combined schools are small. Nevertheless, these small schools show a very 

low LCR and LER. 

• Combined schools: Nearly one third of combined schools are small. Small 

schools have a very low LER for what are effectively ‘extended’ primary 

schools. LERs and LCRs for small combined schools are much lower than for 

large combined schools, indicating significant mismatching of resources. 

22


• Intermediate Schools: Two thirds of the small number of intermediate 

schools are small, with low LERs and LCRs. 

• Farm Schools are overwhelmingly small with only 7 farm schools having an 

enrolment of more than 300. LERs and LCRs in small farm schools are very 

low indeed. 

• More than two thirds of Full Primary Schools are small. LERs and LCRs, 

although both close to 30:1, do not differ as much from large schools, 

indicating a better resourcing across this type of school. 

Table 19: Indicators by type and size of school 2004 

Small School 

Enrolment 

Number of 


Average 

Enrolment 

Total 

Enrolment 


Classrooms 

Educators 

in Post 

LCR 

LER 

ECR 

Primary & Secondary 

Or less 300 7 254 1,779 94 77 18.9 23.1 0.82 

Combined Schools (All More than 300 55 649 35,675 979 1,081 36.4 33.0 1.10 

Grades) All Schools 62 604 37,454 1,073 1,158 34.9 32.3 1.08 

Or less 300 745 228 170,130 5,345 6,419 31.8 26.5 1.20 

Combined Schools More than 300 1,640 492 807,549 15,222 22,272 53.1 36.3 1.46 

(Grades R to 9) All Schools 2,385 410 977,679 20,567 28,691 47.5 34.1 1.40 

Or less 300 20 170 3,406 127 140 26.8 24.3 1.10 

Intermediate Schools More than 300 11 584 6,426 177 197 36.3 32.6 1.11 

(Grades 5 to 9) All Schools 31 317 9,832 304 337 32.3 29.2 1.11 

Or less 300 442 52 22,825 1,243 1,053 18.4 21.7 0.85 

Farm Schools (Mostly More than 300 7 432 3,024 82 90 36.9 33.6 1.10 

Primary Grades) All Schools 449 58 25,849 1,325 1,143 19.5 22.6 0.86 

Or less 300 1,199 163 195,744 6,180 6,594 31.7 29.7 1.07 

Full Primary Schools More than 300 502 616 309,364 8,384 8,463 36.9 36.6 1.01 

(Grades R to 7) All Schools 1,701 297 505,108 14,564 15,057 34.7 33.5 1.03 


Or less 300 325 105 34,012 1,441 1,254 23.6 27.1 0.87 

Schools (Grades R to More than 300 90 464 41,746 1,369 1,379 30.5 30.3 1.01 

3/4) All Schools 415 183 75,758 2,810 2,633 27.0 28.8 0.94 


Or less 300 26 210 5,451 279 200 19.5 27.3 0.72 

Schools (Grades 4/5 to More than 300 64 471 30,173 935 887 32.3 34.0 0.95 

7) All Schools 90 396 35,624 1,214 1,087 29.3 32.8 0.90 

Hospital Schools 8 72 578 15 16 38.5 36.1 1.07 


Or less 300 97 200 19,442 870 934 22.3 20.8 1.07 

Schools (Grades 8 to More than 300 309 729 225,265 6,214 7,538 36.3 29.9 1.21 


Or less 300 49 100 4,923 220 242 22.4 20.3 1.10 

‘Lower’ Secondary More than 300 5 471 2,355 64 72 36.8 32.7 1.13 

Schools (Grades 8-10) All Schools 54 135 7,278 284 314 25.6 23.2 1.11 

Or less 300 189 196 37,094 1,366 1,744 27.2 21.3 1.28 

Senior Secondary More than 300 228 549 125,198 2,815 4,012 44.5 31.2 1.43 

Schools (Grades 10-12) All Schools 417 389 162,292 4,181 5,756 38.8 28.2 1.38 

Museum School 1 1 1 1 3 1.0 0.3 3.00 

EASTERN CAPE 6,019 346 2,082,160 53,422 64,667 39.0 32.2 1.21 

23


• Nearly 80% of Junior Primary Schools are small. LERs again do not differ 

as greatly from large schools again showing better resourcing across the subsystem. 

• Just under 30% of the small number of Senior Primary Schools are small. 

LERs and LCRs are relatively low, especially for classrooms. 

• Full secondary schools are generally larger schools with only around a 

quarter defined as small. Small secondary schools however have very low 

LCRs and LERs. 

• Most of the small number of ‘Lower’ Secondary Schools are small with only 

5 schools having an enrolment greater than 300. Similarly to full secondary 

schools, LERs and LCRs are very low. 

• 45% of the Senior Secondary Schools are defined as small. The LER in 

small schools is again very low 

3.2.5. Out-of-age learners and efficiency 

The first section of this report drew attention to the detrimental impact of over and 

under-aged learners on national funding through the equitable share. The table 

below shows over and under-aged learners in the Eastern Cape in 2002 in each 

grade. All figures in this section are taken from the most recent detailed analysis of 

education indicators by EMIS 19 

Table 20: Percentage of learners enrolled in 2002 that were under-aged, 

appropriately aged and over-aged 

Under 

aged 

Appropriately 

aged 

Over 

aged 

Grade 1 21% 47% 32% 

Grade 2 15% 41% 43% 

Grade 3 16% 35% 50% 

Grade 4 16% 32% 52% 

Grade 5 17% 29% 54% 

Grade 6 19% 28% 53% 

Grade 7 20% 27% 54% 

Grade 8 19% 25% 56% 

Grade 9 18% 24% 59% 

Grade 10 18% 22% 60% 

Grade 11 19% 22% 59% 

Grade 12 21% 22% 57% 

Average 18% 29% 52% 

The figures show very high rates of out of age learners, and especially of over-aged 

learners. Over-age enrolment is especially large in high school as high rates of 

repetition in the earlier grades lead to a cumulative problem. The root cause of high 

numbers of over-aged learners is high repetition rates throughout the public school 

system. The graph below shows repetition rates by grade in 2002. 

19 EMIS: ‘Review of Education Indicators 2002’. 

24


Graph 1: Repetition rates by grade 2002 

25% 

Repetition Rate: Grades 1 - 12, 2002 

20% 

20% 22% 16% 

15% 

10% 

5% 

10% 9% 9% 

10% 9% 

7% 

6% 

8% 

12% 

0% 

G1 G2 G3 G4 G5 G6 G7 G8 G9 G10 G11 G12 

Repetition rates are lowest in the higher primary grades and highest in the high 

school grades. They are especially high in the FET grades throughout the province, 

which may indicate academically weaker learners deliberately being kept back by 

schools in and attempt to improve matric results. 

Table 21: Repetition rates by grade and education district 2002 

District G1 G2 G3 G4 G5 G6 G7 G8 G9 G10 G11 G12 Avg 

Bizana 11% 12% 12% 14% 15% 16% 13% 13% 13% 21% 25% 27% 16% 

Butterworth 9% 8% 9% 11% 11% 9% 8% 9% 8% 18% 20% 24% 12% 

Cofimvaba 12% 11% 10% 11% 12% 8% 8% 8% 7% 18% 22% 17% 12% 

Cradock 21% 15% 12% 14% 14% 10% 5% 8% 13% 18% 16% 14% 13% 

East London 10% 7% 6% 5% 5% 4% 4% 11% 17% 19% 25% 11% 10% 

Engcobo 14% 12% 12% 12% 10% 9% 9% 7% 7% 25% 29% 14% 13% 

Fort Beaufort 7% 5% 5% 5% 5% 4% 3% 11% 15% 17% 19% 15% 9% 

Graaff-Reinet 10% 4% 4% 5% 8% 6% 2% 3% 14% 21% 13% 3% 8% 

Grahamstown 6% 6% 5% 7% 4% 4% 3% 3% 16% 19% 16% 11% 8% 

Idutywa 9% 8% 8% 10% 8% 8% 7% 6% 6% 19% 16% 20% 10% 

KWT 12% 8% 8% 8% 6% 5% 3% 11% 18% 18% 23% 19% 12% 

Lady Frere 11% 9% 9% 12% 12% 7% 6% 9% 7% 22% 26% 14% 12% 

Libode 7% 9% 9% 11% 10% 9% 8% 6% 9% 20% 27% 31% 13% 

Lusikisiki 10% 12% 11% 12% 13% 10% 8% 9% 11% 30% 31% 29% 15% 

Maluti 10% 10% 10% 10% 10% 8% 7% 7% 6% 22% 26% 28% 13% 

Mt Fletcher 13% 11% 15% 14% 13% 9% 11% 10% 13% 20% 19% 12% 13% 

Mt Frere 13% 12% 13% 13% 12% 11% 10% 9% 11% 21% 18% 17% 13% 

Port Elizabeth 8% 4% 4% 4% 5% 4% 1% 4% 17% 19% 17% 2% 8% 

Queenstown 13% 10% 11% 11% 10% 9% 9% 11% 15% 21% 22% 17% 13% 

Qumbu 10% 10% 11% 11% 11% 9% 7% 7% 8% 20% 24% 22% 12% 

Sterkspruit 13% 11% 10% 14% 11% 8% 8% 11% 10% 18% 21% 26% 13% 

Uitenhage 10% 6% 4% 5% 5% 4% 1% 3% 13% 16% 13% 1% 7% 

Umtata 10% 9% 9% 9% 8% 7% 6% 5% 5% 17% 21% 15% 10% 

Umzimkulu 13% 13% 12% 12% 13% 8% 9% 8% 7% 27% 29% 19% 14% 

25


Repetition rates also vary tremendously across the province from a low of 7% in 

Uitenhage to a high of 16% in Bizana. Repetition rates in the FET grades are 

especially high in many of the former Transkei districts, with repetition at 30% in 

grades 10 to 12 in Lusikisiki. 

High repetition causes a number of problems. Firstly, high repetition creates a 

growing pressure towards large classes through the school cycle, as repeaters join 

the learners coming up from the previous grade, enlarging the class. This is one of 

the main reasons for especially high over-age enrolment in the higher grades. 

Secondly, high over-age enrolment can create serious social and management 

challenges in schools, as learners who are effectively young adults share the 

classroom with teenagers. 

