Description
The total population is expected to grow by 32 percent between 2010 and 2020. Over the same period, the under 15 years age-group will remain constant at 44.2 percent of the total.
Regional Bureau
for Education in Africa
Tanzania
Beyond Primary Education, the Quest for Balanced and Efficient
Policy Choices for Human Development and Economic Growth
EDUCATION SECTOR ANALYSIS
EXECUTIVE SUMMARY
SN/2012/ED/PI/1
The findings, interpretations, and conclusions expressed in this volume do not necessarily reflect the views of the
Executive Director of UNESCO or the Government of Mainland Tanzania.
SN/2012/ED/PI/1
Tanzania
Beyond Primary Education, the Quest for Balanced and
Efficient Policy Choices for Human Development
and Economic Growth
EXECUTIVE SUMMARY
EDUCATION SECTOR ANALYSIS
Regional Bureau
for Education in Africa
Tanzania Education Sector Analysis 4
Acknowledgments
This Education Sector Analysis was prepared through a close collaborative effort by the
government of Tanzania, the Pôle de Dakar (UNESCO/BREDA), the UNESCO Institute of
Statistics, and the UNESCO Dar es Salaam cluster office.
The government team consisted of staff from the different ministries in charge of education,
led by the Ministry of Education and Vocational Training (MoEVT), as well as other ministries
and departments, including the Ministry of Community Development, Gender and Children
(MCDGC), the Ministry of Finance and Economic Affairs (MoFEA), the Prime Minister’s Office
for Regional Administration and Local Government (PMO-RALG), the National Examinations
Council of Tanzania (NECTA), the National Council for Technical Education (NACTE), the
Tanzania Commission for Universities (TCU), the Vocational Education and Training Authority
(VETA), the National Bureau of Statistics (NBS) and the Bureau for Educational Research and
Education of the University of Dar es Salaam (BERE/UDSM), which was instrumental in
facilitating all theoretical workshops.
The government team was successively led by Cyprian Miyedu, former Chief of the
Monitoring and Evaluation (M&E) Section, Department of Policy and Planning of MoEVT,
the late George Maliga, Chief of the M&E Section of MoEVT, and Muhwela Kalinga, Acting
Chief, M&E Section, under the overall leadership of Professor H.O. Dihenga, the Permanent
Secretary of MoEVT. Related administrative issues were handled by Mr Malili and Ms Levira.
For Chapters 1 and 3, the government ESA team consisted of Ms Baitwa (Chapters head,
Budget and Finance Division, MoEVT), Ms Elinzu (NBS), Mr Kitali (PMO-RALG), Ms Luena
(EMIS, MoEVT), Mr Minja (Administration and Personnel, MoEVT), Mr Mtyama (MoEFA), Ms
Omolo (TMC-DPLO/LGA Temeke District Council) and Mr Zullu (Administration and
Personnel, MoEVT). Mr Pambe (Chapters head, Primary Education, MoEVT), Ms Kiisheweko
(TCU), Ms Levira (Adult Education, MoEVT), Mr Maiga (Adult Education, MoEVT), Mr
Mchunguzi (Higher Education, MoEVT), Ms Sigwejo (NACTE), Mr Saro (FDC, MCDGC) and
Mr Wilberforce (EMIS, MoEVT) constituted the government team for Chapters 2 and 5. The
team for Chapter 6 included Mr Mhagama (Chapter head, VETA Division, MoEVT), Mr
Misana (Technical Education, MoEVT), Mr Malili (Higer Education, MoEVT), Mr Mwakapalala
(NBS), Mr Ndamgoba (FDC, MCDGC), Mr Petro (EMIS, MoEVT) and Mr Sunday (MIS,
MCDGC). The government team for Chapters 4, 7 and 8 was composed of Mr Mwenda
(Chapters head, Secondary Education, MoEVT), Mr Gabriel (LGA Bagamoyo, PMO-RALG),
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Tanzania Education Sector Analysis 5
Mr Kinunda (Higher Education, MoEVT), Mr Nzoka (Teacher Training, MoEVT), Mr Mbowe
(NECTA), Ms Mrigo (Administration and Personnel, MoEVT), Mr Pambe (Primary Education,
MoEVT), Mr Ponera (EMIS, MoEVT) and Mr Shauri (Primary Education, MoEVT). Chapter 7
received additional inputs from staff from the Inspection Department of MoEVT.
The Pôle de Dakar (UNESCO/BREDA) team consisted of Borel Foko (Team Leader, Education
Policy Analyst) and Diane Coury (Education Policy Analyst), under the overall guidance of
Jean-Pierre Jarousse (former Head of the Pôle de Dakar) and Mohammed Bougroum (Head
of the Pôle de Dakar). Inputs were also provided by Pôle’s members, Alain Patrick Nkengne
Nkengne, Mireille Harivola Ravelojaona and Ibrahima Dao.
The team received constant support from the UIS team of the UNESCO Dar es Salaam cluster
office, which consisted of Marc Bernal (UIS Regional Advisor for Eastern and Southern
Africa), Criana Connal (former EMIS Programme Specialist) and Erick Makoye and Abdulatif
Min-Hajj (IT specialists). Special thanks are due to Marc Bernal and Criana Connal who
provided strong support and facilitated the policy dialogue throughout the process.
The UNESCO Dar es Salaam cluster office was also instrumental in the effective elaboration
of the ESA. The team would particularly like to thank Min Jeong Kim (Education Programme
Specialist) who helped complete the process and Flora Rusenene and Rahma Islem for their
constant administrative support. Special thanks are due to Barnaby Rooke for the editing
work and Regis L’Hostis for the graphic design.
The team received valuable comments from the peer reviewers Criana Connal, Jean-Pierre
Jarousse, Jean-Marc Bernard, Agripina Habicht, Monica Githaiga, and Joseph Vere, as well
as from the development partner groups led by Corey Huntington (Canadian High
Commission).
The preparation of this report was funded by the Education Management Information
System (EMIS) Programme, financially supported by multiple donors, under the
administrative responsibility of the UIS/UNESCO-Dar es Salaam cluster office, and by the
Pôle de Dakar (UNESCO/BREDA).
Tanzania Education Sector Analysis 6
Foreword
T
his education sector analysis (ESA) for mainland Tanzania is a detailed analytical
document that offers a comprehensive picture of mainland Tanzania’s education
sector. The main purpose of an ESA (also known as Country Status Report, or CSR)
is to provide an evidence-based diagnosis of an education sector, to enable
decision-makers to orient national policies. It also provides relevant analytical
information to nourish the dialogue between the government and education sector
stakeholders, including development partners. In the current development context, marked
by the necessity for countries to develop sound, sustainable and credible strategies and
plans in which education is embedded, ESAs represent a valuable and essential tool.
This is the second ESA for Tanzania; the first one having been conducted in 2001. Although
its main objective is to provide a comprehensive picture of the education system in 2009
(the last year for which statistics were available), it also provides some analysis of the
evolution of the system over the decade, when feasible and relevant. This second report is
also more than an update. It provides more in-depth analysis on certain aspects of the
system: detailed unit costs by subsector, external efficiency, quality and out-of-school, and
technical education and vocational training and higher education in particular. It provides
key monitoring and evaluation inputs on the education sector as a whole, that are
particularly valuable in the framework of the implementation of the Education Sector
Development Programme.
This 2011 ESA was carried out between February 2009 and November 2010 by a multi-
ministerial national team with the support of the Pôle de Dakar (UNESCO/BREDA) and the
UNESCO Institute of Statistics. It was part of the activities conducted under the Education
Sector Management Information System (ESMIS) Programme,
1
one goal of which is to
support the development of capacities in data analysis using data generated by the ESMIS
and other sources to strengthen sector-wide planning and policy reforms. The ESA process
contributed to the strategy for building capacities in data analysis through a combination
of: (i) learning-by-doing, through a series of workshops, and (ii) theoretical training sessions,
offered in parallel to the workshops by the Bureau of Educational Research and Evaluation
of the University of Dar es Salaam (BERE/UDSM), based on the SAMES
2
materials provided
by the Pôle de Dakar.
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Tanzania Education Sector Analysis 7
The analyses presented in this ESA were made possible by using existing data and
information from multiple sources, and more particularly: school administrative surveys
conducted by the Ministry of Education and Vocational Training (BEST, TCU and NACTE
data); household budget, labor force, demographic and health surveys conducted by the
National Bureau of Statistics; and SACMEQ data on learning achievements, including
examination data from NECTA. Macroeconomic data and government finance statistics were
provided by MoFEA, and specific data were made available from VETA and the HESLB.
Obtaining timely (household surveys, SACMEQ, and payroll data) and reliable key data (EMIS
data were fraught with flaws) was a major constraint that has heavily limited the scope of
some analyses. Nevertheless, some important conclusions have been reached, both on the
achievement front, and on the major challenges faced by the education system.
The 2011 ESA has highlighted some interesting achievements, including:
• Sustained economic growth and greater public resources have translated into a relatively
higher education budget. The government spent 4.3 percent of GDP on education in
FY 2008/09 (from a low 2.5 percent in FY 2000/01), much more than countries with
similar levels of development. Education has also been given high budget priority. The
sector benefited from 26.5 percent of recurrent government expenditure after debt
service in FY 2008/09, well above the African low-income countries’ average of 21.4
percent;
• Tanzania is on track to achieve the millennium development goal of universal primary
education. Access is almost universal and the primary completion rate is close to 90
percent. The fee-free primary education policy has had a positive impact by boosting
both access and retention. Tanzania’s preprimary gross enrollment ratio is close to 37
percent, compared with just 20 percent on average for comparable African countries.
Tanzania’s administration of this level, using similar teaching approaches as for the
primary cycle and similar school premises, has helped to lower unit costs and increase
enrollment;
• Enrollment has increased for all cycles, and particularly in higher education, allowing
Tanzania to rapidly catch up with the levels of comparable developing countries: in 2009,
the number of higher education students in Tanzania was 36 percent lower than the
average, down from 50 percent in 2006. This trend is likely to continue as a direct
consequence of the expected development of secondary education;
• The Tanzanian higher education and TVET sectors are well positioned to adequately
manage the development and diversification of supply. Existing policies and regulatory
bodies provide a sufficient, solid and modern institutional framework for the system to
build upon for its future development;
• Education has a significant impact on social and human development, particularly on
literacy, poverty, fertility, and maternal and child health. Primary education is the level
that has the greatest impact on social outcomes: it contributes to almost 60 percent of
the total impact, which further reinforces the justification for sustained efforts to ensure
that all Tanzanian children complete at least the primary cycle; and
• Education responds to labor market needs. Greater levels of education lead to higher
incomes. The wage premium for workers with secondary education is particularly
significant, suggesting that there is a severe shortage of individuals with secondary
qualifications. There is also a strong connection between vocational training and
graduates’ employment. In general, the income of VET graduates compares favorably
with that of self-employed individuals with primary education or O-Level secondary.
The 2011 ESA also points to key challenges in the coming years for the development of the
education sector in Tanzania, including:
• Achieving greater efficiency gains (or implementing cost-saving strategies) in the use of
public education resources. Indeed, it is unlikely that the current level of budget priority
given to the education sector will be maintained over the next decade, due to competing
demands by health, agriculture and infrastructure;
• Increasing the public resources allocated to secondary education. Tanzania’s secondary
cycle receives 35 percent less funding than countries who are equally close to achieving
universal primary education. This situation should be carefully reviewed to avoid
affecting quality as the sector expands. Secondary schools already display high pupil to
teacher ratios (49 to 1);
• Ensuring children enter primary school at the right age. Approximately 13 percent of
primary school-aged children were still out of school in 2006, 88 percent of which had
never attended. Although poverty is a constraint, age appeared to be the main reason
for nonattendance. Late primary entry is common (only 36 percent of Standard I
students were of official school age
_
seven years
_
in 2006) and is known to have a
detrimental impact on schooling paths;
Tanzania Education Sector Analysis 8
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• Improving access to and retention in secondary cycles. Although considerable
improvements in access to secondary school have been noted, especially at O-Level,
they are still limited. In 2009, half of children had access to O-Level and 23 percent were
able to reach the last grade of the cycle, up from just eight percent in 2003. A-Level
access is still strikingly low, at five percent. Whereas lack of supply is a major hindrance
to O-Level and A-Level access, economic difficulties and cultural issues among certain
population groups also contribute to fragile school demand. The policy to have a
secondary school in each ward has had a very positive impact on secondary access and
on primary retention rates;
• Supporting pro-poor schooling. Important disparities in access exist according to gender
and area of residence, and they increase with successive levels of education, but the
most discriminatory factor in schooling patterns is families’ level of income. It has also
been shown that households’ contributions to education are still significant at the
primary level (equivalent to a quarter of public resources), despite the fee-free primary
education policy. Furthermore, disadvantages tend to be cumulative. Poor rural girls face
the worst access and retention conditions;
• Taking affirmative action to enhance girls’ participation in school to ensure gender parity
at postprimary levels. Insistence on girls fulfilling their traditional role in society, early
marriage and pregnancy all favor dropout. Trends could be reversed by: (i) awareness
raising campaigns to sensitize parents on the value of educating girls beyond primary,
and on the negative impact of early marriage and pregnancy on schooling and female
health; (ii) greater numbers of female teachers and the provision of community-based
hostels to avoid girls the long journeys to and from school, addressing security concerns;
and (iii) scholarships and cash transfers targeting bright girls, reducing direct and
opportunity costs, mirroring the government’s programme targeting the most talented
primary graduates from poorer backgrounds;
• Improving pedagogical management to raise the quality of basic education. Although
the improvement dynamic observed in primary education learning outcomes between
2000 and 2007 is very encouraging, and better than in neighboring countries, learning
achievements are still modest by international standards. In addition, national
examination pass rates are dropping, and the results of those who graduate are low,
especially at primary and O-Level;
• Reducing disparities between regions, districts and schools, that persist despite
decentralization, highlighting the need for effective planning and monitoring tools to
allocate education inputs more efficiently. A decentralized information and monitoring
system could help by providing decision makers with timely, accurate and reliable data on
the education sector. In addition to an EMIS system, financial and human resource
management systems would improve fiscal management and accountability. A first
response to this challenge was given in 2009, with the development of a pilot decentralized
Basic-Education Management Information System (BE-MIS). Tested in 28 district councils
in 14 regions, the BE-MIS is to be scaled up to all councils nationwide by 2014; and
Tanzania Education Sector Analysis 9
• Adequate planning of TVET and higher education expansion. The increase in primary
and secondary school enrollments is already placing much strain on secondary, TVET
and higher education institutions. An urgent response is required to ensure the smooth
and manageable development of these subsectors.