By way of illustration EMIS reports that ‘a typical 18 year-old in a Grade 12 class of 

40 learners in an average Eastern Cape school is likely to be sharing the class with 9 

other learners aged 18, 8 learners aged less than 18 and 23 learners aged between 

19 and 25+. This no doubt makes for a problematic teaching and learning 

environment’. 20 

3.2.6. Conclusions on public school education in the Eastern Cape 

The Eastern Cape has inherited different schooling systems from the apartheid era 

education departments. Many of the challenges created by these systems have still 

to be effectively addressed. Specific issues that need to be highlighted are: 

• Combined schools and associated secondary schools form the largest single 

sub-system in the province. One of the defining features of this sub-system is 

mismatched levels of provisioning. While educator provisioning is adequate in 

most districts, with the possible exception of Pondoland, classroom backlogs 

are pervasive in the former Transkei. 

• The greatest numbers of educators in small schools is, in declining order of 

size, in combined schools, full primary schools, senior secondary schools, 

junior primary schools and farm schools. Large numbers of small schools in 

these types of schools create pressure for a large establishment through the 

prevalent low learner:educator ratios. 

• There is a wide variation in educator provisioning between small and large 

schools. Small schools typically show LERs in the range 20 to 25. The 

province needs to find ways to increase the average LER in small schools to 

avoid pressure to increase the educator establishment. 

• Out-of age enrolment and repetition is very high, especially in the former 

Transkei. As discussed at the start of the report, out of age enrolment has a 

detrimental effect on national funding through the ESF. High repetition is also 

a waste of scarce resources and inhibits teaching and learning in the 

classroom through large class sizes. 

The province has chosen to target a relatively favourable LER in its educator 

provisioning over the last few years. The 2004 declared educator establishment is 

67,124, which would give an LER of 31:1 if implemented, significantly below many 

20 EMIS: ‘Review of Education Indicators 2002’. p.46. 

26


other provinces. Person-to-post matching for this establishment is currently being 

completed. A number of points need to be made in relation to educator provisioning: 

• Educator provisioning has improved greatly in many districts and is at broadly 

acceptable levels in most of the province. 

• At the same time many districts in the former Transkei continue to have 

significant classroom backlogs with LCRs greater than 40 in most districts. 

• While non-personnel non-capital (NPNC) expenditure is analysed in more 

detail later in this report, it is plain from inter-provincial expenditure figures 

that the Eastern Cape is below average and well below the national target of 

R500 per capita. 

The Eastern Cape has attached a lower priority to addressing the classroom backlog 

or to providing learner materials in the classroom and school services, in comparison 

to relatively favourable levels of educator provisioning. Most of the districts in the 

former Transkei have a more favourable learner:educator ratio than the Western 

Cape. In the context of relative cuts in the provincial allocation to education and the 

current and future funding pressures set out at the start of this report, there is a clear 

case for reprioritising resources. 

4. PUBLIC SCHOOL EXPENDITURE IN THE EASTERN CAPE 

This section looks at recent expenditure on public schooling in the Eastern Cape for 

the past three complete financial years 2001/02 to 2003/04. Three key areas for 

educational performance are then discussed: personnel, learner support material 

and infrastructure, with special attention given to the factors driving expenditure. 

4.1. Public school expenditure – recent performance 

The table below sets out expenditure on public schooling under programme 2 by 

economic classification, modified to clearly identify the three main categories of 

personnel, non-personnel non-capital, and capital that will be analysed throughout 

the remainder of this report. Major items of important educational expenditure are 

clearly identified. Recent expenditure history highlights the following trends and 

issues to note: 

• Expenditure on public school education has grown in real terms in recent 

years, a fact already noted across the provinces. 

• Non-personnel non-capital expenditure has grown more rapidly than overall 

expenditure. 

• Capital expenditure has grown very rapidly in recent years, more than 

doubling from 2001/02 to 2003/04. 

• The proportion of public school expenditure on personnel has slightly declined 

from 92.3% in 2001/02 to 89.8% in 2003/04 as real budget increases have 

allowed a higher proportion of expenditure to be spent on non-personnel. 

• NPNC per capita has grown in recent years but is still well below the national 

target of R500 per learner. 

27


Table 22: Programme 2 Public Schooling Expenditure Performance 21 

2001/02 2002/03 2003/04 

R '000 % R '000 % R '000 % 

1. CURRENT PERSONNEL 6,535,511 92.3% 7,124,252 90.5% 7,834,363 89.8% 

Annual growth rate - Personnel 9.0% 10.0% 

2. NON-PERSONNEL NON-CAPITAL 352,820 5.0% 414,649 5.3% 471,778 5.4% 

Public school learner enrolment - EMIS 2,090,484 2,097,890 2,109,144 

NPNC per learner 169 198 224 

Annual growth rate - NPNC 17.5% 13.8% 

2.1. School Services 

Learner Support Material 220,566 318,108 254,972 

Learning Equipment 549 - 4,130 

Scholar Transport 3,580 

Water & Electricity 24,179 20,193 28,324 

Hire of Buildings 2,110 54 6,387 

Catering Services 19,001 15,190 18,192 

Security Services 952 

School furniture 1,960 548 11,271 

2.2. Professional Services 

Agency & Consultants Fees 25,317 20,337 32,466 

Maintenance and Adaptation of Buildings 11,241 21,213 36,671 

3. TRANSFERS (NON-CAPITAL) 2,412 0.0% 20,935 0.3% 19,880 0.2% 

Subsidies 1,246 20,023 19,880 

Bursaries 1,084 

4. CAPITAL 186,840 2.6% 308,893 3.9% 399,956 4.6% 

Annual growth rate - Capital 65.3% 29.5% 

Construction of Buildings 38,905 43,031 29,294 

Agency - Capital Buildings 155,721 243,209 368,722 

Miscellaneous 21 0.0% 5 0.0% 

TOTAL EXPENDITURE 7,077,604 100.0% 7,868,729 100.0% 8,725,982 100.0% 

Annual growth rate - total 11.2% 10.9% 

• In 2003/04 significant expenditure was made on learning equipment and 

school furniture for the first time in recent years. Expenditure on both items is 

still low, especially on learner equipment. 

4.2. Personnel expenditure 

This section analyses the main factors behind personnel expenditure in public 

schools, looking in detail at the operation of the educator post provisioning model. 

After implementation of the recently agreed public sector pay agreements total 

personnel expenditure in public schools for the current financial year 2004/05 is 

21 Figures are taken from the Eastern Cape Budget Statement 2004/05 and from FMS and BAS end 

of year expenditure control reports. Under a strict economic classification capital transfers would be 

allocated to transfers (capital) but have been allocated to capital to keep expenditure on the school 

construction programme together. Partly due to this reason, items do not reconcile with the totals by 

economic classification. Only expenditure items of direct importance to education in schools are 

highlighted, taken individually or together from the financial control reports. Items under the objective 

of education support services have not been highlighted. 

28


projected to be R8,525 million. This comprises 64,845 permanent educators in post 

(R8,216 million), 288 substitute educators (R22 million) and 4,708 school 

administrators and office based educators (R287 million). Determination of the 

educator post establishment and the filling of posts is clearly the key factor driving 

personnel expenditure in schools. 

4.2.1. The post-distribution model for educators 

The model that is commonly referred to as the ‘post provisioning model’ is in fact, to 

give it its’ full title, a ‘post distribution model for the allocation of educator posts to 

schools’. The model is summarised here with the full model attached as Appendix 2. 

The model is based on a simple principle that available posts are distributed among 

schools proportionally to their number of weighted learners. The basic formula for 

each school is therefore a simple ratio: 

P SCHOOL = P TOTAL x WL SCHOOL / WL TOTAL , where: 

P SCHOOL is the number of posts allocated to a school, 

P TOTAL is the total number of posts available for distribution, 

WL SCHOOL is the number of weighted learners of the school, and 

WL TOTAL is the total number weighted learners of all schools. 

The concept of a ‘weighted learner’ instead of an actual learner is used to enable 

schools to compete on an equal footing for posts. A series of factors increase the 

weighting of learners. The most important of these are: 

• The maximum ideal class size for a learning area and phase which is a 

target currently set at 35 for grades R to 4, 40 for grades 5 and 6, 37 for 

grades 7 to 9, and at different levels based on learning areas in grades 10 to 

12 (see below). 

• The period load of educators is set for a lower period load in the secondary 

school phases due to more complex time tables and subject combinations. 

Period loads are based on ‘average prevailing practices’ and are currently 

100% for grade R, 98% for grades 1 to 9, and 84% for grades 10 to 12. 

• The need to promote a learning area: More favourable LERs are provided 

for learning areas in grades 10 to 12, with most LERs below 30. Technical 

and artistic learning areas are given low LERs in recognition of the need for 

more direct tuition. This leads to a weighting for each FET phase subject 

known as a ‘subject learner weighting’. 

• Weighting by ‘subject-learners’ for grades 10 to 12: The total number of 

weighted learners in grades 10 to 12 are determined in respect of each 

examinable subject by multiplying the numbers of learners taking each subject 

with the relevant subject-learner weighting, then adding for each subject (up 

to six subjects for each learner) to give the total number of weighted learners. 

• Size of the school: A constant number of weighted learners is added to each 

school seen as providing for posts to deal with basic operations, irrespective 

of the number of learners in a school. This has the effect of distributing posts 

towards small schools on the basis that ‘the smaller a school the more difficult 

it is to manage with a certain LER and the more favourable it should be’. 

29


• Number of grades: It is ‘more complex to manage a school with a relatively 

large number of grades than a similar sized school with only a few grades’. 

Additional weighted learners are added for each grade in which learners are 

enrolled. 

• Combined schools: Further weighted learners are added for combined 

schools ‘to compensate for the management complexity of such a school’. 

• Medium of instruction: Further weighted learners are added for grades with 

more than one medium of instruction. 

• Poverty: The total number of weighted posts in each school is then adjusted 

by its poverty ranking. Up to 5% of all posts are set aside for poverty redress, 

with these redress posts distributed to posts using the same indices as the 

Norms and Standards for School Funding (NSSF). 

The calculation of weighted posts is a complicated exercise, requiring a special 

survey by EMIS each time a new establishment is declared and the use of a 

computerised model. Readers requiring a more detailed understanding of the 

distribution model are directed to its full description. 

The post distribution model only distributes the declared educator establishment. A 

separate process is followed to determine the total number of posts to be allocated, 

which is driven by both the budget and the target overall LER for the province. 

A calculation is made by the Department of the ‘pool’ of posts that can be afforded 

from the forthcoming budget. This calculation takes the total education budget and 

deducts or ‘top slices’ different elements of the budget. In sequence these elements 

are: 

• Funds for non-personnel. 

• Funds for administrators, managers and office-based educators. 

• Funds for non-school educators (such as FET colleges), in-school 

administrators, exam markers, ABET lecturers, etc. 

Funds available for educators in schools are derived by this process. The number of 

educators that can be afforded from these funds is dependent on the average cost of 

an educator, which is in turn affected by annual changes in salary and benefit 

conditions. 

The number of educators that can be afforded does not necessarily match the target 

establishment, which is in practice driven by the LER. The post declaration for 2004 

is 67,024 which corresponds to a LER of 31.6. Declaration of the educator post 

establishment in practice results from negotiation between the Department and the 

educator unions over these factors, with trade offs between the number of posts that 

the Department calculates it can afford, and the establishment that will produce a 

target LER. For the 2004 establishment for example the Department has contrasted 

an ‘affordable pool’ of 65,471 posts with the declared establishment of 67,074. 

4.2.2. Impact of educator post distribution in the Eastern Cape 

A number of the characteristics of the Eastern Cape schooling system combine to 

increase the number of weighted learners calculated by the model: 

30


• The large number of small schools in the province each of which receives 

additional weighted learners. 

• The high number of grades covered by many schools, which endows a school 

with further additional weighted learners, and; 

• The prevalence of combined schools which are given a further allocation of 

weighted learners. 

• Small secondary schools offering a large number of subjects produce a high 

subject-learner weighted enrolment in comparison to actual enrolment. The 

number of subjects offered by secondary schools does not vary greatly on 

average across the province, with most secondary schools offering 10 to 12 

subjects in the FET phase. This characteristic is exacerbated in senior 

secondary schools which are more likely to be small and which only cover 

grades 10 to 12 where the number of learning areas comes into operation in 

determining the calculation of weighted learners. Simply put, small secondary 

schools have a small number of learners taking a large number of subjects 

producing a high weighted learner enrolment. Intuitively, this is a necessary 

feature of the model as each subject ideally requires a dedicated educator to 

offer it. 

It is important to realise that although the schooling system in the province produces 

a large number of weighted learners, this does not automatically lead to declaration 

of a large establishment. The size of the educator post establishment is driven by 

both budget and the target for the overall LER. The characteristics of the schooling 

system do however lead to redistribution of posts towards small schools, combined 

schools and senior secondary schools, all of which is reflected in the data set out for 

the schooling system in section 3.2 above. 

It is also important to note that a combination of significant post redistribution 

towards small schools and a post allocation often driven by a target LER means that 

the LER in large schools will always be above the average LER for the province as a 

whole. 

The combination of a relatively favourable LER for the province overall, the features 

of the post distribution model, and the special characteristics of the Eastern Cape 

schooling system have clearly led to significant redistribution of educator posts in 

favour of small schools and the poorer ex-homeland areas. The operation of the post 

distribution model has therefore led to greater equity in educator allocation in the 

province. In the light of the analysis set out in section 3 however the time has come 

to ask if the manner in which educator post provisioning has been applied in practice 

is not now impeding the allocation of limited resources to equally vital priorities. 

4.2.3. Non-educator personnel in public schools 

Non-educator personnel in public schools perform a wide range of functions, 

including accounts, secretaries, cleaners, hostel staff and security. These functions 

are vital in ensuring the smooth operation and management of the school. In June 

2004 there were 4 316 staff in post performing these functions in the Eastern Cape. 

This translates to close to 2 support staff for every 3 schools, an insufficient level of 

provisioning for effective school operations. Three points should be noted: 

31


• Support staff are concentrated in relatively wealthy public schools. Poorer 

schools rely on teachers, volunteers or parents to perform administration and 

support tasks. 

• Unlike educators, there has been no redistribution of posts to poorer areas or 

schools. 

• Although figures have not been obtained, provisioning of non-educator 

personnel in schools is thought to be far lower in the Eastern Cape than in 

wealthier provinces, reflecting the greater ability of better-off schools to pay 

support staff from their own funds. 

There is in fact no formal establishment for non-educators in schools. National policy 

on the provisioning of non-educators is being finalised. The national Department of 

Education’s Action Plan for Basic Education emphasised the importance of better 

provisioning of support staff in schools and has called for policy to finalised. 22 

4.3. Non-personnel non-capital expenditure 

The analysis throughout this report has highlighted the importance of NPNC funding 

in the education process. This section examines provision of both learner support 

materials (LSM) and other support to schools and learners under NPNC 

4.3.1. Learner support materials 

Learner support materials (LSM) are one of the most vital components of educational 

resourcing in the classroom, and often one of the most neglected areas. The bulk of 

LSM in the Eastern Cape is provided through an annual order of textbooks and 

stationery targeted for delivery before the start of the school year. There are smaller 

supplementary ‘top up’ orders, mostly of stationery at other times in the year. The 

table below sets out the value of LSM per learner delivered in each district for the 

last three financial years. 

LSM is one of the main categories of NPNC provisioning covered by the Norms and 

Standards for Schools Funding (NSSF). It should therefore be allocated to schools 

based on their position in the poverty quintiles. This applies for both section 21 

schools that have been given delegated budgets and all other schools. The 

distribution shows significant redistribution towards poorer districts. Most schools in 

the former Transkei districts would be placed in the two poorest quintiles Q1 and Q2. 

The province is also doing well in meeting the norm of R100 per learner for LSM set 

in the NSSF for 2000. With average inflation of 6% since 2000, this norm was R120 

in 2003/04. Although the norm was not met overall in 2001/02 it was achieved in 

many of the poorer districts. By 2002/03 and 2003/04 the norm was met overall and 

was exceeded by between 25% and 50% in the former Transkei districts. 

The picture is even more favourable if all expenditure on LSM, including top up 

orders is taken into account. The expenditure figures for LSM in table 20 above may 

22 National Department of Education: ‘Plan of Action – Improving access to basic education for all’, 

June 2003, p.10. 

32


include some misallocation of expenditure from other items. Nevertheless, they 

indicate total LSM provision per capita of R106 in 2001/02, R152 in 2002/03 and 

R121 in 2003/04. The low figure for 2003/04 will be most probably due to unpaid 

bills. In the two previous years it is clear that the Eastern Cape has exceeded the 

norm set out in the NSSF. 

Table 23: Annual order LSM per capita by district - Rands 

District 2001/02 2002/03 2003/04 

BIZANA 103.31 120.58 174.46 

BUTTERWORTH 106.17 151.34 151.79 

COFIMVABA 114.11 115.18 142.35 

CRADOCK 103.37 89.48 103.08 

EAST LONDON 66.25 89.12 76.55 

ENGCOBO 105.18 115.71 136.12 

FORT BEAUFORT 122.70 250.31 130.42 

GRAAFF-REINET 76.22 65.24 95.75 

GRAHAMSTOWN 76.13 92.28 81.83 

IDUTYWA 91.10 120.77 169.84 

KING WILLIAMS TOWN 100.03 118.04 107.44 

LADY FRERE 105.19 130.09 150.57 

LIBODE 73.15 111.05 166.01 

LUSIKISIKI 99.45 157.23 178.03 

MALUTI 81.74 146.14 143.59 

MT FLETCHER 106.51 158.41 151.44 

MT FRERE 97.39 145.22 159.83 

PORT ELIZABETH 60.12 80.91 74.45 

QUEENSTOWN 113.00 105.41 106.81 

QUMBU 111.25 122.81 135.64 

STERKSPRUIT 133.12 137.86 118.75 

UITENHAGE 67.61 173.15 91.07 

UMTATA 105.92 260.98 145.10 

UMZIMKULU 95.52 179.67 146.72 

EASTERN CAPE 93.56 136.10 132.73 

4.3.2. Other recurrent support to schools 

Performance is far less favourable when turning to other items of recurrent support 

to schools. From table 22 it is clear that the Eastern Cape has prioritised most NPNC 

expenditure on LSM provision. Other expenditure has been directed, in order of 

priority, to maintenance and adaptation of buildings (although this will include 

expenditure more properly classed as capital expenditure), water and electricity, 

catering services and school furniture (which received significant funding in 2003/04 

for the first time in recent years). Very little was spent on learning and teaching 

equipment, a vital area in the classroom. 

The Department of Education’s review of education resourcing notes that this is a 

common problem to many provinces. ‘Both schools and PEDs report that the 

extensive attention and protection given to LSMs has resulted in a situation in which 

33


funding for LSMs is regarded as more adequate than funding for other nonpersonnel 

recurrent items in school, like electricity, minor repairs, and so on. The 

review continues to report that ‘there is a general sense in schools and amongst 

provincial planners that the school allocations are inadequate, at least in the bottom 

four quintiles. The arguments change somewhat for the fifth quintile owing to the 

enormously increased capacity of households to make private contributions’. 23 

There has been concern at the wide variations between provinces in school 

allocations under the NSSF, especially in the two poorest school quintiles Q1 and 

Q2, with far lower allocations in the poorer provinces. The Department of Education 

has responded by proposing a unified national school allocation for each quintile 

using a ‘resource targeting list’. 24 The average targets are R475 for 2005, R499 for 

2006 and R524 for 2007 with targets correspondingly higher in the two poorest 

quintiles Q1 and Q2. The Eastern Cape, and probably many provinces, is well below 

these targets. NPNC expenditure per capita in 2003/04 was R224. With a learner 

enrolment of close to two million the province will need to target a NPNC budget of 

close to R1 billion in the next few years to provide adequate recurrent school 

funding. The province will also need to move beyond LSM to target other recurrent 

support to schools. 

4.4. School Infrastructure 

This section briefly sets out the main school infrastructure backlogs that have been 

indicated throughout this report and discusses criteria for school buildings set by 

physical planning norms. 

4.4.1. Infrastructure backlogs 

The Physical Planning Directorate has devoted much attention in recent years to 

obtaining accurate information on the true extent of infrastructure backlogs in 

schools, including cleaning of data, the application of norms and criteria for physical 

infrastructure and investment in the Education Facilities Management System 

(EFMS) to improve the base for physical planning. They are targeting the elimination 

of all backlogs by 2010 and have recently drafted a five year Infrastructure 

Implementation Plan 2005-10 to meet this target. The plan targets total capital 

expenditure in all education institutions of between R600 to R650 million a year from 

2005/06 to 2008/09, falling to R283 million in 2009/10 as backlogs are eliminated 

The table below sets out a rough estimate of the cost of eliminating the backlogs at 

current prices, totalling R2,443 million. It does not include the cost of building 

laboratories and media centres. Eliminating the backlog over a longer ten year 

period would therefore cost R244 million a year at current prices. 