The challenges faced by higher education are of particular importance:
• It is essential that funding mechanisms be improved. Higher education is blatantly
inefficient, paying little attention to potential economies of scale. In addition,
approximately 28 percent of the level’s budget is devoted to badly targeted social
expenditures, particularly loans transferred directly to students: 48 percent of students
benefit from a loan, yet less than 10 percent come from the poorest quintiles, which
calls for an improvement in the loan targeting mechanisms; and
• Students’ career objectives and the distribution of graduates by subject area must be
adjusted, to achieve better relevancy of higher education programmes to the labor
market and enable Tanzania to keep abreast of rapid technological development and
needs. Science subjects in particular attract too few students (only 24 percent of
students for the 2007/08 academic year, down from 34 percent in 2003/04). Adequate
analytical tools should be implemented, such as labor market tracer surveys.
Technical education and vocational training will also be key to Tanzania’s development.
Some of the key required actions that this ESA highlights for the subsector include:
• Strengthening the subsector’s coordination mechanisms. Although regulatory and
quality assurance bodies provide important guarantees for the controlled development
of the TVET subsector, it still faces a series of challenges, including: (i) the diversity of
training demand linked to the heterogeneity of the target population; (ii) the institutional
fragmentation of technical education, under the umbrella of various ministries; (iii) the
fragmentation of vocational education and training service delivery, involving two
ministries and a parastatal agency; and (iv) the practical continuity between vocational
and technical curricula and programmes, although theoretically bridges do exist, as
defined by the national qualifications’ framework;
• Revising subsector budget trade-offs. The Tanzanian TVET system as a whole is not as
underfunded as in many other African countries. However, technical nonhigher
education absorbs almost 57 percent of all TVET resources, against just 37 percent for
vocational training, and six percent for folk education. This funding imbalance should
be reduced in order to scale-up vocational education and training activities; and
Tanzania Education Sector Analysis 10
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• Defining a funding formula to rationalize the allocation of resources among technical
institutions. Surprisingly, it has been noticed that planning and welfare courses are twice
as expensive as health and allied science courses. However, even for a given subject
area, and among institutions with comparable levels of enrollment, variations in the
resources allocated are sizeable. This situation merits an improved funding formula and
for more coordination in planning and budgeting among parent ministries.
More broadly, this ESA offers valuable and comprehensive resources to anyone interested
in the education sector in Tanzania. It is however a snapshot of the system at a particular
time. As the sector makes progress in implementing its sector plan, this report’s findings
are therefore likely to become outdated, although many features will remain valid. It is the
hope of both the Ministry of Education and development partners that this document will
be of use to all stakeholders in the education sector.
Tanzania Education Sector Analysis 11
Dr. Shukuru
Kawambwa (MP)P)
Minister of Education and
Vocational Training
Tanzania
Vibeke Jensen
Director
and Representative
UNESCO Dar es Salaam
Office for Comoros,
Madagascar,
Mauritius, Seychelles
and Tanzania
Ann Therese Ndong-Jatta
Director
Regional Bureau
for Education in Africa
UNESCO
1 The Education Sector Management Information System (ESMIS) Programme is implemented by the government of Tanzania with
the financial and technical support of development partners (the European Union, UNESCO, UNICEF, and UNFPA), within the
overall framework of the Education Sector Development Programme for 2008-17. The UNESCO Institute of Statistics is providing
technical assistance through its permanent Dar es Salaam cluster office.
2 The Sectoral Analysis and Management of the Education System (SAMES), also known as the PSGSE (Politiques Sectorielles et
de Gestion des Systèmes Educatifs) is a masters degree offered by the University Cheikh Anta Diop of Dakar (Senegal) with the
support of the Pôle de Dakar, targeting Ministry of Education staff and other actors working in the field of education in Africa.
The training is currently available in French. An English course is currently under development with the University of The Gambia.
For the purpose of this ESA, all training modules were translated into English and made available to BERE.
Tanzania Education Sector Analysis 12
Abbreviations
A
b
b
r
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v
i
a
t
i
o
n
s
ACSEE
AE/NFE
BE-MIS
BERE
BEST
BREDA
CBET
COBET
CSEE
ESA
ECCD
EMIS
ESMIS
FDC
GDP
GER
IIEP
ILFS
HBS
HESLB
HLI
LGA
LIC
MCDGC
MoEVT
MoFEA
Advanced Certificate of Secondary Education Examination
Adult Education and Nonformal Education
Basic Education - Management Information System
Bureau of Educational Research and Evaluation
Basic Education Statistics in Tanzania
Regional Bureau for Education in Africa
Competence Based Education and Training
Complementary Basic Education in Tanzania
Certificate of Secondary Education Examination
Education Sector Analysis
Early Childhood Care and Development
Education Management Information System
Education Sector Management Information System
Folk Development College
Gross Domestic Product
Gross Enrollment Rate
International Institute for Educational Planning
Integrated Labor Force Survey
Household Budget Survey
Higher Education Student Loan Board
Higher Learning Institution
Local Government Authority
Low-Income Country
Ministry of Community Development, Gender and Children
Ministry of Education and Vocational Training
Ministry of Finance and Economic Affairs
Tanzania Education Sector Analysis 13
MRY
NACTE
NBS
NECTA
NGO
PEDP
PMO-RALG
PSLE
PTR
SACMEQ
SADC
TCU
TDHS
TE
TVET
UDSM
UIS
UNESCO
VET
VTC
Most Recent Year
National Council for Technical Education
National Bureau of Statistics
National Examinations Council of Tanzania
Nongovernmental Organization
Primary Education Development Plan
Prime Minister’s Office - Regional Administration and Local Government
Primary School Leaving Examination
Pupil to Teacher Ratio
The Southern and Eastern Africa Consortium for Monitoring Educational Quality
Southern African Development Community
Tanzania Commission for Universities
Tanzania Demographic and Health Survey
Technical Education
Technical and Vocational Education and Training
University of Dar es Salaam
UNESCO Institute of Statistics
United Nations Educational, Scientific, and Cultural Organization
Vocational Education and Training
Vocational Training Center
Executive Summary
1. In a context of high demographic pressure, Tanzania has mobilized important
public resources to adequately address the growing demand for education.
The total population is expected to grow by 32 percent between 2010 and 2020. Over the
same period, the under 15 years age-group will remain constant at 44.2 percent of the total.
The primary school-aged population (seven to 13 years) is projected to reach 10.2 million by
2020, corresponding to an additional 1.8 million children compared with 2009.
Tanzania Education Sector Analysis 14
The government has given high budget priority to the education sector: in FY 2008/09,
education was allocated about 26.5 percent of government recurrent expenditure after debt
service, higher than the East African Community average (25.1 percent), and than the other
African low-income countries’ average (21.4 percent). In terms of GDP, the increase is
significant: from 2.5 percent of GDP in FY 2000/01 to 4.3 percent of GDP in FY 2008/09, a
value that is also higher than the average for all African low-income countries (3.3 percent).
Population (million)
Annual Growth Rate (%)
Sex Ratio (number of boys per 100 girls)
Population Under 15 Years (% of total)
Urban Population (% of total)
Demographic Trends and Projections, 1967-2020
12.3
n.a.
95.2
—
6.4
34.4
3.0
96.0
46.5
23.1
43.2
2.9
96.9
44.4
26.3
Census-Years
1967 2002 2010 2020
NBS-Projections
57.1
2.8
98.6
44.2
29.7
2000/01
2004/05
2008/09
Percentage of Actual Public Expenditure Allocated to Education
—
16.6
6.1
—
1.19
0.56
—
20.4
18.2
Recurrent
Expenditure
Development
Expenditure
Total
Expenditure
% of Total
24.3
23.3
26.5
% of Total,
(after debt)
2.5
3.1
4.3
% of GDP % of GDP % of Total % of GDP
—
4.3
4.9
Source: NBS data and projections (NBS, 2006; URT, 2005); and authors’ estimates.
Source: Authors’ calculations based on Tables 1.3, 1.4, 1.5 and 1.6.
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y
• Improved government capacities to mobilize significant resources directly from national
income. This has indeed allowed domestic revenues to increase from 9.2 percent of
GDP in FY 1998/99 to 15.9 percent of GDP in FY 2008/09. It is imperative that the
government supports this favorable trend in domestic revenue collection, to reduce
its dependency on foreign aid, which has represented almost 40 percent of total public
resources since FY 2002/03.
2. The allocation and use of public education resources is still not optimal however.
The increase in recurrent public education expenditure has been followed by significant changes
in subsector allocations. Over the decade, the share of primary education (including preprimary
education) has decreased from 58 percent to 48 percent, a level similar to that of other
countries close to achieving universal primary education. Most primary education savings have
benefited higher education, whose share of resources has increased to 27 percent of the total
education budget, making the subsector one of the best financed among African countries.
Secondary education continues to be heavily underfunded. In 2008/09, it absorbed 13.5
percent of education public resources; a level far below countries that are equally close to
achieving universal primary education.
Tanzania Education Sector Analysis 15
500,000
450,000
400,000
350,000
300,000
250,000
200,000
1
9
9
8
2
0
0
0
2
0
0
2
2
0
0
4
2
0
0
6
2
0
0
8
2
0
0
9
*
*
2
0
1
0
*
*
2
0
1
4
*
*
1
9
9
9
2
0
0
0
2
0
0
2
2
0
0
4
2
0
0
6
2
0
0
8
2
0
0
9
*
*
2
0
1
0
*
*
2
0
1
4
*
*
Constant 2001 T Sh
GDP per Capita Annual GDP Growth Rate
9.0
8.0
7.0
6.0
5.0
4.0
3.0
2.0
Percent
GDP Trends (FY) 1998/99-2008/09 and Projections
Source: Based on Table 1.3.
Note: **Projections.
Along with the high budget priority given to the education sector, this positive evolution
was also made possible following:
• Impressive and sustained economic growth registered over the last decade. Over the
2000-08 period, the average annual economic growth rate was estimated at 7.1
percent, a higher figure than the African low-income countries’ average, of 6.2 percent.
This trend is likely to strengthen given that average GDP per capita (about US$ 565 in
2010) remains lower than the African low-income countries’ average (US$ 800).
Tanzania Education Sector Analysis 16
This situation has led to a sharp 50 percent reduction in public spending per student at the
secondary level, while it has increased in all other subsectors. The Tanzanian secondary unit
cost is only two-thirds of the African LIC average, while the higher education unit cost (the
average for university and higher technical education) is 20 percent higher. While the
government’s strategy to expand secondary education is not matched by current budget
trade-offs within the sector, options to increase secondary education funding must be
explored to ensure the quality of the service delivered is not harmed. Although it may not be
possible to reallocate funds from higher education to secondary, the government should look
for efficiency gains and/or potential cost-saving measures within the higher education sector.
The TVET system is better funded than in many African countries, receiving seven percent of
public education resources, against five percent on average for the latter. However, main
allocation issues stem from funding imbalances amongst its different subsectors. Indeed,
while technical nonhigher education absorbs almost 57 percent of all TVET resources,
vocational training receives just 37 percent, against a low six percent for folk education. This
funding imbalance should be reduced in order to scale-up vocational education and training
activities. For technical education, the high level of randomness in resource allocation among
institutions is a problem, that is mainly linked to striking unit costs in specific programs.
Source: Tables 3.2 and 3.3 and authors’ calculations based on MoFEA and EMIS data for Tanzania; and Pôle de Dakar/UNESCO-
BREDA for other countries.
Note: * Based on countries with similar primary school duration (7 years) and closer to UPE; ** Based on countries with similar secondary
school duration (7 years) and closer to UPE; *** Based on the averages of all African low-income countries for which data were available.
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Primary
Secondary
TVET
Technical Nonhigher
VETA
Folk Education
Higher Education
University Education
Technical Higher
Other
Preprimary
Teacher Training
Adult and Nonformal Education
Total
Mainland Tanzania (2008/09) Comparable African Countries’ Average
Comparison of the Allocation of Public Recurrent Education Expenditure,
by Cycle, Tanzania and Selected African Countries’ Average, 2006 or MRY
44.2
13.5
7.0
4.0
2.6
0.4
26.9
23.6
3.4
8.3
4.5
2.5
1.3
100.0
43.6
26.3
5.0
—
20.8
—
4.8
—
100.0
*
**
***
***
***
The way resources are used highlights potential room for improvement. Indeed, evidence
shows that:
• Basic education focuses too little on spending that directly improves the quality of the
service delivered;
• In secondary education, capitation grant spending is 40 percent lower than the norm,
and student meals absorb four times as much of the budget;
• Teacher training colleges also overspend on student meals, to the tune of 90 percent
of nonsalary expenditures;
• Preprimary and primary pupil to teacher ratios are excessively high, partly because high
salaries constitute a constraint to further recruitment. Secondary PTRs are also well
above par, due to a quantitative and qualitative shortage of teachers; and
• In higher education, social spending is excessive (28 percent of higher education unit
costs not including scholarships for study abroad), and inequitable (almost 48 percent
of students receive a loan, although less than 10 percent are from the poorest quintiles).