Expenditure on school infrastructure has risen rapidly in recent years to exceed 

these levels, from R187 million in 2001/02 to R400 million in 2003/04. The Eastern 

Cape has access to further off-budget funding from donors that supplements these 


public schools, March 2003, p.63. 

24 National Department of Education: National Norms and Standards for School Funding – Proposals 

for amendments, April 2004. 

34


resources. A maintenance and adaption budget has reached significant levels for 

the first time with expenditure rising from R11 million in 2001/02 to R37 million in 

2003/04, and projected to rise to R53 million by 2006/07. 

Table 24: School infrastructure backlogs 2004 

Numbers Unit Cost R mill 

Mud classrooms 5,991 125000 749 

New classrooms 12000 125000 1,500 

Water provision 1279 30000 38 

Toilet provision 842 15000 13 

Electricity provision 1924 25000 48 

Fencing 2171 25000 54 

Telephones 2935 14000 41 

Total 2,443 

4.4.2. Norms and standards for school planning 

The Directorate of Physical Planning has also developed a draft physical resource 

planning manual with criteria based on national norms but adapted to the Eastern 

Cape. Some of the most important criteria set out in the manual are: 

• The maximum classroom occupancy should be 40 learners per classroom for 

a primary school and 35 per classroom for a secondary school. If a small 

school has only one class in each grade this would define a small school as 

280 learners or less in the case of primary schools and 175 learners or less in 

the case of secondary schools. 

• The maximum school size should be 960 pupils in a primary school and 1,200 

pupils in a secondary school. 

• Criteria to consider in establishing a new school include: No school building 

yet established, overcrowding of schools in established communities, distance 

to travel to existing facilities, demographics of the area, condition of the 

existing school and land availability. 

• Amalgamation of schools should be considered: where low numbers are 

prevalent, by looking at the viability of schools in the area, considering 

curriculum issues (better diversity), and looking at schools that are not 

performing. 

• The manual also sets out formal processes for opening, closing and 

amalgamating schools. 

It is quite a challenge to set space norms for schools. Small schools exist 

unavoidably in many parts of the province and the structure of the schooling system 

will not change overnight. Nevertheless it is vital to have clearly defined criteria for 

school infrastructure and strong processes for school opening, closure and 

amalgamation. Communities understandably want a school close by, preferably in 

their immediate locality. In the context of the former homeland areas, with large 

numbers of small villages, the tendency for each community to have a school is one 

of the main pressures in the province creating small schools. 

35


5. IMPROVING QUALITY IN EASTERN CAPE SCHOOLS 

This section discusses potential realignment of the schooling system focusing on the 

issues identified in the earlier sections. 

5.1. Realignment and quality 

Data on the schooling structure of the province reveal three types of school that 

create pressure to increase the educator establishment: 

• Combined schools, especially small combined schools. 

• The associated senior secondary schools, especially small schools. 

• Small schools throughout the province, especially farm schools, full primary 

and junior primary schools. 

There is a strong case for realigning the public school system to address these 

issues by implementing a full primary (grades R to 7) and full secondary (grades 8 to 

12) system throughout the province. A number of educational benefits would be 

likely to result from this realignment of the schooling system. 


wide age spread within these schools, an especially important consideration 

with the continued high prevalence of over aged learners in schools. This 

would make management of these schools easier and contribute to social 

cohesion within the school. The quality of education in the new full primary 

schools in Transkei would increase over time. 














• Moving to a full secondary school system would therefore enable much better 

utilisation of educators in the former Transkei. Larger secondary schools 

would be able to ‘cluster’ resources, offering a wider subject choice and 

achieving economies of scale in providing much needed education resources 

such as computer labs, laboratories and media centres. Educators would be 

more effective and able to spend higher proportions of their time in the 

classroom. The quality of education in former Transkei secondary schools 

would, over time, increase tremendously. 

36


• Clustering resources in larger high schools would also support the effective 

introduction of a number of major policy initiatives. The introduction of the FET 

curriculum from 2006 in grades 10 to 12, geared to modern social and 

economic needs, requires effective resourcing with teaching and learning 

materials and equipment. Similarly, the e-Education policy will require all 

schools to be effectively using information and communication technologies 

(ICT) for learning by 2013. Resources for the implementation of both of these 

policies, which will especially impact high schools, can be provided and used 

more effectively in larger high schools. 

Table 25: No combined schools and small secondary schools – projected 

indicators by type and size of school 2004 


Enrolment 



Average 

Enrolment 

Total 

Enrolment 


Classrooms 

Educators 

in Post 

LCR 

LER 

ECR 


Or less 300 7 254 1,779 47 55 37.5 32.5 1.15 

Combined Schools (All More than 300 55 649 35,675 951 1,098 37.5 32.5 1.15 

Grades) All Schools 62 604 37,454 999 1,152 37.5 32.5 1.15 

Or less 300 0 0 0 0 0 0.0 0.0 0.00 

Combined Schools More than 300 0 0 0 0 0 0.0 0.0 0.00 

(Grades R to 9) All Schools 0 0 0 0 0 0.0 0.0 0.00 

Or less 300 20 170 3,406 91 105 37.5 32.5 1.15 

Intermediate Schools More than 300 11 584 6,426 171 198 37.5 32.5 1.15 

(Grades 5 to 9) All Schools 31 317 9,832 262 303 37.5 32.5 1.15 

Or less 300 442 52 22,825 571 652 40.0 35.0 1.14 

Farm Schools (Mostly More than 300 7 432 3,024 76 86 40.0 35.0 1.14 

Primary Grades) All Schools 449 58 25,849 646 739 40.0 35.0 1.14 

Or less 300 2,353 189 445,362 11,134 12,725 40.0 35.0 1.14 

Full Primary Schools More than 300 1,733 502 870,310 21,758 24,866 40.0 35.0 1.14 

(Grades R to 7) All Schools 4,086 322 1,315,672 32,892 37,591 40.0 35.0 1.14 


Or less 300 325 105 34,012 850 972 40.0 35.0 1.14 

Schools (Grades R to More than 300 90 464 41,746 1,044 1,193 40.0 35.0 1.14 

3/4) All Schools 415 183 75,758 1,894 2,165 40.0 35.0 1.14 


Or less 300 26 210 5,451 136 156 40.0 35.0 1.14 

Schools (Grades 4/5 to More than 300 64 471 30,173 754 862 40.0 35.0 1.14 

7) All Schools 90 396 35,624 891 1,018 40.0 35.0 1.14 

Hospital Schools 8 72 578 14 17 40.0 35.0 1.1 


Or less 300 0 0 0 0 0 0.0 0.0 0.00 

Schools (Grades 8 to More than 300 677 857 580,433 16,584 19,348 35.0 30.0 1.17 


Or less 300 0 0 0 0 0 0.0 0.0 0.00 

Junior Secondary More than 300 0 0 0 0 0 0.0 0.0 0.00 

Schools (Grades 8-10) All Schools 0 0 0 0 0 0.0 0.0 0.00 

Or less 300 0 0 0 0 0 0.0 0.0 0.00 

Senior Secondary More than 300 0 0 0 0 0 0.0 0.0 0.00 

Schools (Grades 10-12) All Schools 0 0 0 0 0 0.0 0.0 0.00 

Museum School 1 1 1 1 3 1.0 0.3 3.00 

EASTERN CAPE 5,819 358 2,081,201 54,183 62,334 38.4 33.4 1.15 

37


The table above shows the impact on the current system of three linked measures: 

• Realigning combined schools to full primary schools and distributing grade 8 

and 9 learners within the same district to senior secondary schools, enabling 

schools to become full primary and secondary schools. 

• Closing small secondary schools, defined as those schools that cannot 

expand to reach an enrolment of 300 or more. Almost all junior secondary 

schools would either close, or expand into grades 11 and 12 to become full 

secondary schools. Small secondary schools would have strong incentives to 

either expand or face closure. 

• Harmonising LERs and LCRs across small and large schools at the current 

space norms (LCR equal to 40 for primary schools and 35 for secondary 

schools) and to LERs of 35 for primary schools and 30 for secondary schools. 

Realignment of the schooling system along these lines would greatly reduce the 

pressures towards a large establishment with the following results: 

• A reduction in the required educator establishment from the current numbers 

of 64,667 in post (EMIS 10 th day return survey 2004) to 62,334 with a saving 

of 2,333 posts. The table below shows the annual savings from this educator 

establishment to be R290 million at current prices. This would release funds 

equivalent to a 44% increase in the 2004/05 non-personnel budget which 

could be reprioritised to teaching and learning materials, school services or 

building improvements. 

• Only a minor increase would result in the overall LER for the province from 

32.2 to 33.4, as small and large schools harmonise around agree space and 

post provisioning norms. 

Table 26: Impact of no combined and small secondary school post savings 

IMPACT 

Educator posts saved 

2,333Numbers 

Value of savings 

R 290R million 

Programme 2 Budget 2004/05 

Personnel 

R 8,267R million 

Non-Personnel Recurrent 

R 658R million 

Savings: Personnel 3.5% 

Savings:Non-Personnel Recurrent 44.1% 

The challenges of harmonising the schooling system around space norms and a 

slightly higher LER are significant. Very small schools with an enrolment of 100 or 

less, mostly primary schools, would find it difficult to organise teaching in class sizes 

of 35. Such schools are often farm schools serving a very small community or 

population catchment. Multi-grade teaching is usual practice in these schools. There 

are special challenges in multi-grade learning and proper training and support to 

teachers would be needed. 

Another result of this realignment would be a need for additional classrooms in 

secondary schools as they expand to become significantly larger schools and take 

additional learners. To set against this, the classroom backlog in combined schools 

38


would be reduced as existing classroom space would be spread over a smaller 

number of grades. The table below shows the classroom backlogs resulting from 

applying the space criteria of an LCR of 40 and 35 in primary and secondary schools 

respectively to the existing system, a no combined no senior secondary system, and 

a non combined no small secondary system. 