3. Households and the private sector contribute considerably to the cost of
schooling, at varying degrees according to the level of education.
Households contribute significantly to education funding; their spending is equivalent to 32.1
percent of public education expenditure. This is however comparatively lower than in other
LICs (48 percent on average). Despite the fee-free primary policy, household contributions
remain important: a quarter of primary public education costs are covered by households.
This raises some concern as for the poorest households, as it might be a major obstacle to
send their children to schools. At the higher education level, the cost-sharing mechanism
seems to be effective, reducing the government’s financial burden. But its effectiveness over
the long run will very much depend on the capacity of the HESLB to recover loans.
Tanzania Education Sector Analysis 17
Secondary Education Public Unit Costs, (FY) 2000/01 - 2008/09
280
260
240
220
200
180
160
140
120
100
2
0
0
0
/
0
1
2
0
0
1
/
0
2
2
0
0
2
/
0
3
2
0
0
3
/
0
4
2
0
0
4
/
0
5
2
0
0
5
/
0
6
2
0
0
6
/
0
7
2
0
0
7
/
0
8
2
0
0
8
/
0
9
T
S
h
(
’
0
0
0
s
)
136
269
248
Thousands of Constant 2008/09 T Sh
Source: Authors’ calculations based on MoFEA and BEST and EMIS data.
Tanzania Education Sector Analysis 18
International Comparison of Household Spending on Education, by Level, 2009 or MRY
Percentage Equivalent of Public Recurrent Education Expenditure
Primary Secondary Higher/Tertiary Average
90
80
70
60
50
40
30
20
10
0
48
32
30
53
83
21
41
26
Mainland Tanzania
African LICs
The role of the private sector varies greatly across sectors. On the one hand it is marginal at
the preprimary and primary levels (where expansion has mainly been supported by the public
sector), and decreasing at O-Level and to a lesser extent at A-Level, following the government’s
policy of increasing secondary access. On the other hand, the expansion of the teacher training
and higher education subsectors increasingly relies on cost-sharing, favoring the development
of private sector contributions. In 2009, 39 percent of students were enrolled in private Teacher
Training Colleges, against five percent in 2004. In technical education, all folk development
courses are government-run, but those delivered through vocational centers are increasingly
private, reflecting the ministry’s policy of diversification to promote the subsector.
Source: Table 3.5 for Tanzania; Rwanda CSR, 2010 and Brossard et al., 2008 for 17 African low-income countries.
Note: 18 African low-income countries are considered here: Benin, Burkina Faso, Cameroon, Chad, Congo, Côte d’Ivoire, Djibouti,
Guinea Bissau, Madagascar, Malawi, Mali, Mauritania, Niger, Rwanda, Senegal, Sierra Leone, Togo and Uganda.
Source: BEST, NACTE, TCU, various years; authors’ computations for Tanzania. World Bank and Pôle de Dakar/UNESCO-BREDA for
other countries.
Note: * Refers to NACTE-registered institutions.
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Preprimary
Primary
O-Level
A-Level
Teacher Training
Technical Education *
VET (VTC Long Courses)
Higher Education
Share of Students Enrolled in Nongovernmental Institutions, 2004-09
Percent
1.3
0.6
38.0
48.6
5.4
—
—
7.4
2.3
1.0
26.6
38.6
9.3
15.5
67.8
19.4
7.8
1.3
14.2
36.4
23.7
16.2
—
23.9
Tanzania
2004 2006 2008 2009 2009 or MRY
Average LIC
5.0
1.5
10.8
32.3
38.6
—
—
28.2
—
16.7
20.4
27.7
—
—
—
19.5
Tanzania Education Sector Analysis 19
4. School enrollment has increased at all levels.
The preprimary sector is comparatively well developed. The policy to mainstream the provision
of preprimary teaching through primary schools (thus controlling unit costs) has enabled a
growing number of young children to benefit from this level. Coverage at the preprimary level
reached 37 percent in 2009, up from 26 percent in 2004. This is a very reasonable level of
preschool attendance compared with the 20 percent average of other countries in the region.
Source: Table 2.1, and census projections for Tanzania.
Note: * TVET includes VTC and FDC long courses, and nonhigher technical education; ** Higher education includes universities,
university colleges and higher technical education.
Tanzania is on the way to reaching universal primary education, but late entry still remains
a major challenge and many children are still out of school. Access to Standard I is almost
universal, although 5.5 percent of children did not have access to primary school in 2006.
The primary completion rate has steadily increased over the past decade, to reach at least
89 percent in 2009. The fee-free primary education policy and extensive classroom
construction have had positive impacts on both primary access and retention levels. The
system is still marked by considerable late entry however: only 36 percent of Standard I
students were of official school-age in 2006.
Source: DHS, 2004; HBS, 2000/01 and 2007; authors’ computations.
Age at Standard I
P
e
r
c
e
n
t
1.0 0.4
5.0
3.8
11.0
17.0
22.6
36.0
23.0
30.7
22.0
19.0
20.5
14.0
17.0
11.8
9.0 9.0
5.1
2.0
5.0
3.0
2.0
5.0
2.1
1.0
Age Distribution of Standard I New Entrants, 2000, 2004 and 2006
Percent
5 6 7 8 9 10 11 12 13+
40
35
30
25
20
15
10
5
0
2000
2004
2006
3.0
2003
2004
2005
2006
2007
2008
2009
Preprimary Primary
Secondary
O-Level
GER (%) Per 100,000 inhabitants
A-Level All
TVET *
Higher
Education **
Schooling Coverage, by Level, 2003-09
Percent, and Students per 100,000 inhabitants
—
26.3
29.3
29.8
34.4
36.7
36.6
104.5
109.5
113.1
115.9
117.6
115.4
112.4
10.5
12.8
15.2
19.0
28.3
33.0
38.6
1.9
2.2
2.3
3.0
3.4
3.6
3.9
7.8
9.5
11.2
14.0
20.5
23.8
27.7
—
—
—
235
—
252
250
—
—
—
174
—
291
335
Tanzania Education Sector Analysis 20
This situation tends to inflate out-of-school statistics. Indeed, among the 925,000 estimated
out-of-school (representing 13 percent of primary school-aged children in 2006), 88 percent
had never attended. Should all children enter on time, the number of children estimated to
never attend school would drop to 425,500. Given its detrimental impact on schooling
paths (exposing them to greater risk of early dropout), ensuring that children attend school
at the correct age should be a priority. MoEVT may address both supply and demand
constraints, for instance through sensitization campaigns to alter parents’ perceptions about
the appropriate age for school attendance, assisted further by the expansion of ECCD
programmes.
School coverage at secondary and higher education levels is still low compared with other
African countries, but is rapidly increasing, especially at the higher education level. School
coverage is particularly low at A-Level, where only four out of 100 school-aged children
were enrolled in 2009, one of the lowest rates of all African low-income countries. The
situation is less problematic at O-Level, for which the GER reached 39 percent in 2009, up
from a low 10.5 percent in 2003.
Considerable emphasis has been put on higher education, to adequately meet the growing
demand from secondary school leavers and produce skills relevant to current and future
economic growth. University enrollment has grown at an average annual rate of 30 percent
over 2005-09, among the highest annual growth rates registered for all subsectors (although
it started with lower enrollment), allowing Tanzania to rapidly catch up with the levels of
comparable developing countries. In 2009, the number of higher education students in
Tanzania was 36 percent lower than the average, down from 50 percent in 2006. However,
university and technical higher education coverage remains low, at 335 students per 100,000
inhabitants in 2009/10, against 381 students per 100,000 in other low-income countries.
Source: Table 2.8 for Tanzania; World Bank and Pôle de Dakar/UNESCO-BREDA for other countries.
Note: To allow for international comparisons: * TVET includes VET and FDC long courses and NACTE-registered technical nonhigher
education; and ** Higher education includes universities, university colleges and technical higher education.
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Tanzania (2008)
Burundi
Kenya
Rwanda
Uganda
East African Community Average
African Low-income Countries
Average
Min – Max
Preprimary Primary
Lower
Secondary
GER (%) Per 100,000 inhabitants
Upper
Secondary
TVET * Higher
Education **
International Comparison of Enrollment, by Level, 2008 or MRY
Percent, and Students per 100,000 inhabitants
36.7
5.4
54.0
18.0
3.7
23.5
20.4
0.8 – 141
115.4
115.3
114.7
151.0
120.7
122.8
103.1
56.9 – 157.7
33.0
22.9
94.6
28.0
28.1
42.4
43.4
15.9 – 94.6
3.6
6.0
39.6
9.0
10.3
13.7
17.2
2.6 – 39.6
252
156
74
440
115
212
228
35 – 484
291
243
359
474
329
337
381
61 – 1009
Tanzania Education Sector Analysis 21
TVET education coverage in Tanzania is higher than in other low-income countries (250
students per 100,000 inhabitants in 2009, compared with 228 students per 100,000).
Seventy percent of TVET students are registered on vocational courses (in VTCs and FDCs),
whereas 30 percent are in nonhigher technical learning streams. The sector still falls short of
the huge needs in TVET programmes for primary and secondary school leavers. The current
annual flow of students into vocational education represents less than five percent of the
potential demand for VET services, while technical nonhigher education covers about 22
percent of potential demand. This underlines the urgency for the diversification of TVET
provision, offering more short and tailor-made courses to enhance productivity and the quality
of products and services.
The number of teacher trainees has increased over the decade, with the exception of the
2007-08 period that registered a decrease in TTC trainees (places were more limited as a
result of the extension of the curricula from one to two years in 2006). However, given the
growing demand for teachers at all levels, the pursuit of the expansion of teacher training is
to be closely monitored and planned, so as to not jeopardize the development of the primary
and secondary school system.
Literacy programmes cover just a quarter of the target population. Similarly, COBET
programmes only cater for a small fraction of out-of-school children, and their efficiency in
mainstreaming children’s return to school is weak.
Access to postprimary levels still remains challenging for many children. Although strong
improvements in access to secondary have been noted, especially at O-Level, they are still
limited. In 2009, half of children had access to O-Level and 23 percent were able to reach
the last grade of the cycle, against just eight percent in 2003. A-Level access is still strikingly
low, at five percent. Whereas lack of supply is a major hindrance to O-Level and A-Level
access, economic difficulties and cultural issues among certain groups also contribute to
fragile school demand. With respect to the former, the policy to have a secondary school in
each ward has had a very positive impact on secondary access and on primary retention
rates. The pursuit of the policy is expected to improve both O-Level and A-Level access and
retention in the coming years.
Tanzania Education Sector Analysis 22
The increase in primary and secondary school enrollments is already putting a lot of strain
on secondary, TVET and higher education institutions, and enrollment at these levels is
expected to grow more rapidly still over the coming years. An urgent and well-planned
response is required to ensure the smooth and manageable development of the system and
that it remains in line with labor market needs. This raises both financial and practical
challenges (teacher requirements, classroom supply). A sectorwide financial simulation
model may help to explore policy options, assessing both facilities and required resources.
5. Dropout is still a problem at postprimary levels however, despite generally good
internal efficiency levels.
While internal efficiency is generally good, dropout remains a problem, particularly at
postprimary levels. Tanzania’s education system is comparatively efficient at both primary and
O-level, and its A-Level efficiency is in line with the African low-income countries’ average.
The primary IEC was estimated at 88 percent in 2007, implying that 12 percent of resources
are wasted due to repetition or dropout. Repetition being generally low (2.4 percent in primary
and under two percent in secondary, on average in 2009), dropout is the main source of
Education Pyramid for Tanzania, 2009
23%
3%
5%
55%
108%
108%
U
p
p
e
r
S
e
c
o
n
d
a
r
y
Higher Education:
335 Students
per 100,000 inhabitants
TVET:
6% of Secondary
GER = 4%
GER = 39%
GER = 112%
L
o
w
e
r
S
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c
o
n
d
a
r
y
P
r
i
m
a
r
y
49%
33%
Source: Tables 2.8 and 2.11 and Figure 2.7.
Note: TVET refers to technical non-higher education and VET courses (both VETA and NACTE-registered).
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Tanzania Education Sector Analysis 23
Improving retention will necessarily require addressing both supply and demand constraints.
This could entail:
• Alleviating schooling direct and opportunity costs. Although most of the interventions
cited above (regarding the expansion of secondary education for instance) should also
favor primary school retention, special attention should be given to costs borne by
parents, that increase with successive grades and levels. School feeding programmes
and cash transfer programmes are being implemented to compensate, but further
cost-benefit analysis is necessary before expanding them, mainly because of their
notoriously high cost;
• Further improving school supply. Schools with incomplete cycles are known to
negatively affect retention. Although this issue appears to be marginal in Tanzania,
scope for improvement nevertheless exists at the primary level: satellite schools, known
to offer incomplete cycles, could possibly be converted into full-cycle schools through
multigrade teaching. At postprimary levels, building more schools will prove decisive;
and
inefficiency, especially at O-Level and A-Level. More efforts are needed to reduce dropout in
order to improve the overall internal efficiency of the system, and reduce resource wastage.
Source: BEST, various years.
Note: * Not provided as 2009 primary schooling patterns are highly affected by the multicohort phenomenon, which tends to
underestimate dropout; ** Because 2007 A-level repetition data were not available, the proportion observed in 2009 was assumed
to have remained constant over the period. The change in the A-Level IEC is therefore only related to the rise in dropout.