Table 27: Classroom backlogs under space norms for different school systems 


Combined Schools (All 

No Combined & No 

Small Schools 

No Combined 



Enrolment 

Or less 300 0 0 0 

More than 300 0 0 0 

Grades) All Schools 0 0 0 

Or less 300 0 0 0 

More than 300 0 2,202 4,967 

Combined Schools 

(Grades R to 9) All Schools 0 2,202 4,967 

Or less 300 0 0 0 

Intermediate Schools More than 300 0 0 0 

(Grades 5 to 9) All Schools 0 0 0 

Or less 300 0 0 0 


Farm Schools (Mostly 

Primary Grades) All Schools 0 0 0 

Or less 300 0 0 0 

Full Primary Schools More than 300 1,552 0 0 

(Grades R to 7) All Schools 1,552 0 0 


Or less 300 0 0 0 

Schools (Grades R to More than 300 0 0 0 

3/4) All Schools 0 0 0 


Or less 300 0 0 0 

Schools (Grades 4/5 to More than 300 0 0 0 

7) All Schools 0 0 0 

Hospital Schools 0 0 0 

Or less 300 0 0 0 


Schools (Grades 8 to 

Current Base 

More than 300 6,471 268 222 

12) All Schools 6,471 268 222 

Or less 300 0 0 0 


Junior Secondary 

Schools (Grades 8-10) All Schools 0 3 3 

Or less 300 0 5 0 

Senior Secondary More than 300 0 5,149 762 

Schools (Grades 10-12) All Schools 0 5,153 762 

Museum School 0 0 0 

ALL SCHOOLS 8,023 7,627 5,954 

39


The classroom backlog would increase from 5,954 to 8,023 in the fully realigned 

schooling system, an increase of 2,069 classrooms. At a current unit cost of 

R125,000 per classroom R259 million would be required. There would also be an 

associated though smaller infrastructure requirement for hostels, toilets and other 

buildings. It must be realised however that this would be a once off construction cost 

whereas post savings would be larger and would continue to accrue in each year. 

The additional cost of classroom construction could also be spread over multiple 

years and accommodated by reprioritisation of funding towards high schools within 

the existing rapidly rising capital budget. 

Options for realigning small primary schools were not considered in the analysis. 

Primary schools serve younger learners that are less likely to be able to travel longer 

distances to school or to stay in hostels. Primary schools are also much more rooted 

in particular communities than are secondary schools. A good schooling model 

would be: 

• Smaller primary schools grades R-7 based in communities close to learners, 

bringing the school to the learners. 

• Larger high schools grades 8-12 clustered in districts with boarding facilities, 

bringing the learners to the school. 

Nevertheless there is a further option for realignment that could be investigated, 

perhaps at a later date. Junior Primary Schools are a significant presence in the 

former Transkei covering up to grades 3 to 4. Many learners are 10 years or older at 

this point and could potentially stay in hostels or travel greater distances to school. A 

primary school sub-system of small junior primary schools feeding into larger 

clustered senior primary schools with hostels bears further investigation. 

5.2. Potential criteria for realignment 

EMIS has recently prepared a study on the reorganisation of very small schools with 

enrolment less than 100. 25 The schools were distributed throughout the province. 

The study found 847 schools with less than 100 learners. One significant finding was 

that 57% of schools had an adjacent school within 5km that could provide a place to 

transfer learners. Clearly there is significant scope for better use of resources by the 

realignment of small schools. 

The study suggests a series of criteria for realignment of small schools: 

• Are there any schools within a 5km radius that can accommodate the small 

school? 

• Does the school have sufficient classrooms to accommodate the new 

learners? 

• In what condition is the neighbouring school? 

• Can transport be provided for the learners, and if so – what will the costs be? 

• What will the social costs be when the small school closes? In a lot of cases 

the educators live in the community and attract money to the community 

25 EMIS: Preliminary investigative study on reorganisation of schools, August 2004. 

40


through his/her salary that is spent there. Will the closing of the school have a 

detrimental effect on the community at large? 

• Can the community afford not to have a school? 

• Although there might be a school within a 5km radius, is there a physical 

boundary that prevents learners from going to school? 

Some of these criteria are subjective and will be difficult to apply consistently. The 

information base is however increasingly in place for a systematic review of school 

location, size, infrastructure and educator provision that would prioritise scarce 

resources in viable schools to build up quality education. 

6. SCENARIOS FOR POST PROVISIONING 

Three scenarios for post provisioning have been prepared calculating the cost of the 

educator establishment, and calculating available resources for NPNC and capital, 

using a computerised simulation of the post provisioning model. The model projects 

the resulting changes in personnel expenditure in public schools under programme 2 

over the forthcoming MTEF period 2005/06 to 2007/08. The impact of this post 

establishment on the available non-personnel non-capital budget and capital budget 

in public schools is calculated. In this way the ‘crowding out’ of non-personnel noncapital 

from a higher post establishment can be modelled and vice-versa. Other 

scenarios can be tested using the model, but the three scenarios set out here are: 

1. No combined schools and no small secondary schools: The impact of 

recommended realignment of combined schools and senior secondary 

schools to a more conventional grades R-7 primary school and grades 8-12 

secondary school system. The closure of all small secondary schools defined 

as schools with an enrolment of 300 or less. The implementation of existing 

space and class norms of a learner:classroom ratio (LCR) of 40:1 in primary 

schools and 35:1 in secondary schools, and a learner:educator ratio of 35:1 in 

primary schools and 30:1 in secondary schools. This realignment process 

phased in over the next 3 year MTEF period. 

2. The current establishment of 67,074: Person-to-post matching is currently 

being completed for the 2004 declared post establishment of 67,124. This 

establishment is phased in over the forthcoming 3 year MTEF period and 

posts are filled up to this establishment 

3. A new establishment of 61,431: A post establishment of 61,431 is 

calculated from an average LER of 35:1. This establishment is phased in over 

the forthcoming 3 year MTEF period. 

Salary increases agreed in September 2004 in the bargaining councils are projected 

forward over the next 3 years. A key assumption is that the projected programme 2 

budget for the current year 2004/05 and the forthcoming MTEF period 2005/06 to 

2007/08 is fixed. Any increase in personnel expenditure must therefore be 

accommodated by a corresponding reduction in non-personnel expenditure and viceversa. 

Learner enrolment is assumed to stay unchanged over the period. 

41


6.1. Scenario 1: No Combined Schools or Small Secondary Schools 

This scenario simulates the impact of a three year phased introduction of the more 

conventional grade R-7 primary school and grade 8-12 secondary school system, 

coupled with the closure of small secondary schools of that cannot reach an 

enrolment of 300 or more. This system was described in section 5.1 above. It is 

important to note that small primary schools are not closed, but their LER and LCR 

are targeted to rise to the space and class norms set out. The impact of these 

structural changes is that the average LER would rise slightly from 32.2 to 33.4 and 

the LCR would fall slightly from 39.0 to 38.4 over the three year period. Permanent 

educator numbers fall gradually from the current in post numbers of 64,845 in 

2004/05 to a filled establishment of 62,505 in 2007/08. 

The impact of this scenario on the public school budget is set out in the table and 

charts below. It is a relatively favourable scenario, with both the size and relative 

proportion of the non-personnel non-capital budget rising to R943 million by 2007/08 

and stabilizing at between 8% to 9% of the total public school budget. At R450, 

NPNC per capita rises to close to the national target by 2006/07. Capital expenditure 

would stabilise at R306 million in 2007/08, close to the figure needed to eliminate the 

backlog over a ten year period. 

Table 28: Projected public school expenditure – no combined schools and no 

small secondary schools, R million 

2004/05 2005/06 2006/07 2007/08 

Educator numbers 64,845 64,065 63,285 62,505 

Personnel - R million 8,525 8,972 9,434 9,881 

Non-personnel non-capital - R million 504 780 946 943 

NPNC per capita 242 375 455 453 

Transfers 26 27 26 26 

Capital 312 319 307 306 

TOTAL BUDGET/EXPENDITURE 9,610 10,473 11,168 11,609 

Percentage personnel 89% 86% 84% 85% 

Percentage non-personnel 5% 7% 8% 8% 

Growth rate in personnel 5% 5% 5% 

Growth rate in non-personnel 55% 21% 0% 

Chart 2: Educator numbers – no combined schools and no small secondary 

schools 

Educator numbers 

65,500 

65,000 

64,500 

64,000 

63,500 

63,000 

62,500 

62,000 

61,500 

61,000 

2004/05 2005/06 2006/07 2007/08 

42


Chart 3: Percentage of the public school budget on personnel – no combined 

schools and no small secondary schools 

Percentage personnel 

92% 

91% 

90% 

89% 

88% 

87% 

86% 

2004/05 2005/06 2006/07 2007/08 

Chart 4: Percentage of the public school budget on non-personnel non-capital 

– no combined schools and no small secondary schools 

Percentage non-personnel 

10% 

8% 

6% 

4% 

2% 

0% 

2004/05 2005/06 2006/07 2007/08 

Chart 5: non-personnel non-capital (NPNC) per capita – no combined schools 

and no small secondary schools 

NPNC per capita 

500 

450 

400 

350 

300 

250 

200 

150 

100 

50 

0 

455 453 

375 

242 

2004/05 2005/06 2006/07 2007/08 

43


6.2. Scenario 2: The Current Establishment Of 67,074 

This scenario simulates the impact of a three year phased introduction of the 2004 

agreed establishment of 67,074, to which person to post matching is currently being 

completed. The average LER would fall from 32.2 to 31.0 over the three year period. 

Permanent educator numbers rise gradually from the current in post numbers of 



charts below. It would be a damaging scenario for education over the medium term, 

with both the size and relative proportion of the non-personnel non-capital budget 

falling after 2005/06 to R429 million by 2007/08, 4% of the total public school budget. 

Such a non-personnel non-capital budget would be completely insufficient to support 

quality education in the classroom through adequate provision of learner materials. 

NPNC per capita would fall to an unacceptable R206. Capital expenditure would fall 

to R139 million, insufficient to eliminate the backlog over an acceptable period. 

Table 29: Projected public school expenditure – current establishment of 

67,074, R million 

2004/05 2005/06 2006/07 2007/08 



Non-personnel non-capital - R million 504 638 544 429 



Capital 312 261 177 139 





Growth rate in non-personnel 27% -15% -21% 

Chart 6: Educator numbers – current establishment of 67,074 


67,500 

67,000 

66,500 

66,000 

65,500 

65,000 

64,500 

64,000 

63,500 

2004/05 2005/06 2006/07 2007/08 

44


Chart 7: Percentage of the public school budget on personnel – current 

establishment of 67,074 


94% 

93% 

92% 

91% 

90% 

89% 

88% 

87% 

86% 

85% 

2004/05 2005/06 2006/07 2007/08 


– current establishment of 67,074 

7% 

6% 

5% 

4% 

3% 

2% 

1% 


0% 

2004/05 2005/06 2006/07 2007/08 


– current establishment of 67,074 


350 

300 

250 

200 

150 

100 

50 

0 

307 

242 

262 

206 

2004/05 2005/06 2006/07 2007/08 

45


6.3. Scenario 3: A New Establishment Of 61,431 

This scenario simulates the impact of a three year phased introduction of the 

proposed 2005 establishment of 61,431. The average LER would rise from 32.2 to 

35.0 over the three year period. There would therefore be a similar, although greater 

impact, to the structural changes proposed in scenario 1. The principal difference 

between the two scenarios is structural. Without changes in the structure of the 

school system an average LER of 35:1 would lead to a significantly lower LER in 

small schools and a correspondingly higher LER, especially in primary schools. This 

is due to the distribution inherent in the post provisioning model towards small 

schools and secondary schools which have a greater number of learning areas. 

Permanent educator numbers fall gradually from the current in post numbers of 



charts below. It is a favourable scenario, with both the size and relative proportion of 

the non-personnel non-capital budget rising to R1,063 million by 2007/08 and to 10% 

of the total public school budget. By 2007/08 NPNC per capita would have risen 

above the NSSF target of R500 per learner. Capital expenditure would rise to R345 

million by 2007/08, sufficient to eliminate the backlogs over ten years. 

Table 29: Projected public school expenditure – new establishment of 61,431, 

R million 

2004/05 2005/06 2006/07 2007/08 



Non-personnel non-capital - R million 504 814 1,022 1,063 



Capital 312 333 332 345 





Growth rate in non-personnel 62% 26% 4% 

Chart 10: Educator numbers – new establishment of 61,431 


66,000 

65,000 

64,000 

63,000 

62,000 

61,000 

60,000 

59,000 

2004/05 2005/06 2006/07 2007/08 

46


Chart 11: Percentage of the public school budget on personnel – new 

establishment of 61,431 


92% 

91% 

90% 

89% 

88% 

87% 

86% 

85% 

2004/05 2005/06 2006/07 2007/08 

Chart 12: Percentage of the public school budget on non-personnel noncapital 

– new establishment of 61,431 


12% 

10% 

8% 

6% 

4% 

2% 

0% 

2004/05 2005/06 2006/07 2007/08 

Chart 13: Percentage of the public school budget on non-personnel noncapital 

– new establishment of 61,431 


600 

500 

400 

391 

491 

511 

300 

200 

242 

100 

0 

2004/05 2005/06 2006/07 2007/08 

47


7. CONCLUSIONS AND RECOMMENDATIONS 

7.1. Conclusions 

This study has established a number of findings from analysis of provincial and 

Eastern Cape public school indicators and expenditure: 

National and provincial funding for education 

• Following a difficult period of very limited available resources from 1997/98 to 

2000/01, the Eastern Cape has been able to significantly increase 

expenditure on public schooling in recent years, primarily due to high real 

growth above the rate of inflation in national to provincial transfers and in 

allocations to education within the province. 

• This trend is however unlikely to continue as the growth rate of transfers from 

national will decrease and population and enrolment trends are likely to give 

the Eastern Cape a declining share of national transfers to provinces. 

• Since 2001/02 rapidly increasing expenditure on social grants has decreased 

the share of expenditure on education and health in all provinces. The 

Eastern Cape has however reduced the share of expenditure on education 

more rapidly than in any other province, from 40,6% in 2001/02 to 34,7% in 

2003/04. 

• Capital expenditure on addressing school infrastructure backlogs and nonpersonnel 

non-capital spending on learning resources and school services are 

equally vital areas of spending to educator provisioning. It is important to 

maintain a balance between these three broad categories of expenditure. 

Prioritising resources in education 

• In comparison to other provinces the Eastern Cape has a favourable 

learner:educator ratio and a high learner:classroom ratio indicating high 

school infrastructure backlogs. The Eastern Cape is a province of small 

schools with the second lowest average enrolment per school in the country. 

• A favourable LER and a high LCR indicates a relative misallocation of 

resources between educator and classroom provisioning given limited 

funding. 

• The Eastern Cape has made a strategic choice to prioritise a low 

learner:educator ratio leading to relatively favourable educator post 

provisioning relative to other education resources. Other provinces have 

clearly set different relative priorities, enabling higher levels of resourcing for 

non-personnel non-capital and capital expenditure. 

• The Eastern Cape has attached a lower priority to addressing the classroom 

backlog or to providing learner materials in the classroom and school 

services, in comparison to relatively favourable levels of educator 

provisioning. Most of the districts in the former Transkei have a more 

favourable learner:educator ratio than the Western Cape. In the context of 

48


relative cuts in the provincial allocation to education and the current and future 

funding pressures set out at the start of this report, there is a clear case for 

reprioritising resources. 

• Pursuit of a low LER in the province has achieved the goal of relatively 

favourable post provisioning in most districts of the province. The time has 

now come to reprioritise resources in favour of other vital areas of the 

education process. 

Personnel, recurrent and capital expenditure 

• The large number of small schools in the province create a pressure to 

increase the educator establishment due to their low LERs. 

• The post provisioning model allocates posts especially to small schools, 

schools with a large number of grades and combined schools, creating 

pressure for a large establishment in the context of the Eastern Cape. 

• The province has been able to meet national norms in the provision of learner 

support materials (LSM). It is however below the average per capita spending 

on non-personnel non-capital expenditure per capita and well below draft per 

capita norms for NPNC. 

• Capital expenditure on school infrastructure has increased rapidly in recent 

years. Based on available figures the Eastern Cape will be able to meet its 

target of eliminating infrastructure backlogs over the next ten years. 

Realigning schools for quality education 

• There is a strong case for realigning the public school system to address 

these issues by implementing a full primary (grades R to 7) and full secondary 

(grades 8 to 12) system throughout the province. A number of educational 

benefits would result from this realignment of the schooling system. 


wide age spread within these schools, an important consideration with the 

prevalence of over aged learners in schools. This would make management 

of these schools easier and contribute to social cohesion within the school. 














• Moving to a full secondary school system would enable much better utilisation 

of educators in the former Transkei. Larger secondary schools would be able 

to ‘cluster’ resources, offering a wider subject choice and achieving 

49


economies of scale in providing much needed education resources such as 

computer labs, laboratories and media centres. Educators would be more 

effective and able to spend higher proportions of their time in the classroom. 

• Clustering resources in larger high schools would also support the effective 

introduction of a number of major policy initiatives. The introduction of the FET 

curriculum from 2006 in grades 10 to 12, geared to modern social and 

economic needs, requires effective resourcing with teaching and learning 

materials and equipment. Similarly, the e-Education policy will require all 

schools to be effectively using information and communication technologies 

(ICT) for learning by 2013. Resources for the implementation of both of these 

policies, which will especially impact high schools, can be provided and used 

more effectively in larger high schools. 

• More classrooms would be required in secondary schools to support 

realignment. The classroom backlog would increase from 5,954 to 8,023 in 

the fully realigned schooling system, an increase of 2,069 classrooms. At a 

current unit cost of R125,000 per classroom R259 million would be required. 

There would also be an associated though smaller infrastructure requirement 

for hostels, toilets and other buildings. This would be a once off construction 

cost whereas post savings would be larger and would continue to accrue in 

each year. The additional cost of classroom construction could also be spread 

over multiple years and accommodated by reprioritisation of funding towards 

high schools within the existing rapidly rising capital budget. 

Scenarios for post provisioning 

• Three scenarios of educator post provisioning were run. The scenario of 

realigning combined schools and senior secondary schools to a more 

conventional full primary and full secondary system, coupled with the closure 

of any small secondary schools that could not increase their enrolment above 

300, would achieve a balanced resourcing of public schools with a small 

increase in the overall LER for the province from 32.2 to 33.4. A lower 

educator establishment would produce significant savings of R290 million a 

year which could be allocated to other vital areas. It would also produce a 

higher quality education system over time. 

• Declaring a post establishment at a learner:educator ratio of 35:1 would 

produce greater savings from a reduction in the establishment. Resources 

could be prioritised to the under-funded are of NPNC spending on learning 

materials and school services, resulting in the targeted NPNC budget of R1 

billion (R500 per learner) necessary to meet draft norms and standards for 

school recurrent funding being met by 2007/08. 

• Implementing the 2004 post declaration of 67,074 would lead to a further fall 

of the LER to 31.6:1. If implemented it would also lead to a fall in the capital 

budget to R319 million and the NPNC budget back to R429 million (R206 per 

learner) by 2007/08, well below current levels. There would be a resulting 

serious impact on education in the classroom through insufficient funding for 

learning materials and school services and to address classroom backlogs. 

This would constitute a serious mis-prioritisation of limited available 

resources. 

50


7.2. Recommendations 

Resource planning and prioritisation 

The Eastern Cape needs to take a stronger and more proactive role in discussions 

over the national funding framework and the equitable share formula, or face a 

steadily declining relative allocation of national resources to the province. This 

requires developing fiscal planning and negotiation capacity in both the provincial 

Treasury and the Department of Education. 

Under the pressure of increasing expenditure on social grants the province has 

sharply reduced relative allocations to education over the last three years, more 

rapidly than in any other province. The province needs to find ways to increase the 

proportion of expenditure on education over the next MTEF period. 

The Eastern Cape Department of Education needs to target a better balance of 

funding between personnel, capital and non-personnel non-capital funding of 

learning materials and school services. Over the next MTEF period should 

progressively implement the third scenario set out in this report, which would result 

by the end of this period 2007/08 in: 

• An educator establishment of 61,431 giving an average learner educator ratio 

of 35:1 and 83% of total expenditure on personnel. 

• A non-personnel non-capital budget of R1 063 billion meeting draft norms and 

standards targets for recurrent school funding of R500 per learner. 

• A capital budget of R345 million giving sufficient funding to eliminate school 

infrastructure backlogs by 2013 and to build additional classrooms in 

realigned full secondary schools. 

In the current climate of overdrafts and limited financial resources this requires 

significant reprioritisation of funds within the province or access to new sources of 

funding. 

Post provisioning 

The Department of Education should declare an educator post establishment of 

61,431 for 2005 based on an overall LER of 35. The new establishment should 

however be phased in over the three years 2005-07 allowing for parallel 

implementation of recommended structural changes in the public school system. 

Realignment of schools for quality education 

One of the chief goals in this realignment of schools should be to release and 

reprioritise resources for quality education. The objective should be to bring and 

retain primary schools close to the learner, while at the same time bringing older 

learners to larger high schools, to board if necessary, and clustering resources to 

support the introduction of a high quality FET curriculum. Funding would be released 

for the learning materials necessary for quality education. 