Primary
Internal Efficiency Coefficient
Dropout-Related (no Repetition)
Repetition-Related (no Dropout)
Years Required to Completion
O-Level
Internal Efficiency Coefficient
Dropout-Related (no Repetition)
Repetition-Related (no Dropout)
Years Required to Completion
A-Level
Internal Efficiency Coefficient
Dropout-Related (no Repetition)
Repetition-Related (no Dropout)
Years Required to Completion
Primary and Secondary Schooling Internal Efficiency Coefficients, 2000-09
67
69
97
10.5
82
83
98
4.9
—
—
—
—
88
92
96
7.9
83
85
98
4.8
83
84
99
2.4
2000 2007 2009
—
—
—
—
81
82
98
5.0
72
73
99
2.8
**
**
*
Percent and Number of Years
Tanzania Education Sector Analysis 24
• At the primary level, closely monitoring repetition would be helpful, especially for
Standard I, that has the highest proportion of repeaters. However, as ECCD
programmes expand and the school preparedness of children improves, this issue
should resolve itself. Assessing the relevance and quality of teaching would be
worthwhile, as dropout is often justified by a lack of interest in school.
6. Important disparities persist in access to formal schooling according to gender,
area of residence and especially families’ income levels; and, they tend to be
cumulative.
Beyond the primary level, girls’ participation in education is systematically lower than that of
boys. Gender parity indexes decrease from 1.04 (girls’ enrollment is greater than boys’) in
primary school to 0.65 at the higher/tertiary level. TVET is still slightly gender-oriented: male
students accounted for 55 percent of trainees in 2008. At the higher education level, female
enrollment has barely reached 34 percent: girls are doubly prejudiced by their lower chances
of reaching secondary school, and by their comparatively lower results in the ACSEE exam.
Schooling inequalities are particularly unfair to children from rural areas. Children from
urban areas have better access probabilities to all levels of education than their rural peers,
in part due to the inadequate supply of rural schools. The gap in the probability of access
reaches 23 percentage points for O-Level entry, and eight percentage points for A-Level
entry.
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Gender
Male
Female
Gender Parity Index (Female/Male)
(Memo: Index, 2000)
Area of Residence
Urban
Rural
Location Parity Index (Rural/Urban)
(Memo: Index, 2000)
Income Group
Q5 (The wealthiest)
Q1 (The poorest)
Wealth Parity Index (Q1/Q5)
(Memo: Index, 2000)
Total Tanzania
GERs and Parity Indexes, by Socioeconomic Characteristic, 2006
29.9%
27.2%
0.91
0.89
45.9%
23.8%
0.52
0.53
48.1%
23.0%
0.48
0.21
28.6%
114.6%
118.8%
1.04
0.95
119.6%
115.8%
0.97
0.79
125.3%
117.1%
0.93
0.82
116.6%
31.7%
30.2%
0.95
1.13
56.6%
21.9%
0.39
0.13
64.8%
19.1%
0.30
0.23
30.9%
7.2%
6.0%
0.83
0.95
16.2%
2.6%
0.16
0.09
26.8%
1.6%
0.06
0.19
6.6%
2.9%
1.9%
0.65
0.75
n.a. *
7.9%
0.0%
0.00
0.15
2.4%
Preprimary Primary O-Level A-Level Higher
Source: HBS, 2007, authors’ calculations.
Note: The location parity index is irrelevant to higher learning institutions, that are all located in urban areas.
Reading Note: A gender parity index of 0.83 (2006, A-Level) indicates that for every 100 boys enrolled, there were 83 girls.
Tanzania Education Sector Analysis 25
The unavailability of a school nearby is often a major hindrance (in some rural areas, 22
percent of children live over five kilometers away). There is clearly potential to build more
schools in underserved areas, compensating the cost by offering multigrade teaching under
close supervision. Lack of interest in school is also a major reason for nonattendance
(mentioned by 12 percent) that might be counter arrested by improving the relevancy and
quality of teaching.
Disparities in access increase sharply with successive levels of education, especially those
related to income. Wealth parity indexes decrease from 0.94 in primary school to 0.09 at
A-Level, and are virtually nil at the higher/tertiary level. Retaining the poorest students in
primary schools and ensuring their transition to postprimary cycles is a major challenge.
Although the abolition of school fees has been a major measure in alleviating education
expenses, the poorest households still face prohibitive schooling costs (uniforms, stationery,
books, and so on). Interventions specifically targeting these households, such as cash
transfers, may help to remove economic and financial barriers. Better coverage of the
scholarship grants and remedial classes should make schooling more equitable for the poor.
Furthermore, disadvantages tend to be cumulative. Poor rural girls face the worst access
conditions, and disparities tend to broaden as of the end of primary (for every 100 rich urban
boys completing primary, only 53 poor rural girls do). They then explode at postprimary levels,
leaving poor rural girls with virtually no opportunities to pursue secondary education.
Finally, literacy programmes targeted at parents should give positive results, mainly by
gradually overcoming cultural barriers to education. The encouragement of families and
schools to ensure that all children have birth certificates (although not strictly an education
sector intervention), may also have a positive impact on school access and retention.
Access disparities by region are equally marked. For instance, primary access and retention
are particular issues in Rukwa, Tabora and Dodoma regions. Beyond school supply
constraints, economic, cultural and environmental issues (agro-pastoral activities, cultural
beliefs, tobacco production and climate conditions) shape demand and keep children out
of school. In 2006, secondary access probabilities were as low as four percent in one region,
and were just 16 percent in five others, well below the national average of 27 percent.
Extensive primary and secondary school construction has contributed to loosen school supply
constraints in many of those regions since.
Source: HBS, 2007: authors’ calculations.
Primary Access
Primary Completion
O-Level Access
O-Level Completion
A-Level Access
A-Level Completion
Cumulated Disparities in Schooling Profiles, by Extreme Group, 2006
Percent
98.8
94.2
55.4
36.5
21.3
12.8
Male/Urban/Q5 Female/Rural/Q1 Parity Ratio
92.5
50.1
7.1
1.1
0
0
0.94
0.53
0.13
0.03
—
—
Socioeconomic Status
Q1
Q2
Q3
Q4
Q5
Area of Residence
Rural
Urban
Gender
Girls
Boys
Benefit Incidence of Public Education Resources, by Level of Income,
Area of Residence, and Gender, 2009
Percent, and Appropriation Index
27.0
23.8
20.0
17.3
11.9
74.0
26.0
52.3
47.7
Share of the
Population
(%)
(a)
12.7
15.4
21.1
18.0
32.8
47.1
52.9
45.7
54.3
Public
Resources
Absorbed (%)
(b)
0.5
0.6
1.1
1.0
2.8
0.6
2.0
0.9
1.1
Appropriation
Ratio
(b)/(a)
1.0
1.4
2.2
2.2
5.9
1.0
3.2
1.0
1.3
Appropriation
Index
Tanzania Education Sector Analysis 26
TVET and higher education opportunities are also unequal across areas and regions. Just
five regions (Dar es Salaam, Iringa, Arusha, Kilimanjaro and Mwanza) are home to almost
55 percent of VTCs. HLIs are also particularly present in cities and the eastern part of the
country. The expansion of open distance learning will be crucial in breaking the urban/rural
fracture.
Regional Disparities in Primary Access and Retention Probabilities, 2006
Primary Access Probability (%)
P
r
i
m
a
r
y
R
e
t
e
n
t
i
o
n
P
r
o
b
a
b
i
l
i
t
y
(
%
)
110
100
90
80
70
60
50
40
88 90 92 94 96 98 100 102
Tabora
Kigoma
Arusha
Kilimanjaro
Dar
Iringa
Mara
Ruvuma
Kagera
Mbeya
Tanga
Mwanza
Shinyanga
Lindi
Morogoro
Mtwara
Singinda
Dodoma
Manyara
Rukwa
Pwani
Source: Authors’ calculations based on probabilistic profiles using HBS, 2007 data.
Source: Authors’ calculations based on Annex Table 5.8.
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Tanzania Education Sector Analysis 27
The distribution of public education resources is therefore unequal, benefiting the most
privileged students. Indeed, the 10 percent most educated benefit from 47 percent of public
education resources, in line with the LIC average. The benefit incidence analysis further
shows that boys benefit from 30 percent more public education expenditure than girls. Due
to longer schooling, 33 percent of public resources are allocated to the 12 percent of
students from the most privileged households, and those belonging to the poorest families
only benefit from 13 percent of these resources, despite representing 27 percent of the
population.
Further action is required to support pro-poor schooling, ensure a more equitable
development of the education system and ultimately of society. The opportunity cost may
be to favor future iniquities and the intergenerational transmission of poverty.
7. Quality continues to represent an important challenge to the sector, as
demonstrated by the modest level of learning outcomes.
Although the dynamic of improvement in learning outcomes observed in primary education
between 2000 and 2007 is very encouraging, and good compared to neighboring countries,
learning achievements are modest by international standards.
SACMEQ Reading and Mathematics Scores, 2007
SACMEQ Scores
SACMEQ Score
Mauritius
Kenya
Tanzania
Seychelles
Swaziland
Botswana
Zimbabwe
SACMEQ
South Africa
Zanzibar
Mozambique
Uganda
Lesotho
Namibia
Malawi
Zambia
300 400 500 600 700
623
574
434
Math: 553
Reading: 578
Math: 510
Reading: 512
Math
Reading
Source: SACMEQ 2007 data; IIEP, 2010.
Tanzania Education Sector Analysis 28
National examination pass rates are dropping, and the results of those who graduate are
low, especially at primary and O-Level, implying that too few leave the cycle with an
adequate level of mastery of the programme. In 2009, barely 50 percent of candidates
passed the PSLE, down from 70 percent in 2006. This could be explained by the increase in
the number of students with learning difficulties following the implementation of the fee-
free primary education policy, that was not followed by adequate measures (no sufficient
classes and remedial courses, rising PTRs, lack of textbooks) or by the more strict secondary
school access criteria. At O-Level, the share of graduates is also declining, and reached 66
percent in 2009.
Scores are skewed toward Grade C at PSLE, and toward Division IV (the minimum level) for
81 percent of O-Level graduates. Performance is particularly poor in mathematics and
sciences.
PSLE Core Subjects’ Grade Distribution, by Gender, 2009
Math English Kiswahili Social Studies Sciences
M
a
l
e
F
e
m
a
l
e
M
a
l
e
F
e
m
a
l
e
M
a
l
e
F
e
m
a
l
e
M
a
l
e
F
e
m
a
l
e
M
a
l
e
F
e
m
a
l
e
100%
80%
60%
40%
20%
0%
Fail
C Grade
B Grade
A Grade
75
19
13
83 62
24
21
68
29
39
40
33
35
39
33
48
40
36
53
40
Source: NECTA statistical yearbooks; authors’ computations.
Source: Department of Secondary Education - MoVET, 2010; authors’ computations.
Note: Divisions I to IV are considered as a pass.
O-Level results were also found to be strikingly poor in community schools, which enroll
the majority of students, and represent the pillar of MoEVT’s policy to increase secondary
school access. More analysis is required to adequately assess O-Level quality issues, for which
improved EMIS data will first be required.
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Public
Community
Nongovernmental
Seminaries
Total Mainland
School Candidates’ CSEE Pass Rates and Score Distribution, by Type of School, 2009
12,046
161,277
52,131
5,223
230,677
82.2
67.7
82.0
89.3
72.2
6.8
1.1
4.5
13.7
2.6
Number of
Candidates
Pass
Rate (%)
I II III IV
Distribution of Pass Grades/Divisions (%)
9.2
4.3
8.5
15.4
6.0
22.9
13.6
19.5
25.4
16.1
61.1
81.0
67.5
45.5
75.3
Tanzania Education Sector Analysis 29
At A-Level, the situation is generally better, although pass rates have fallen slightly, to 89
percent in 2009. School candidates systematically outperform private ones, both in quantity
(with respective pass rates of 93 percent and 74 percent in 2009), and in quality (12 percent
and 38 percent reached the minimum level). Half of school candidates score a Division III
grade, a quarter scores a Division II grade and 14 percent a Division I grade, a result almost
never attained by private candidates. Gender disparities are minimal. The globally good
scores could be due to only the best and most fortunate students reaching A-Level.
Implementing mechanisms to adequately monitor learning outcomes will be important given
the rising number of O-Level graduates to enroll and the introduction of the new A-Level
curriculum in 2010.
In VET, 78 percent of long course students completed their year in 2008; 58 percent entered
an exam, 80 percent of whom passed. As far as technical education and higher education
examination results are concerned, high levels of success (above 82 percent) are observed,
although the low number of candidates sitting the exam implies that those who do are the
best performers. The fact that many students bear the cost of their studies has probably
encouraged greater care in the choice of courses, and greater responsibility in learning. No
gender differences are apparent in success rates or the quality of results, although relatively
fewer girls sit higher examinations, and their participation drops the higher the award
involved.
The objective that all children should achieve acceptable levels of learning is made all the
more elusive by the disparities in achievements, although these have narrowed over the
years. At both primary and O-Level, disparities in results exist according to gender, wealth
and area of residence. Although the analysis of SACMEQ scores over 2000-07 shows that
disparities are narrowing, it also pinpoints that: (i) the poorest children’s performance is
starkly below that of their wealthier peers; and (ii) disadvantages tend to be cumulative:
poor rural girls perform the worst. Girls underperformance at CSEE is of particular concern.
Share of Students Reaching Minimum SACMEQ Levels in Reading
(Kiswahili) and Math, by Socioeconomic Characteristic, 2000-07
2000 2007 2000 2007
100%
80%
60%
40%
20%
Reading
Math
Urban
25% Richest (Q4)
Boys
Girls
Rural
25% Poorest (Q1)
Source: SACMEQ, 2000, 2007 data; MoEVT.
Tanzania Education Sector Analysis 30
8. Education does nevertheless have an important impact on social and human
development.
Education, especially primary education, has an important impact on literacy, poverty,
fertility, and maternal and child health. From 7.7 percent for uneducated individuals, the
probability of being literate increases to 87.3 percent for those with full primary education
and to 99 percent for O-Level leavers. Women who have never attended school benefit
from antenatal care from a health professional for only 73 percent of pregnancies, whereas
Raising the quality of basic education will require a multipronged strategy. Based on the
factors found to have a significant impact on learning, and pending further data on and
analysis of learning outcomes and the school/class environment, some policy orientations
can be formulated.