51


Over the three year period 2006-08 combined, senior secondary and small 

secondary schools (less than 300 enrolment) should therefore be realigned from 

2006 onwards. Schools would realign to a full primary (grades R to 7) and full 

secondary (grades 8 to 12) system. This will entail the transfer of grade 8 and 9 

learners from combined schools to senior secondary schools during this period 

within their district. Secondary schools would be encouraged to increase their 

enrolment to at least 300 or face closure. The Department will need to prioritise the 

construction of just over 2,000 classrooms to convert senior secondary schools to full 

secondary schools during these 3 years. This can however be accommodated within 

the existing capital programme with reprioritisation of existing construction to the 

targeted schools. 

Finalise school planning criteria 

The information is present to finalise clear criteria to open new schools, close old 

schools and to amalgamate schools in the draft physical planning manual. Analysis 

of population growth or decline in communities, and the distance of learners from 

schools, is required to complete the picture. The Department should complete its 

school planning criteria in 2005 by investigating these areas. 

Learner to school matching 

In an analogous process to person to post matching the Department should conduct 

a ‘learner to school matching’ during 2005 to examine school planning and 

realignment. Building on existing EMIS work and school planning criteria a clear 

picture should be built up of: 

• Where small schools are and what are their characteristics 

• Where community populations are growing or declining and hence where 

communities are under-served or over-provided 

One of the key goals should be to identify small schools that will need to be retained, 

schools that can be amalgamated, and schools that are clearly non-viable and which 

need to be closed. The matching should be conducted in each district. 

52


REFERENCES 

Eastern Cape Province Budget Statement 2004/05 

Eastern Cape EMIS: Review of Education Indicators 2002. 

Eastern Cape EMIS: 

Department of Education: 


Preliminary investigative study on reorganisation of 

schools, August 2004 

Review of the financing, resourcing and costs of 

education in public schools, March 2003 

Improving access to free and quality basic 

education for all, June 2003 

Department of Education: Education statistics in South Africa 2001 

Department of Education: School Register of Needs 2000 


National Treasury: 

National Norms and Standards for School Funding 

– Proposals for amendments, April 2004 

Trends in inter-governmental finance - 2000/01 to 

2006/07, September 2004. 

National Treasury: Inter-Governmental Fiscal Review (IGFR) 2003, 

p.59. 

Statistics South Africa: Census 2001: Primary Tables Eastern Cape – 

Census 1996 and 2001 compared, 2003. 

Statistics South Africa: 

Mid-year population estimates for South Africa, 

July 2004 

53


APPENDIX 1 

COMPARATIVE ANALYSIS OF EASTERN CAPE EDUCATION 

SPENDING IN SCHOOLS 

1. BACKGROUND 

Since 2000/01 the Eastern Cape Department of Education has received 

progressively increasing budgets. A rapid review of education spending completed in 

March 2004 found that the Department has been able to devote increased funding to 

school education. The Department now wishes to conduct a detailed analysis of 

education spending in schools examining the main factors driving and affecting 

education spending, especially personnel expenditure. It is proposed that a 

consultant is contracted through the Imbewu 2 programme to conduct this analysis. 

2. TASKS 

Different factors affect education expenditure in schools at national and provincial 

level and within the Eastern Cape province itself. Analysis of the trends and the 

principal factors driving and affecting expenditure is needed. Analysis should be 

undertaken for the last three completed budget years for which final expenditure is 

available (2001/02 to 2003/04) and the current MTEF period (2004/05 to 2006/07), 

data permitting. 

2.1. National and provincial funding for education 

National government allocates funding to provinces based on an Equitable Share 

Formula (ESF). The education component of this formula is based upon the school 

age population and the proportion of that age group in school. Funding for education 

is however not solely determined by national allocations. Provinces have their own 

authority to determine budget allocations between different departments and, to a 

greater or lesser extent, their own sources of funding for allocation. 

The National Department of Education and National Treasury conduct ongoing 

analysis of provincial education expenditure. Drawing on this material and analysis 

by non-governmental organisations, a brief review should be conducted of trends in 

the funding allocated to education, to school education and in the school population 

and enrolment cost drivers. 

2.2. Factors driving school education expenditure in the Eastern Cape 

The principal task within the study is however the analysis of the main drivers of 

expenditure on school education within the Eastern Cape. As 88% of education 

expenditure was on personnel in 2003/04, expenditure on teachers and other staff in 

schools is a major focus. Analysis is required of the main elements within 

expenditure on school education in the Eastern Cape, especially those most crucial 

for school education. These elements are Personnel, Infrastructure, Learning 

Materials and Norms and Standards funding. The impact of expenditure on 

personnel backlogs on the available budget must also be analysed. Data at this level 

will only be available for the Eastern Cape and comparison with a small number of 

provinces, probably Western Cape. The following factors require detailed analysis. 

54


Personnel 

High personnel expenditure in schools risks ‘crowding out’ non-personnel on learner 

materials and other essential items. Detailed analysis is needed in the following 

areas: 

• Trends in expenditure on school staff, especially educators, and in the 

numbers of staff. 

• The impact of the post provisioning model for schools on personnel 

expenditure must be analysed in detail, in combination with the effect of 

school size and type (primary, secondary, combined) on personnel 

requirements. 

• The impact of personnel expenditure on available non-personnel funding in 

schools. 

• The impact of educator qualifications on personnel expenditure in schools. 

• Trends in Learner:Educator ratios both within the province and with respect to 

other provinces. 

• Linking to the post provisioning model, trends in the numbers of educators per 

school. 

Infrastructure 

Analysis is required of expenditure on school construction, upgrading and 

maintenance and their trends, together with Learner:Classroom and 

Educator:Classroom ratios and trends. 

Learner Materials 

Analysis is required of expenditure on Learner Materials, including per capita 

expenditure and trends. 

Norms and Standards 

Analysis is required of the allocations to Section 21 schools under the norms and 

standards for schools funding, including the allocations and expenditure per capita 

and trends. 

3. OUTPUTS 

The outputs from the study will be: 

• A detailed analysis of factors driving costs in school education in the Eastern 

Cape, especially personnel, compared with other provinces. 

• An analysis of the scope for reallocating or dedicating additional funding for 

education at national and provincial level. 

• Recommendations on the allocation of the resources for school education in 

the Eastern Cape, especially personnel, to increase education efficiency. 

4. SKILLS AND TIME REQUIRED 

A consultant with experience in education finance and economics, especially in the 

Eastern Cape, is required. Familiarity with the South African education system and 

experience with education data analysis will also be needed to undertake the study. 

It is estimated that 20 person days will be needed to complete the study. 

55


APPENDIX 2: POST DISTRIBUTION MODEL FOR THE ALLOCATION 

OF EDUCATOR POSTS TO SCHOOLS 

PRINCIPLES ON WHICH THE MODEL IS BASED 

1. The model is based on the principle that available posts are distributed among 

schools, proportionally to their number of weighted learners. 

2. The concept of “weighted learner”, instead of actual learner, is used to enable 

schools to compete on an equal footing for posts. As some learners and some 

learning areas require more favourable post allocations than others, each learner 

is given a certain weighting that reflects its relative need in respect of post 

provisioning. Other factors like the size of the school, the need to redistribute 

resources and the need to ensure equal access to the curriculum may require 

that additional weighted learners be allocated to some schools. A weighted 

learner enrollment for each school is determined, which, in relation to the total 

learner enrollment of the province, reflects its relative claim to the total pool of 

available posts in the province. 

FACTORS THAT ARE BEING TAKEN INTO ACCOUNT IN DETERMINING THE 

POST PROVISIONING NEEDS OF SCHOOLS AND LEARNERS 

3. Educational and administrative factors that impact differently on the post 

provisioning needs of learners and of schools for which specific provision is made 

in the model are the following: 

 

 

 

 

The maximum ideal class size applicable to a specific learning area or phase. 

This ideal maximum value also takes into account complicating factors that may 

apply, such as additional contact time required between educator and learner and 

the requirement to attend to learners in more than one place at the same time. 

Although the situation in South Africa is such that ideal maximum class sizes 

cannot be complied with, these ideal values form a basis of comparison between 

the requirements of all the learning areas and grades. 

Period load of educators. It is common practice that educators in the secondary 

school phases have a lower period load than educators in the primary school 

phases. This is mainly as a result of more complex timetables and subject 

combinations. A lower period load implies a more favourable overall learnereducator 

ratio. The norms used in this regard are based on average prevailing 

practices and do not represent workload policy. 

Need to promote a learning area. By providing a more favourable learnereducator 

ratio in respect of a learning area in grades 10 to 12, schools can be 

motivated to promote such a learning area. This may only be done in terms of 

national or provincial policy in this regard. 

The size of the school. The smaller a school, the more difficult it is to manage 

with a certain learner-educator ratio and the more favourable it should be. This 

matter is addressed by adding a certain constant number of weighted learners to 

each school. The constant additional number of weighted learners could be seen 

56


as providing for a school’s principal post, or for part of it, independently from the 

number of learners. It could also be seen as providing for posts to deal with 

certain basic responsibilities that each school has, irrespective of its size. 

 

 

 

 

The number of grades. Especially in respect of smaller schools, it is more 

complex to manage a school with a relatively large number of grades than a 

similar sized school with only a few grades. This matter is addressed by linking 

the additional number of weighted learners, referred to under the previous point, 

to the number of grades. A further increase in the number of weighted learners 

of a combined school is required to compensate for the management complexity 

of such a school. 

More than one language medium of instruction. In order to deal with this 

complicating factor, the number of weighted learners that is granted per grade in 

terms of the previous point, is increased if more than one language medium of 

instruction is used in the particular grade. A head of department may set a 

certain minimum number or percentage of the learners in a grade that must 

receive tuition in a second language before recognition is given in this way. 

Disabilities of learners. These learners require additional support from various 

categories of personnel. Norms in this regard still need to be determined. For 

the year 2003 a field-testing project will be conducted that will be aimed at 

determining norms with regard to the staffing of special and full-service schools 

and also incorporating schools with special/remedial/aid and/or pre-vocational 

classes, as well as district support teams. This project will be conducted in a 

number of districts where the allocation of posts will take place in accordance 

with the objectives of the field-testing project. In the other districts the status quo 

will remain for the time being. In order to manage the transformation and fieldtesting 

processes, all posts currently allocated to LSEN schools are to be topsliced 

from the pool of posts to be distributed by means of the post distribution 

model. Schools in districts where the field-testing will not take place will retain 

their current establishments unless circumstances require otherwise. The topsliced 

posts currently allocated to LSEN schools, as well as to other institutions or 

offices in the districts where the field-testing will take place will be allocated on 

the basis of criteria and outcomes of the field-testing process. 