A national student learning assessment system will also prove crucial in the current context
of curricula changes and decentralization. This should track individual exam results and link
data to past performance and school/class inputs. Setting clear benchmarks for early grades
core learning outcomes (especially in math and literacy) will help teachers and parents to
monitor pupils’ progress and weaknesses, and enable timely remedial measures.
Finally, the use of English as the main teaching language in secondary education could be
reviewed in favor of a more gradual phasing in throughout schooling careers, to ensure that
students master the language adequately by the level they are expected to use it to learn.
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Increase student learning time
Set up remedial classes to reduce repetition
Promote preschool attendance
Support poorer children
Involve communities in school management
Favor girls’ education activities
Upgrade teachers’ qualifications to set standards
Provide students with textbooks in key subjects
Improve the coherence of teacher allocation
Equip schools with latrines
Potential Measures to Improve Basic Education Learning Achievements
++
+++
++
++
+++
+++
++
+++
Impact Cost Impact Cost
Primary O-Level
$ (1)
$
$ to $$$ (2)
$ to $$$ (3)
$
$
$ to $$ (4)
$
+++
+++
+++
+++
$ to $$ (4)
$
$ to $$$ (5)
$$
Source: Synthesis of Tables 4.5 and 4.8.
Note: + Low impact, ++ medium impact, +++ high impact; $ low cost, $$ costly, $$$ very costly. The level of impact has been assessed
based on the regression results; the level of cost is based on estimated unit costs. Costs may vary greatly according to the type of
services offered. (1) Improving teacher and student attendance records could reduce absenteeism at a fairly low cost; (2) Community-
based preschool attendance will be much cheaper than enrollment in the regular preschool system; (3) Depending on the type and
amount of support/transfers provided; (4) In-service training would be a low-cost option; (5) costs may be very much inflated whether
the incentive packages require the construction of teachers’ quarters or not, or if the recruitment of additional teachers is needed.
Tanzania Education Sector Analysis 31
The primary level thus has the greatest impact on social outcomes, contributing to almost
60 percent of the total impact of education on social development, which further reinforces
the justification for efforts made to ensure that all Tanzanian children complete at least the
primary cycle. At equal investment, the efficiency of the primary cycle in enhancing human
development is 2.4 times higher than that of the secondary cycle.
9. The sector also has a direct connection to labor market requirements.
Tanzania’s labor force has a better education profile today than in 2001, although highly
qualified human capital remains limited. The share of individuals aged 15 to 60 years with
secondary education and above increased from 5.6 percent to just seven percent between
2001 and 2006. Although progress is slow, the number of individuals with tertiary or higher
education has more than doubled over the period. Over the same period, the average
number of salaried jobs created has increased by about 10.3 percent per year, casting some
doubts on the absorptive capacity of the salaried employment sector (the main supplier of
jobs for higher education leavers), to adequately absorb the growing number of higher
education leavers. To maintain this growth rate, policy makers should assess the ability of
those who have completed primary education are assisted in 81 percent of all cases, and
those who have completed O-Level do so for 85 percent of pregnancies. Age at first
childbirth ranges from 18 years for uneducated women to 21 years for those with complete
secondary, a three year difference.
Source: Authors’ calculations based on TDHS, 2004/05 data.
Note: * Literacy: based on 5,107 men and women aged 22 to 44 years, assessing the probability of being literate; ** Poverty:
based on 6,838 household heads, assessing the relationship between the probability of a household belonging to the first poverty
quintile (Q1) and the level of schooling of the head of household. The poverty measure is based on a wealth index derived from
available assets in the household; *** Child health: based on 6,650 children aged under five years, assessing the relationship
between women’s schooling and the probability that their child is given vitamin A; # Other indicators: based on 4,020 to 5,684
women aged 15 to 49 years, with at least one childbirth for the probability of being assisted at delivery by a qualified health
professional, and at least two childbirths otherwise.
Reading Note: Figures are not simple descriptive statistics of the different phenomenon according to the highest education level
completed; they result from econometric models that identify the net impact of education with all other variables (gender, age,
area of residence, income level) held constant. So, the simulated net probability of literacy for a person having completed A-Level
is 99.7 percent. This rate being simulated means that it is for a theoretical individual with the same socioeconomic characteristics
as an average Tanzanian person, but with complete secondary education.
Literacy
Extreme Poverty
Woman’s Age at First Childbirth (Years)
Total Births (Number)
Probability of Receiving Antenatal Care
Probability of Professionally Assisted Birth Delivery
Probability of Receiving Vitamin A Treatment
Simulated Net Impact of Education on Social Behavior, 2004/05
81.9%
23.3%
19.0
4.0
80.8%
47.4%
22.1%
7.7%
62.9%
17.9
4.5
73.5%
31.6%
8.7%
87.3%
21.9%
19.5
3.8
81.2%
53.3%
18.6%
98.8%
9.1%
20.5
3.4
84.8%
75.5%
27.3%
99.7%
5.6%
20.9
3.2
86.3%
85.3%
32.5%
None
Average
Primary O-Level A-Level
Highest Level Completed
Tanzania Education Sector Analysis 32
higher education leavers to join the nonwage sector and become self-employed, for
instance. Indeed, according to the regional pattern, Tanzania should have about 570,000
higher education students in 2025. This should require enrollment growth of 8.8 percent
per year, much lower than in recent years. These issues should be discussed in the
framework of a simulation model relating the development of secondary education to that
of higher education.
Nevertheless, improved education leads to higher income. The wage premium for workers
with secondary education is particularly high, especially among A-Level leavers. This pattern
suggests that there is a severe shortage of secondary qualifications in the economy. The
average income of tertiary education (technical nonhigher) leavers depends very much on
their sector of employment, being close to that of O-Level leavers in the public sector, but
30 percent higher in the private sector (although still barely half the income of an A-Level
leaver). Individuals who never pursued their education beyond primary earn more in self-
employment than in the private sector.
Source: Authors' computations based on ILFS, 2006 data.
Note: * Too few individuals to compute reliable average income.
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Labor Force
Employed
Public Sector - Salaried
Private Sector - Salaried
Self-Employed or Family Business
Agriculture and Other
Unemployed
Inactive
Employment Status of the Labor Force (25-35 Years), by Level of Education, 2006
98.4
97.5
0.7
8.8
24.5
63.5
0.9
1.6
97.6
97.3
0.2
2.1
14.6
80.4
0.3
2.5
98.1
96.2
16.8
21.6
37.7
20.1
1.9
1.9
95.7
88.0
37.5
33.6
13.2
3.7
7.7
4.3
100.0
100.0
53.3
27.2
4.0
15.5
0.0
0.0
98.2
97.3
2.1
8.8
23.6
62.8
0.9
1.8
Average
No
Schooling
Tertiary/
Higher
Total
O-Level A-Level
Secondary
Percent
No Schooling
Primary
O-Level
A-Level
Technical Nonhigher
Higher education
Annual Income, by Education Attainment and Employment Sector, 2006
1,426
1,663
2,125
5,361
1,921
5,682
526
713
1,453
4,100
1,881
5,413
585
902
1,831
4,906
1,915
5,592
700
1,060
1,548
4,029
—
—
Public
Self-
Employment
(Nonagricultural)
Private Average
Wage Sector
Thousands of T Sh
Source: Authors' computations based on ILFS, 2006 data.
Tanzania Education Sector Analysis 33
VET training is particularly valued by the market. A tracer study conducted in April 2010 by
VETA documented the employment and income status of about five thousand VET graduates.
It showed that VET leavers’ average employment rate is close to 85 percent; their likelihood
of finding permanent employment is slightly higher still, and in about 87 percent of cases,
there was a direct connection between graduates’ training and their job. These results suggest
that the quality of skills and qualifications is reasonable, and that the main challenge is
unemployment. Indeed, VET graduate unemployment is close to 15 percent, mainly attributed
to a mismatch between training and the availability of related jobs and to the lack of resources
to start a business. This situation calls for policies both on the supply-side (improving the
relevance and professionalism of training for selected sectors) and the demand-side (assisting
graduates in mobilizing the required resources and assets). The possibility of devoting a share
of the skill development levy to business start-up funds should be assessed.
Strikingly, some VET education offers no significant added value over primary or O-Level. In
general, the income of VET graduates compares favorably with that of self-employed
individuals with primary education or O-Level. However, graduates with clothing and textile,
and hospitality and tourism sector skills appear to earn at best the same amount as primary
school leavers, which is worthy of more detailed analysis. On the other hand, VET courses
have provided significant added value to electricity or agriculture and food processing
graduates.
10. Education management needs to be improved, particularly on the administrative
and pedagogical fronts.
Tanzania has a shortage of teachers at both the primary and secondary levels. The pupil to
teacher ratio was 55 to 1 in government primary schools in 2009, well above the SADC
average and the national target (45 to 1). On the basis of the latter, the accumulated
shortfall of primary school teachers was 30,405. The secondary level PTR stood at 43 to 1,
Employment Rate of VET Graduates, by Sector, 2010
Agriculture & Food Processing
Construction
Clothing and Textile
Mechanics
Hospitality and Tourism
Electricity
Automotive
Business Administration
Other
60% 70% 80% 90% 100%
94%
92%
91%
88%
86%
82%
78%
75%
74%
Source: Preliminary results of the April 2010 VET Tracer Study, on 4,569 VET graduates (VETA, 2010).
Note: Other sectors include: ICT, laboratory technology, printing, mining, education (pedagogy, adult learning strategies, training
of trainers) and general subjects.
O-Level Only
Both Levels
A-Level Only
Total
Secondary Level PTRs and PqTRs, by Level and School Type, 2009
52:1
19:1
20:1
46:1
26:1
23:1
23:1
25:1
48:1
21:1
21:1
41:1
74:1
20:1
21:1
61:1
37:1
27:1
24:1
32:1
68:1
22:1
22:1
54:1
Nongvt. Gvt. Total Nongvt. Gvt. Total
PTR PqTR
Schools offering
Tanzania Education Sector Analysis 34
The proportion of qualified teachers has increased at the primary level, but has plummeted
at the secondary level, reaching 90 percent and 76 percent in 2009, respectively. The teacher
training system has shown difficulties to respond to the growing demand for teachers
following the surge in secondary enrollment. The lack of language, mathematics and science
teachers is a particular issue. Only 28 percent of teachers specialized in sciences in 2009 for
instance, down from 40 percent in 2004.
Analyses show poor consistency in teacher allocation across schools, both at the primary
and secondary levels, highlighting management flaws. The average degree of consistency
for school teacher allocation was 40 percent in 2007, meaning that 60 percent of teachers
were allocated according to criteria other than the level of enrollment. The results underline
the limits of current management practices and raise the issue of the need for new
monitoring tools to ensure more equitable deployment.
Primary Level PTRs, by School Type, 2000-09
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
70
60
50
40
30
20
10
0
48
21
56
25
53
24
54
22
56
55
23
47
59
57
21
46
28
53
46
41
Government Schools Nongovernmental Schools
P
T
R
Source: Regional BEST, 2000-07, BEST, 2008 and 2009.
Source: BEST.
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up from a low 19 to 1 in 2004, government schools accounting for most of the increase,
with the average PTR reaching 49 to 1 (against 23 to 1 in nongovernmental schools).
Tanzania Education Sector Analysis 35
The primary teaching profession is more financially attractive in Tanzania than in the
subregion. A Tanzanian primary school teacher earns about US$ 6,560 per year (in 2005
purchasing power parity, or 6.1 times GDP per capita), against an average of US$ 4,320 for
other African LICs (4.5 times GDP per capita). Although this should facilitate recruitment, it
also imposes a constraint on resources. Tanzania is however close to achieving universal
primary education, and as teacher requirements drop in line with the demographic pressure,
reducing the primary PTR should be more feasible, improving learning conditions, and
ultimately, the quality of service.
Secondary school teachers on the other hand are comparatively underpaid, despite their
shortage. Their low compensation (5.9 times GDP per capita, against 7.5 times in
comparable countries) is partly due to the high proportion of unqualified teachers at this
level. MoEVT developed a multipronged Teacher Development and Management Strategy
in 2008, focusing mainly on supply-side issues. The attractiveness of the profession should
also be reviewed to better retain candidates, inspired by labor market surveys and cross-
country comparisons.
The loose school-level relationship between learning outcomes and school resources points
to weaknesses in pedagogical management. Students from schools that cost the most do
not perform the best, and the least endowed schools do not always achieve the worst
results. These patterns show that beyond the issue of resource allocation, the way resources
are used seems to have a major influence on the level of learning outcomes. Improving
supervision and accountability at the local level is known to be an effective remedy, through
greater information on school inputs and performance, favoring school-based management
and teacher incentives.
Coherence in the Allocation of Primary Teachers among Government Schools, 2007
0 500 1,000 1,500 2,000 2,500 3,000 3,500
80
70
60
50
40
30
20
10
0
y = 0.0178x + 1.5023
R
2
= 0.5947
Number of Pupils
N
u
m
b
e
r
o
f
T
e
a
c
h
e
r
s
Source: SACMEQ, 2007, authors' computations.
Tanzania Education Sector Analysis 36
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11. The strong disparities in the allocation of education inputs further illustrates
management shortcomings.
Significant geographical disparities exist in teacher deployment, with particular allocation
issues in remote rural areas. This is striking at the district-level: primary PTRs range from a
low 28 to 1 in Iringa district, to levels in excess of 80 to 1, such as in the districts of Ukerewe
(129 to 1), Ilala (115 to 1), Chato (95 to 1), Manyoni (91 to 1) and Uyui (89 to 1). In the
Sikonge district, one school reported an extraordinary PTR of 313 to 1 (PEDP II, 2009). The
average urban district-level PTR was 43 to 1, compared with 60 to 1 in rural districts.