Access to the Curriculum. In order to ensure affordable and fair access of 

learners to the curriculum, the numbers of learners that are fully funded in respect 

of subjects that are more expensive to offer need to be regulated. (Certain 

subjects are more expensive than others because they require smaller classes 

and/or special equipment and facilities.) A head of department, therefore, may 

identify specific schools at which the offering of such subjects should take place 

as well as the maximum number of learners at such schools that should take the 

subjects concerned. This means that a maximum number (or percentage) of 

learners may be set in respect of a particular subject at a particular school. 

Should a school exceed such a limit, the excess learners will be funded in terms 

of the norms applicable to the least expensive subject. It is possible that the 

maximum number of learners that will be counted as taking a particular subject at 

a particular school may be specified as zero even though such a subject was 

considered for post provisioning purposes in the past. This would mean that all 

57


such learners taking such a subject would be counted as if they are taking the 

least expensive subject for purposes of post provisioning. 

In order to assist a school to introduce such a subject, a certain minimum number of 

learners may be counted for post provisioning purposes during a phasing in period, 

even though the actual number of learners taking the subject is lower than this 

number. The implementation of these measures must be in accordance with a 

department’s policy on redress in the implementation and promotion of the 

curriculum. 

 

 

 

Poverty. In order to compensate for the negative impact that poverty has on 

learning, the poverty grading of a school is also taken into account. 

Level of funding. Policy may require that different phases be funded at different 

levels. Currently, all grades are set at a 100% funding level while Grade R is set 

at a funding level of 0%. This is merely a tool that could be used if and when 

required. 

Ad Hoc factors. Certain factors that are not considered above, such as an 

unexpected growth in learner numbers, may exist at a particular school and may 

justify the allocation of additional posts to such a school. These posts must be 

allocated from an additional pool of posts that need to be created for this 

purpose. 

WEIGHTING NORMS 

4. The following norms and principles will apply in respect of all learners: 

(a) Grades 1 to 9: 

Based on the principle that uniform curricula apply to learners in schools in all 

phases up to grade 9, the following formula is used to determine the weighting 

of a learner: 

c divided by the ideal maximum class size, divided by the average prevailing 

period load, multiplied by the funding level. 

(w = c/m/l x f) 

The value of c is set at 40 and refers to the highest ideal maximum class size 

in relation to which others are expressed. 

Grade Max Class Period load Funding Weight 

size (%) level 

(m) (l) (f) (w) 

R 35 100 0 0 

1 to 4 35 98 100 1,166 

5 to 6 40 98 100 1,02 

7 37 98 100 1,103 

8 to 9 37 88 100 1,229 

58


(b) Grades 10 to 12: 

 

 

In view of the variety of learning areas, each learner is weighted 

separately in terms of his or her curriculum. 

Within the limits of the maximum number of learners recognized for post 

provisioning purposes, a weighting (subject-learner weighting (slw)) is 

determined for each subject taken by a learner by means of the following 

formula: 

c (where c = 40) divided by the ideal maximum class size, multiplied by the 

promotion factor, divided by the average period load, multiplied by the funding 

level, divided by 7. The following norms apply: 

(slw = c/m x p/l x f/7) 

Subject 

Ideal 

maximum 

class size 

Promotion 

factor 

Period 

load (%) 

Funding 

level (%) 

(m) (p) (l) (f) 

All agricultural subjects with a practical component 16 1 84 100 

(Farm Mechanics, Animal Husbandry, Field 

Husbandry, etc.) 

All Technical subjects excluding Technical Drawing 16 1 84 100 

Technical Drawing 27 1 84 100 

Woodwork, Metalwork, Industrial Arts, etc. 25 1 84 100 

Home Economics, Needlework and clothing 25 1 84 100 

Hotel-keeping and Catering 19 1 84 100 

Art (Including Design, Painting, Sculpture, etc.) 12 1 84 100 

Dance (Ballet, etc.) 12 1 84 100 

Music (First Instrument) 6 1 84 100 

Music Performance (Second Instrument) 6 1 84 100 

Speech and Drama 12 1 84 100 

Biology 32 1 84 100 

Physical Science 32 1 84 100 

Mathematics 38 1 84 100 

Computer Studies 28 1 84 100 

Typing (Including Computyping) 28 1 84 100 

Shorthand/Snelskrif 28 1 84 100 

All other examinable subjects 38 1 84 100 

Provision for non-examinable subjects 38 1 84 100 

Note: The values that appear in the table as promotion factors are all set 

as 1. This means that no provision is made in the table for the promotion 

of any of these subjects. Should provision be made in policy that a certain 

subject should be promoted by, say 7%, the value of “1” would become 

“1,07”. The promotion factor per subject should be included in the 

provincial curriculum policy and would apply equally to all learners counted 

in the subject. 

 

A total number of weighted learners is determined in respect of each 

examinable subject by multiplying the number of learners taking the 

59


 

 

 

subject (subject-learners) with the relevant subject-learner weighting (slw). 

If a subject has a limit in respect of the number or percentage of learners 

that may take such a subject, all learners exceeding this limit will be 

subtracted from this number of subject-learners and added to the total 

number of subject-learners in respect of “all other examinable subjects”. If 

the actual number of learners taking a subject is lower than what is 

provided as a minimum in order to assist the school to phase in the 

particular subject, the provided minimum will be counted in respect of the 

subject concerned. The difference between the provided minimum and 

the actual number must be subtracted from the number of learners in 

respect of “all other examinable subjects”. A total number of weighted 

learners for all the examinable subjects is then determined. 

Each learner is allowed to take 6 examinable subjects. If the total value 

that is obtained by multiplying the number of learners in a particular grade 

by the number of subjects taken by these learners exceeds 6 times the 

number of learners, the total weighted learners will be adjusted 

accordingly. 

Provision is also made for a combination of non-examinable subjects, 

which, together, are given the same weighting as one “ordinary” 

examinable subject. A total number of non-examinable subject-learners is 

determined by multiplying the actual number of learners with the nonexaminable 

slw. This is done automatically, irrespective of whether or not 

learners at a particular school take non-examinable subjects. 

A total number of weighted learners is then determined by adding the total 

numbers of examinable and non-examinable weighted learners together. 

(c) 

A further distinction between schools is made based on the size of the school, 

the number of grades and whether or not more than one language medium of 

instruction is used. Provision for this is made by adding a certain number of 

weighted learners to a school’s weighted enrollment linked to each recognized 

language group (maximum of 2 language groups) and each grade provided 

for at the school. The following values apply: 

 

 

A base number of weighted learners must be added to each school. Any 

value from 10 to 20, in accordance with a department’s needs in this 

regard, will apply. A head of a provincial department must select a value 

that will ensure a proper balance in the allocation of posts to institutions of 

different sizes. 

Additional weighted learners must be added in respect of each grade in 

which learners are enrolled. If learners in a particular grade are taught in 

more than one language medium, a further additional weighting will apply 

in respect of that grade. (A minimum number (or percentage) of learners 

in a particular grade receiving tuition in a second language may be 

specified before the additional provision applies. This additional weighting 

only applies once, irrespective of the number of additional languages that 

may apply): 

60


Grades 1 2 3 4 5 6 7 8 9 10 11 12 

Primary 

language 2 2 2 2 2 2 2 3 3 3 3 3 

group 

Second 

language 

group 

4 4 4 4 4 4 4 6 6 6 6 6 

Any of the values in the table may be increased by a maximum of 2, provided that 

the head of a provincial department is satisfied that such an increase would lead to a 

more equitable allocation of posts. 

(d) 

In respect of a combined school, the base number of 10 to 20 weighted 

learners that is granted to a school in terms of paragraph (c), is granted in 

respect of both the primary school phase and the secondary school phase 

that the school has. For this purpose the secondary school phase must 

include learners in any of grades 10 to 12. 

5. (a) The total number of weighted learners in each school is then adjusted in 

terms of its poverty ranking. The head of a provincial department must set aside 

a certain percentage of its available posts for poverty redress based on the 

department’s relative level of internal inequality. The Minister may from time to 

time set the maximum percentage that provincial departments may use for this 

purpose. Until this limit is revised, it is set at 5%. 

(b) The redress posts are to be distributed to schools based on the relative 

poverty of the learners of a school, using an appropriate index within the 

framework of the indices utilized by the province in the National Norms and 

Standards for School Funding. The basis on which the redress posts are to 

be distributed among schools is as follows: 

School quintiles 

Poorest 20% 

Next 20% 

Next 20% 

Next 20% 

Least poor 20% 

Allocation from redress pool of posts 

35% of posts 





DISTRIBUTION FORMULA 

6. After the total number of weighted learners for each school has been determined, 

the number of posts to be allocated to a school is determined by means of the 

following formula: 

Posts = Total number of posts available, multiplied by weighted learners of 

school, divided by total weighted learners of all schools. 

61


PHASING IN OF THE MODEL 

7. The total effect that the implementation of the model has on the post allocations 

to individual schools should be phased in over a reasonable period. In phasing in 

the effects of the model, heads of departments should take into account all 

relevant factors that apply. These factors include the importance of maintaining 

stability in schools, the employment interests of educators and the need to 

provide classrooms, equipment and other facilities that schools require in terms 

of their curricula and their numbers of learners and posts. 

COMMUNICATION OF NEW POST ESTABLISHMENTS WITH SCHOOLS 

8. Where a school’s establishment is likely to change in any school year, the 

adjusted post establishment should, as far as possible, be communicated to the 

school on or before 30 September preceding the school year. 

ROLE OF THE NATIONAL DEPARTMENT OF EDUCATION (DOE) 

9. Provincial departments are required to adhere to the intent and spirit of these 

norms. Where a province deviates from any of these norms it needs to justify 

such deviation to the DOE. The DOE may require information from time to time 

from provinces in order to ensure that these norms are being implemented. 

Provinces are thus required to comply with these requests. 

TRANSITIONAL ARRANGEMENT 

10. For the 2003 school year, departments must communicate final or interim staff 

establishments of schools on or before 1 January 2003. 

62

A Comparative Analysis of Education Expenditure in Eastern Cape Schools

School Community Integration Pilot Project - Department of Education

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