Relationship between CSEE Pass Rates and Secondary Level Unit Costs, 2009
- 100 200 300 400 500 600 700 800 900
100
80
60
40
20
0
Unit Costs (Thousands of T Sh)
C
S
E
E
P
a
s
s
R
a
t
e
(
%
)
R
2
= 0.042
Source: Cost of teachers and textbooks from BEST, 2009; Salaries from Table 3.18; CSEE results from NECTA.
Note: Unit costs for the CSEE analysis include teacher salaries and textbook prices.
Tanzania Education Sector Analysis 37
The situation is more critical still as far as qualified teachers are concerned. The pupil to
qualified teacher ratio (PqTR) ranges from above 100 to 1 (Ilala, Bahi, Ulanga, Nanyumbu,
Ukerewe, Manyoni, Urambo and Uyui districts) to under 35 to 1. This situation implies a
very heavy workload for some teachers, potentially negatively affecting their motivation and
willingness to stay in remote areas. This major issue will need to be adequately addressed
through the implementation of an incentive package that could include cash benefits, a
hardship or relocation allowance, fast-track career progression, and/or preferential access
to training and learning materials and improved school environment facilities (including
teachers’ quarters).
Textbooks are generally in short supply in government schools, especially at the secondary
level, and suffer from misallocation. One textbook is shared by three students on average
in primary and between four to nine students at O-Level, according to the subject. Although
many possible explanations exist, the timely transfer and amount of school capitation grants
are definitely related to the lethargic supply. Regional disparities reveal the kind of extremes
Government School Pupil to Teacher Ratios, Primary Level, by Region, 2009
Lake Natron
Arusha
45 Kilimanjaro
37
Tanga
54
Manyara
52
Singida
56
Tabora
68
Shinyanga
73
Mara
62
Lake Victoria
Kagera
61
Kigoma
59
Rukwa
65
Mbeya
55
Lake
Tangyanika
Dodoma
56
Pwani
42
DSM
49
Lindi
55
Mtwara
52
Ruvuma
48
Iringa
45
Morogoro
48
Iringa
45
Lake Natron
Arusha
45 Kilimanjaro
37
Tanga
54
Manyara
52
Singida
56
Tabora
68
Shinyanga
73
Mara
62
Lake Victoria
Kagera
61
Kigoma
59
Rukwa
65
Mbeya
55
Lake
Rukwa
Lake
Tanganyika
Lake
Nyasa
Dodoma
56
Pwani
42
DSM
49
Lindi
55
Mtwara
52
Ruvuma
48
Morogoro
48
Source: BEST, 2009.
Legend: Light grey – PTR under 45:1; Medium grey – PTR between 46:1 and 65:1; Dark grey – PTR above 65:1.
Tanzania Education Sector Analysis 38
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that averages can conceal, showing ratios of more than 3.6 pupils per textbook in Kagera
and Lindi regions, against 1.3 in Tanga region. The coherence of textbook availability across
districts is weak, with R
2
values ranging from 57 percent for math books to 67 percent for
English books.
The allocation of capitation grants is also fraught with inefficiencies. They are mainly due
to amounts allocated often being lower than planned budgets, and to delays in the
reception of funds by schools. The allocation formula is currently based on expected
enrollment; a more equitable formula would take the different needs of schools into
account. Timely fund transfers might be facilitated by the option of sending block grants
for nonwage spending directly to schools. Finally, to ensure that the funds are spent as
planned, a reliable and sustainable accounting system is to be implemented. School
management committees and boards could provide valuable oversight of such functions.
Strengthening their capacity in planning, budgeting, monitoring and evaluation is becoming
critical.
These disparities highlight the need for effective planning and monitoring tools to allocate
education inputs more efficiently. In addition to an EMIS system, financial and human
resource management systems would improve fiscal management and accountability. A first
response to this challenge was given in 2009, with the development of a pilot decentralized
Basic-Education Management Information System (BE-MIS), which was tested in 28 district
councils in 14 regions, and is to be scaled up to all councils nationwide by 2014.
3.6
2.7
1.4
Availability of English Books in Government Primary Schools, by Region, 2009
Pupil - Textbook Ratio
4.0
3.5
3.0
2.5
2.0
1.5
1.0
N
u
m
b
e
r
o
f
P
u
p
i
l
s
p
e
r
B
o
o
k
T
a
n
g
a
K
i
l
i
m
a
n
j
a
r
o
R
u
k
w
a
T
a
b
o
r
a
M
w
a
n
z
a
K
i
g
o
m
a
N
a
t
i
o
n
a
l
S
i
n
g
i
d
a
S
h
i
n
y
a
n
g
a
M
a
n
y
a
r
a
I
r
i
n
g
a
D
o
d
o
m
a
D
a
r
e
s
S
a
l
a
a
m
R
u
v
u
m
a
M
t
w
a
r
a
A
r
u
s
h
a
M
b
e
y
a
M
o
r
o
g
o
r
o
P
w
a
n
i
M
a
r
a
K
a
g
e
r
a
L
i
n
d
i
2.7
3.6
1.4
Source: BEST, 2009.
Tanzania Education Sector Analysis 39
12. Higher education is in a favorable position to adequately manage the
development and diversification of the subsector’s supply.
The government has deployed a series of strategies to ensure the adequate and more
concerted development of both higher education and the TVET subsectors, to supply the
economy with the increasing number of skilled and knowledgeable professionals it needs
to sustain its growth. A solid and modern institutional framework has been established for
higher education’s development: the sector was integrated into MoEVT in 2008 to promote
more integration across education subsectors, and the Tanzania Commission for Universities
has been strengthened to comply with quality assurance requirements. Various mechanisms
have been implemented or are under consideration to improve equity and access, including:
(i) a streamlined admissions procedure and centralized admissions system; (ii) an extended
national qualifications framework, building bridges between vocational and university
education; (iii) cost-sharing policies; and (iv) student loans, provided to 81 percent of all
higher education students via the HESLB.
Many HLIs are still not running at full capacity, allowing for the expansion of the system at
limited cost. In the sample of HLIs used in this report, the total intake capacity was 50,508,
of which only 37,142 places were effectively occupied, or 74 percent. Nevertheless, if the
current enrollment trend continues, the need for greater capacity will require imminent
attention, considering subject specializations.
University teaching conditions are favorable. Although staff are predominantly male, female
teachers accounting for just a fifth of HLI teachers in 2009/10: (i) half are aged 40 years
and under, and 30 percent are aged over 50 years; (ii) 25 percent of the teaching staff were
highly ranked (professor, associate professor or senior lecturer); (iii) almost all lecturers had
the required level of qualifications; (iv) 87 percent of teachers were full-time; (v) higher
education teaching salaries were very attractive; and (vi) student to teacher ratios averaged
15 to 1.
However, the high level of administrative staff in higher learning institutions is an issue. The
ratio of administrative staff to teaching staff in the sample used was 1 to 1 on average, in
some cases reaching 2.4 to 1, underlining the scope for efficiency gains.
In theory, the country is today adequately equipped to cater for the expected growth in the
intake of students. However, to ensure the smooth and coherent development of the sector,
attention must be paid to course requirements, and to the likely timescale in which the
subsector is going to expand. The existing state institutions and parastatal agencies should
be able to orient this policy both from its supply and its demand side.
Tanzania Education Sector Analysis 40
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13. The TVET system is also endowed with an improved and solid institutional
framework, including regulatory and quality assurance bodies.
TVET coordination is being improved through a new institutional set-up, incorporating
vocational education and training and technical education under MoEVT. The sometimes
incoherent development of trainings by individual institutions is being addressed through
the development of a TVET development programme. Yet, technical and vocational
education are still separately managed.
Quality assurance processes have been greatly improved under both NACTE and VETA, through:
• Registration and accreditation standards and procedures. At the end of 2009, 96 percent
of the 221 physically recorded technical education institutions were fully or provisionally
registered, up from 41 percent in 2002. Thirty nine percent were given accreditation;
• Education qualification frameworks, including the National Technical Awards;
• An outcome-based training approach;
• The registration of all technical education teachers. In June 2009, 1,574 out of 2,970
had full or provisional registration (53 percent); and
• VETA’s rigorous registration and accreditation guidelines. In 2008, 78 percent of VTC
centers were registered (50 percent provisionally, and 28 percent fully), and
underperforming or unoperational centers’ registration was revoked.
An effective monitoring and evaluation mechanism to make the technical and vocational
education more responsive to labor market demands has been put in place. Under VETA,
zonal labor market analysts regularly collect data that is then compiled at the national level,
and complemented with mini market surveys to track current and prospective industry
needs. FDC training programmes are also demand-driven; curricula are developed after
conducting community training needs assessments. However, labor market surveys are still
limited by technical education institutions’ capacities and resources, creating a mismatch
between the development of needed skills and current institutional service delivery.
Source: NACTE.
Note: Includes Zanzibar. Out of a total number of 221 HLIs.
Preparatory / Candidacy
Provisional
Full
Total (Full + Provisional)
% (Out of 221 HLIs)
Registration and Accreditation Status of Technical HLIs, 2009
8
35
178
213
96%
33
36
50
86
39%
Registered Accredited
Number
Stage of
Tanzania Education Sector Analysis 41
14. TVET nevertheless faces a series of challenges.
Technical and vocational education institutions are facing increasing pressure to support
new socioeconomic developments and ensure that a growing number of basic and
secondary school leavers are provided with adequate skills to enable them to develop their
full potential in the workplace. Although regulatory and quality assurance bodies provide
important guarantees for the controlled development of the TVET subsector, it faces a series
of challenges:
(i) The diversity of training demand linked to the heterogeneity of the target population
(school leavers, technicians wanting to upgrade or change jobs, low skilled/educated
people from urban and rural areas);
(ii) The variety of TVET programs and providers (ministries, parastatal agencies, faith-
based organizations, NGOs, private institutions, vocational training centers, Folk
Development Colleges, and so on);
(iii) The institutional fragmentation of the TVET system, involving two ministries and three
different parastatal agencies;
(iv) The practical continuity between VET and TE curricula/programmes, although
theoretical bridges do exist between both sectors, as defined in the national
qualifications’ framework;
(v) The lack of practical mechanisms for vertical academic promotion within VET. The
competency-based qualifications framework should facilitate the transition between
levels. In 2008 however, only 13 percent of the 889 VTCs offered the CBET.
To date, the training of tutors has not been given enough attention and support. The
training of vocational training centre staff is still a major challenge. The shortage of quality
teaching staff and FDC tutors is acute. Trainers’ competencies are focused on methodology,
and their practical industrial competencies need reinforcing and updating. Preservice and
in-service training opportunities will need to be adequately set up to improve teaching
quality.
The TVET system seems to have adequate monitoring tools (such as labor market surveys
and tracer surveys) to adequately develop and update curricula according to changing
market demand and forthcoming economic needs. However, a dynamic connection
between TVET training institutions and industry is desirable to sustain and facilitate the
smooth and coherent development of relevant workforce skills.
Tanzania Education Sector Analysis 42
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Adequately diversifying the sources and level of funding will prove key to enable the TVET
subsector and its institutions to meet their goals. Technical institutions particularly lack
modern training equipment and sufficient and relevant learning materials. Cost-sharing
mechanisms and granting trainees access to higher education loans should be considered.
VET resources are also insufficient to adequately cater for institutions’ operational needs.
To complement trainee fees, government grants, the proceeds from fund-raising activities
and the development and skills levy, the subsector could seek funds from the private sector
or communities, and implement short-term cost-efficiency measures.
15. The way forward should involve more balanced and efficient sector policies.
Important progress has been registered as much on the institutional front (through
coordination and piloting mechanisms) as on the school coverage one. This has been greatly
helped by the additional resources devoted to education over the decade. The possibility that
this trend not be sustained due to competing sectors’ needs calls for more effective education
policies and the removal of major inefficiencies. In this context, the Education Sector Analysis
(ESA) has helped to identify the following options that are available to policy makers:
• Increase the public resources allocated to secondary education, especially for capitation
grants and more teachers;
• Improve higher education funding mechanisms, by better targeting loan beneficiaries
and better taking advantage of potential economies of scale;
• Ensure children enter primary school at the right age;
• Improve secondary access and retention;
• Support pro-poor schooling, starting at primary level;
• Take affirmative action to enhance girls’ participation in school and ensure gender
parity at postprimary levels;
• Improve pedagogical management to raise the quality of basic education;
• Reduce disparities in the allocation of education inputs between regions, districts and
schools;
• Strengthen the development of literacy programmes targeted at parents, women and
active adults;
Tanzania Education Sector Analysis 43
• Revise TVET budget trade-offs and strengthen TVET coordination mechanisms to
better respond to the strong and heterogeneous demand;
• Define a funding formula to rationalize the allocation of resources among technical
institutions;
• Adequately plan the expansion of TVET and higher education. University students’
career objectives and the distribution of graduates by subject area must be adjusted
on the basis of the results of relevant tracer surveys;
• Strengthen the EMIS to further improve the coverage and quality of education data at
school and district levels;
• Scale-up the BE-MIS, including decentralized financial and human resource databases
to improve fiscal management and accountability systems.
This education sector analysis (ESA) for mainland Tanzania is a detailed analytical
document that offers a comprehensive picture of mainland Tanzania’s education
sector. This ESA is part of an on-going series of education country-specific reports
being prepared by government teams, technically supported by UNESCO, the World
Bank and other development partners. The main purpose of an ESA (also known as
a Country Status Report, or CSR) is to provide an evidence-based diagnosis of an
education sector to enable decision-makers to orient national policies. It also
provides relevant analytical information to nourish the dialogue between the
government and education sector stakeholders, including development partners.
In the current development context, marked by the necessity for countries to
develop sound, sustainable and credible strategies and plans in which education is
embedded, ESAs represent a valuable and essential tool.
This is the second ESA for Tanzania; the first one having been conducted in 2001.
Although its main objective is to provide a comprehensive picture of the education
system in 2009 (the last year for which statistics were available), it also provides
some analysis of the evolution of the system over the decade, when feasible and
relevant. This second report is also more than an update. It provides more in-depth
analysis on certain aspects of the system: detailed unit costs by subsector, external
efficiency, quality and out-of-school, and technical education and vocational
training and higher education in particular. It provides key monitoring and
evaluation inputs on the education sector as a whole, that are particularly
valuable in the framework of the implementation of the Education Sector
Development Programme.
Regional Bureau
for Education in Africa
doc_312165113.pdf
The total population is expected to grow by 32 percent between 2010 and 2020. Over the same period, the under 15 years age-group will remain constant at 44.2 percent of the total.
Regional Bureau
for Education in Africa
Tanzania
Beyond Primary Education, the Quest for Balanced and Efficient
Policy Choices for Human Development and Economic Growth
EDUCATION SECTOR ANALYSIS
EXECUTIVE SUMMARY
SN/2012/ED/PI/1
The findings, interpretations, and conclusions expressed in this volume do not necessarily reflect the views of the
Executive Director of UNESCO or the Government of Mainland Tanzania.
SN/2012/ED/PI/1
Tanzania
Beyond Primary Education, the Quest for Balanced and
Efficient Policy Choices for Human Development
and Economic Growth
EXECUTIVE SUMMARY
EDUCATION SECTOR ANALYSIS
Regional Bureau
for Education in Africa
Tanzania Education Sector Analysis 4
Acknowledgments
This Education Sector Analysis was prepared through a close collaborative effort by the
government of Tanzania, the Pôle de Dakar (UNESCO/BREDA), the UNESCO Institute of
Statistics, and the UNESCO Dar es Salaam cluster office.
The government team consisted of staff from the different ministries in charge of education,
led by the Ministry of Education and Vocational Training (MoEVT), as well as other ministries
and departments, including the Ministry of Community Development, Gender and Children
(MCDGC), the Ministry of Finance and Economic Affairs (MoFEA), the Prime Minister’s Office
for Regional Administration and Local Government (PMO-RALG), the National Examinations
Council of Tanzania (NECTA), the National Council for Technical Education (NACTE), the
Tanzania Commission for Universities (TCU), the Vocational Education and Training Authority
(VETA), the National Bureau of Statistics (NBS) and the Bureau for Educational Research and
Education of the University of Dar es Salaam (BERE/UDSM), which was instrumental in
facilitating all theoretical workshops.
The government team was successively led by Cyprian Miyedu, former Chief of the
Monitoring and Evaluation (M&E) Section, Department of Policy and Planning of MoEVT,
the late George Maliga, Chief of the M&E Section of MoEVT, and Muhwela Kalinga, Acting
Chief, M&E Section, under the overall leadership of Professor H.O. Dihenga, the Permanent
Secretary of MoEVT. Related administrative issues were handled by Mr Malili and Ms Levira.
For Chapters 1 and 3, the government ESA team consisted of Ms Baitwa (Chapters head,
Budget and Finance Division, MoEVT), Ms Elinzu (NBS), Mr Kitali (PMO-RALG), Ms Luena
(EMIS, MoEVT), Mr Minja (Administration and Personnel, MoEVT), Mr Mtyama (MoEFA), Ms
Omolo (TMC-DPLO/LGA Temeke District Council) and Mr Zullu (Administration and
Personnel, MoEVT). Mr Pambe (Chapters head, Primary Education, MoEVT), Ms Kiisheweko
(TCU), Ms Levira (Adult Education, MoEVT), Mr Maiga (Adult Education, MoEVT), Mr
Mchunguzi (Higher Education, MoEVT), Ms Sigwejo (NACTE), Mr Saro (FDC, MCDGC) and
Mr Wilberforce (EMIS, MoEVT) constituted the government team for Chapters 2 and 5. The
team for Chapter 6 included Mr Mhagama (Chapter head, VETA Division, MoEVT), Mr
Misana (Technical Education, MoEVT), Mr Malili (Higer Education, MoEVT), Mr Mwakapalala
(NBS), Mr Ndamgoba (FDC, MCDGC), Mr Petro (EMIS, MoEVT) and Mr Sunday (MIS,
MCDGC). The government team for Chapters 4, 7 and 8 was composed of Mr Mwenda
(Chapters head, Secondary Education, MoEVT), Mr Gabriel (LGA Bagamoyo, PMO-RALG),
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Tanzania Education Sector Analysis 5
Mr Kinunda (Higher Education, MoEVT), Mr Nzoka (Teacher Training, MoEVT), Mr Mbowe
(NECTA), Ms Mrigo (Administration and Personnel, MoEVT), Mr Pambe (Primary Education,
MoEVT), Mr Ponera (EMIS, MoEVT) and Mr Shauri (Primary Education, MoEVT). Chapter 7
received additional inputs from staff from the Inspection Department of MoEVT.
The Pôle de Dakar (UNESCO/BREDA) team consisted of Borel Foko (Team Leader, Education
Policy Analyst) and Diane Coury (Education Policy Analyst), under the overall guidance of
Jean-Pierre Jarousse (former Head of the Pôle de Dakar) and Mohammed Bougroum (Head
of the Pôle de Dakar). Inputs were also provided by Pôle’s members, Alain Patrick Nkengne
Nkengne, Mireille Harivola Ravelojaona and Ibrahima Dao.
The team received constant support from the UIS team of the UNESCO Dar es Salaam cluster
office, which consisted of Marc Bernal (UIS Regional Advisor for Eastern and Southern
Africa), Criana Connal (former EMIS Programme Specialist) and Erick Makoye and Abdulatif
Min-Hajj (IT specialists). Special thanks are due to Marc Bernal and Criana Connal who
provided strong support and facilitated the policy dialogue throughout the process.
The UNESCO Dar es Salaam cluster office was also instrumental in the effective elaboration
of the ESA. The team would particularly like to thank Min Jeong Kim (Education Programme
Specialist) who helped complete the process and Flora Rusenene and Rahma Islem for their
constant administrative support. Special thanks are due to Barnaby Rooke for the editing
work and Regis L’Hostis for the graphic design.
The team received valuable comments from the peer reviewers Criana Connal, Jean-Pierre
Jarousse, Jean-Marc Bernard, Agripina Habicht, Monica Githaiga, and Joseph Vere, as well
as from the development partner groups led by Corey Huntington (Canadian High
Commission).
The preparation of this report was funded by the Education Management Information
System (EMIS) Programme, financially supported by multiple donors, under the
administrative responsibility of the UIS/UNESCO-Dar es Salaam cluster office, and by the
Pôle de Dakar (UNESCO/BREDA).
Tanzania Education Sector Analysis 6
Foreword
T
his education sector analysis (ESA) for mainland Tanzania is a detailed analytical
document that offers a comprehensive picture of mainland Tanzania’s education
sector. The main purpose of an ESA (also known as Country Status Report, or CSR)
is to provide an evidence-based diagnosis of an education sector, to enable
decision-makers to orient national policies. It also provides relevant analytical
information to nourish the dialogue between the government and education sector
stakeholders, including development partners. In the current development context, marked
by the necessity for countries to develop sound, sustainable and credible strategies and
plans in which education is embedded, ESAs represent a valuable and essential tool.
This is the second ESA for Tanzania; the first one having been conducted in 2001. Although
its main objective is to provide a comprehensive picture of the education system in 2009
(the last year for which statistics were available), it also provides some analysis of the
evolution of the system over the decade, when feasible and relevant. This second report is
also more than an update. It provides more in-depth analysis on certain aspects of the
system: detailed unit costs by subsector, external efficiency, quality and out-of-school, and
technical education and vocational training and higher education in particular. It provides
key monitoring and evaluation inputs on the education sector as a whole, that are
particularly valuable in the framework of the implementation of the Education Sector
Development Programme.
This 2011 ESA was carried out between February 2009 and November 2010 by a multi-
ministerial national team with the support of the Pôle de Dakar (UNESCO/BREDA) and the
UNESCO Institute of Statistics. It was part of the activities conducted under the Education
Sector Management Information System (ESMIS) Programme,
1
one goal of which is to
support the development of capacities in data analysis using data generated by the ESMIS
and other sources to strengthen sector-wide planning and policy reforms. The ESA process
contributed to the strategy for building capacities in data analysis through a combination
of: (i) learning-by-doing, through a series of workshops, and (ii) theoretical training sessions,
offered in parallel to the workshops by the Bureau of Educational Research and Evaluation
of the University of Dar es Salaam (BERE/UDSM), based on the SAMES
2
materials provided
by the Pôle de Dakar.
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Tanzania Education Sector Analysis 7
The analyses presented in this ESA were made possible by using existing data and
information from multiple sources, and more particularly: school administrative surveys
conducted by the Ministry of Education and Vocational Training (BEST, TCU and NACTE
data); household budget, labor force, demographic and health surveys conducted by the
National Bureau of Statistics; and SACMEQ data on learning achievements, including
examination data from NECTA. Macroeconomic data and government finance statistics were
provided by MoFEA, and specific data were made available from VETA and the HESLB.
Obtaining timely (household surveys, SACMEQ, and payroll data) and reliable key data (EMIS
data were fraught with flaws) was a major constraint that has heavily limited the scope of
some analyses. Nevertheless, some important conclusions have been reached, both on the
achievement front, and on the major challenges faced by the education system.
The 2011 ESA has highlighted some interesting achievements, including:
• Sustained economic growth and greater public resources have translated into a relatively
higher education budget. The government spent 4.3 percent of GDP on education in
FY 2008/09 (from a low 2.5 percent in FY 2000/01), much more than countries with
similar levels of development. Education has also been given high budget priority. The
sector benefited from 26.5 percent of recurrent government expenditure after debt
service in FY 2008/09, well above the African low-income countries’ average of 21.4
percent;
• Tanzania is on track to achieve the millennium development goal of universal primary
education. Access is almost universal and the primary completion rate is close to 90
percent. The fee-free primary education policy has had a positive impact by boosting
both access and retention. Tanzania’s preprimary gross enrollment ratio is close to 37
percent, compared with just 20 percent on average for comparable African countries.
Tanzania’s administration of this level, using similar teaching approaches as for the
primary cycle and similar school premises, has helped to lower unit costs and increase
enrollment;
• Enrollment has increased for all cycles, and particularly in higher education, allowing
Tanzania to rapidly catch up with the levels of comparable developing countries: in 2009,
the number of higher education students in Tanzania was 36 percent lower than the
average, down from 50 percent in 2006. This trend is likely to continue as a direct
consequence of the expected development of secondary education;
• The Tanzanian higher education and TVET sectors are well positioned to adequately
manage the development and diversification of supply. Existing policies and regulatory
bodies provide a sufficient, solid and modern institutional framework for the system to
build upon for its future development;
• Education has a significant impact on social and human development, particularly on
literacy, poverty, fertility, and maternal and child health. Primary education is the level
that has the greatest impact on social outcomes: it contributes to almost 60 percent of
the total impact, which further reinforces the justification for sustained efforts to ensure
that all Tanzanian children complete at least the primary cycle; and
• Education responds to labor market needs. Greater levels of education lead to higher
incomes. The wage premium for workers with secondary education is particularly
significant, suggesting that there is a severe shortage of individuals with secondary
qualifications. There is also a strong connection between vocational training and
graduates’ employment. In general, the income of VET graduates compares favorably
with that of self-employed individuals with primary education or O-Level secondary.
The 2011 ESA also points to key challenges in the coming years for the development of the
education sector in Tanzania, including:
• Achieving greater efficiency gains (or implementing cost-saving strategies) in the use of
public education resources. Indeed, it is unlikely that the current level of budget priority
given to the education sector will be maintained over the next decade, due to competing
demands by health, agriculture and infrastructure;
• Increasing the public resources allocated to secondary education. Tanzania’s secondary
cycle receives 35 percent less funding than countries who are equally close to achieving
universal primary education. This situation should be carefully reviewed to avoid
affecting quality as the sector expands. Secondary schools already display high pupil to
teacher ratios (49 to 1);
• Ensuring children enter primary school at the right age. Approximately 13 percent of
primary school-aged children were still out of school in 2006, 88 percent of which had
never attended. Although poverty is a constraint, age appeared to be the main reason
for nonattendance. Late primary entry is common (only 36 percent of Standard I
students were of official school age
_
seven years
_
in 2006) and is known to have a
detrimental impact on schooling paths;
Tanzania Education Sector Analysis 8
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• Improving access to and retention in secondary cycles. Although considerable
improvements in access to secondary school have been noted, especially at O-Level,
they are still limited. In 2009, half of children had access to O-Level and 23 percent were
able to reach the last grade of the cycle, up from just eight percent in 2003. A-Level
access is still strikingly low, at five percent. Whereas lack of supply is a major hindrance
to O-Level and A-Level access, economic difficulties and cultural issues among certain
population groups also contribute to fragile school demand. The policy to have a
secondary school in each ward has had a very positive impact on secondary access and
on primary retention rates;
• Supporting pro-poor schooling. Important disparities in access exist according to gender
and area of residence, and they increase with successive levels of education, but the
most discriminatory factor in schooling patterns is families’ level of income. It has also
been shown that households’ contributions to education are still significant at the
primary level (equivalent to a quarter of public resources), despite the fee-free primary
education policy. Furthermore, disadvantages tend to be cumulative. Poor rural girls face
the worst access and retention conditions;
• Taking affirmative action to enhance girls’ participation in school to ensure gender parity
at postprimary levels. Insistence on girls fulfilling their traditional role in society, early
marriage and pregnancy all favor dropout. Trends could be reversed by: (i) awareness
raising campaigns to sensitize parents on the value of educating girls beyond primary,
and on the negative impact of early marriage and pregnancy on schooling and female
health; (ii) greater numbers of female teachers and the provision of community-based
hostels to avoid girls the long journeys to and from school, addressing security concerns;
and (iii) scholarships and cash transfers targeting bright girls, reducing direct and
opportunity costs, mirroring the government’s programme targeting the most talented
primary graduates from poorer backgrounds;
• Improving pedagogical management to raise the quality of basic education. Although
the improvement dynamic observed in primary education learning outcomes between
2000 and 2007 is very encouraging, and better than in neighboring countries, learning
achievements are still modest by international standards. In addition, national
examination pass rates are dropping, and the results of those who graduate are low,
especially at primary and O-Level;
• Reducing disparities between regions, districts and schools, that persist despite
decentralization, highlighting the need for effective planning and monitoring tools to
allocate education inputs more efficiently. A decentralized information and monitoring
system could help by providing decision makers with timely, accurate and reliable data on
the education sector. In addition to an EMIS system, financial and human resource
management systems would improve fiscal management and accountability. A first
response to this challenge was given in 2009, with the development of a pilot decentralized
Basic-Education Management Information System (BE-MIS). Tested in 28 district councils
in 14 regions, the BE-MIS is to be scaled up to all councils nationwide by 2014; and
Tanzania Education Sector Analysis 9
• Adequate planning of TVET and higher education expansion. The increase in primary
and secondary school enrollments is already placing much strain on secondary, TVET
and higher education institutions. An urgent response is required to ensure the smooth
and manageable development of these subsectors.
The challenges faced by higher education are of particular importance:
• It is essential that funding mechanisms be improved. Higher education is blatantly
inefficient, paying little attention to potential economies of scale. In addition,
approximately 28 percent of the level’s budget is devoted to badly targeted social
expenditures, particularly loans transferred directly to students: 48 percent of students
benefit from a loan, yet less than 10 percent come from the poorest quintiles, which
calls for an improvement in the loan targeting mechanisms; and
• Students’ career objectives and the distribution of graduates by subject area must be
adjusted, to achieve better relevancy of higher education programmes to the labor
market and enable Tanzania to keep abreast of rapid technological development and
needs. Science subjects in particular attract too few students (only 24 percent of
students for the 2007/08 academic year, down from 34 percent in 2003/04). Adequate
analytical tools should be implemented, such as labor market tracer surveys.
Technical education and vocational training will also be key to Tanzania’s development.
Some of the key required actions that this ESA highlights for the subsector include:
• Strengthening the subsector’s coordination mechanisms. Although regulatory and
quality assurance bodies provide important guarantees for the controlled development
of the TVET subsector, it still faces a series of challenges, including: (i) the diversity of
training demand linked to the heterogeneity of the target population; (ii) the institutional
fragmentation of technical education, under the umbrella of various ministries; (iii) the
fragmentation of vocational education and training service delivery, involving two
ministries and a parastatal agency; and (iv) the practical continuity between vocational
and technical curricula and programmes, although theoretically bridges do exist, as
defined by the national qualifications’ framework;
• Revising subsector budget trade-offs. The Tanzanian TVET system as a whole is not as
underfunded as in many other African countries. However, technical nonhigher
education absorbs almost 57 percent of all TVET resources, against just 37 percent for
vocational training, and six percent for folk education. This funding imbalance should
be reduced in order to scale-up vocational education and training activities; and
Tanzania Education Sector Analysis 10
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• Defining a funding formula to rationalize the allocation of resources among technical
institutions. Surprisingly, it has been noticed that planning and welfare courses are twice
as expensive as health and allied science courses. However, even for a given subject
area, and among institutions with comparable levels of enrollment, variations in the
resources allocated are sizeable. This situation merits an improved funding formula and
for more coordination in planning and budgeting among parent ministries.
More broadly, this ESA offers valuable and comprehensive resources to anyone interested
in the education sector in Tanzania. It is however a snapshot of the system at a particular
time. As the sector makes progress in implementing its sector plan, this report’s findings
are therefore likely to become outdated, although many features will remain valid. It is the
hope of both the Ministry of Education and development partners that this document will
be of use to all stakeholders in the education sector.
Tanzania Education Sector Analysis 11
Dr. Shukuru
Kawambwa (MP)P)
Minister of Education and
Vocational Training
Tanzania
Vibeke Jensen
Director
and Representative
UNESCO Dar es Salaam
Office for Comoros,
Madagascar,
Mauritius, Seychelles
and Tanzania
Ann Therese Ndong-Jatta
Director
Regional Bureau
for Education in Africa
UNESCO
1 The Education Sector Management Information System (ESMIS) Programme is implemented by the government of Tanzania with
the financial and technical support of development partners (the European Union, UNESCO, UNICEF, and UNFPA), within the
overall framework of the Education Sector Development Programme for 2008-17. The UNESCO Institute of Statistics is providing
technical assistance through its permanent Dar es Salaam cluster office.
2 The Sectoral Analysis and Management of the Education System (SAMES), also known as the PSGSE (Politiques Sectorielles et
de Gestion des Systèmes Educatifs) is a masters degree offered by the University Cheikh Anta Diop of Dakar (Senegal) with the
support of the Pôle de Dakar, targeting Ministry of Education staff and other actors working in the field of education in Africa.
The training is currently available in French. An English course is currently under development with the University of The Gambia.
For the purpose of this ESA, all training modules were translated into English and made available to BERE.
Tanzania Education Sector Analysis 12
Abbreviations
A
b
b
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v
i
a
t
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s
ACSEE
AE/NFE
BE-MIS
BERE
BEST
BREDA
CBET
COBET
CSEE
ESA
ECCD
EMIS
ESMIS
FDC
GDP
GER
IIEP
ILFS
HBS
HESLB
HLI
LGA
LIC
MCDGC
MoEVT
MoFEA
Advanced Certificate of Secondary Education Examination
Adult Education and Nonformal Education
Basic Education - Management Information System
Bureau of Educational Research and Evaluation
Basic Education Statistics in Tanzania
Regional Bureau for Education in Africa
Competence Based Education and Training
Complementary Basic Education in Tanzania
Certificate of Secondary Education Examination
Education Sector Analysis
Early Childhood Care and Development
Education Management Information System
Education Sector Management Information System
Folk Development College
Gross Domestic Product
Gross Enrollment Rate
International Institute for Educational Planning
Integrated Labor Force Survey
Household Budget Survey
Higher Education Student Loan Board
Higher Learning Institution
Local Government Authority
Low-Income Country
Ministry of Community Development, Gender and Children
Ministry of Education and Vocational Training
Ministry of Finance and Economic Affairs
Tanzania Education Sector Analysis 13
MRY
NACTE
NBS
NECTA
NGO
PEDP
PMO-RALG
PSLE
PTR
SACMEQ
SADC
TCU
TDHS
TE
TVET
UDSM
UIS
UNESCO
VET
VTC
Most Recent Year
National Council for Technical Education
National Bureau of Statistics
National Examinations Council of Tanzania
Nongovernmental Organization
Primary Education Development Plan
Prime Minister’s Office - Regional Administration and Local Government
Primary School Leaving Examination
Pupil to Teacher Ratio
The Southern and Eastern Africa Consortium for Monitoring Educational Quality
Southern African Development Community
Tanzania Commission for Universities
Tanzania Demographic and Health Survey
Technical Education
Technical and Vocational Education and Training
University of Dar es Salaam
UNESCO Institute of Statistics
United Nations Educational, Scientific, and Cultural Organization
Vocational Education and Training
Vocational Training Center
Executive Summary
1. In a context of high demographic pressure, Tanzania has mobilized important
public resources to adequately address the growing demand for education.
The total population is expected to grow by 32 percent between 2010 and 2020. Over the
same period, the under 15 years age-group will remain constant at 44.2 percent of the total.
The primary school-aged population (seven to 13 years) is projected to reach 10.2 million by
2020, corresponding to an additional 1.8 million children compared with 2009.
Tanzania Education Sector Analysis 14
The government has given high budget priority to the education sector: in FY 2008/09,
education was allocated about 26.5 percent of government recurrent expenditure after debt
service, higher than the East African Community average (25.1 percent), and than the other
African low-income countries’ average (21.4 percent). In terms of GDP, the increase is
significant: from 2.5 percent of GDP in FY 2000/01 to 4.3 percent of GDP in FY 2008/09, a
value that is also higher than the average for all African low-income countries (3.3 percent).
Population (million)
Annual Growth Rate (%)
Sex Ratio (number of boys per 100 girls)
Population Under 15 Years (% of total)
Urban Population (% of total)
Demographic Trends and Projections, 1967-2020
12.3
n.a.
95.2
—
6.4
34.4
3.0
96.0
46.5
23.1
43.2
2.9
96.9
44.4
26.3
Census-Years
1967 2002 2010 2020
NBS-Projections
57.1
2.8
98.6
44.2
29.7
2000/01
2004/05
2008/09
Percentage of Actual Public Expenditure Allocated to Education
—
16.6
6.1
—
1.19
0.56
—
20.4
18.2
Recurrent
Expenditure
Development
Expenditure
Total
Expenditure
% of Total
24.3
23.3
26.5
% of Total,
(after debt)
2.5
3.1
4.3
% of GDP % of GDP % of Total % of GDP
—
4.3
4.9
Source: NBS data and projections (NBS, 2006; URT, 2005); and authors’ estimates.
Source: Authors’ calculations based on Tables 1.3, 1.4, 1.5 and 1.6.
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• Improved government capacities to mobilize significant resources directly from national
income. This has indeed allowed domestic revenues to increase from 9.2 percent of
GDP in FY 1998/99 to 15.9 percent of GDP in FY 2008/09. It is imperative that the
government supports this favorable trend in domestic revenue collection, to reduce
its dependency on foreign aid, which has represented almost 40 percent of total public
resources since FY 2002/03.
2. The allocation and use of public education resources is still not optimal however.
The increase in recurrent public education expenditure has been followed by significant changes
in subsector allocations. Over the decade, the share of primary education (including preprimary
education) has decreased from 58 percent to 48 percent, a level similar to that of other
countries close to achieving universal primary education. Most primary education savings have
benefited higher education, whose share of resources has increased to 27 percent of the total
education budget, making the subsector one of the best financed among African countries.
Secondary education continues to be heavily underfunded. In 2008/09, it absorbed 13.5
percent of education public resources; a level far below countries that are equally close to
achieving universal primary education.
Tanzania Education Sector Analysis 15
500,000
450,000
400,000
350,000
300,000
250,000
200,000
1
9
9
8
2
0
0
0
2
0
0
2
2
0
0
4
2
0
0
6
2
0
0
8
2
0
0
9
*
*
2
0
1
0
*
*
2
0
1
4
*
*
1
9
9
9
2
0
0
0
2
0
0
2
2
0
0
4
2
0
0
6
2
0
0
8
2
0
0
9
*
*
2
0
1
0
*
*
2
0
1
4
*
*
Constant 2001 T Sh
GDP per Capita Annual GDP Growth Rate
9.0
8.0
7.0
6.0
5.0
4.0
3.0
2.0
Percent
GDP Trends (FY) 1998/99-2008/09 and Projections
Source: Based on Table 1.3.
Note: **Projections.
Along with the high budget priority given to the education sector, this positive evolution
was also made possible following:
• Impressive and sustained economic growth registered over the last decade. Over the
2000-08 period, the average annual economic growth rate was estimated at 7.1
percent, a higher figure than the African low-income countries’ average, of 6.2 percent.
This trend is likely to strengthen given that average GDP per capita (about US$ 565 in
2010) remains lower than the African low-income countries’ average (US$ 800).
Tanzania Education Sector Analysis 16
This situation has led to a sharp 50 percent reduction in public spending per student at the
secondary level, while it has increased in all other subsectors. The Tanzanian secondary unit
cost is only two-thirds of the African LIC average, while the higher education unit cost (the
average for university and higher technical education) is 20 percent higher. While the
government’s strategy to expand secondary education is not matched by current budget
trade-offs within the sector, options to increase secondary education funding must be
explored to ensure the quality of the service delivered is not harmed. Although it may not be
possible to reallocate funds from higher education to secondary, the government should look
for efficiency gains and/or potential cost-saving measures within the higher education sector.
The TVET system is better funded than in many African countries, receiving seven percent of
public education resources, against five percent on average for the latter. However, main
allocation issues stem from funding imbalances amongst its different subsectors. Indeed,
while technical nonhigher education absorbs almost 57 percent of all TVET resources,
vocational training receives just 37 percent, against a low six percent for folk education. This
funding imbalance should be reduced in order to scale-up vocational education and training
activities. For technical education, the high level of randomness in resource allocation among
institutions is a problem, that is mainly linked to striking unit costs in specific programs.
Source: Tables 3.2 and 3.3 and authors’ calculations based on MoFEA and EMIS data for Tanzania; and Pôle de Dakar/UNESCO-
BREDA for other countries.
Note: * Based on countries with similar primary school duration (7 years) and closer to UPE; ** Based on countries with similar secondary
school duration (7 years) and closer to UPE; *** Based on the averages of all African low-income countries for which data were available.
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Primary
Secondary
TVET
Technical Nonhigher
VETA
Folk Education
Higher Education
University Education
Technical Higher
Other
Preprimary
Teacher Training
Adult and Nonformal Education
Total
Mainland Tanzania (2008/09) Comparable African Countries’ Average
Comparison of the Allocation of Public Recurrent Education Expenditure,
by Cycle, Tanzania and Selected African Countries’ Average, 2006 or MRY
44.2
13.5
7.0
4.0
2.6
0.4
26.9
23.6
3.4
8.3
4.5
2.5
1.3
100.0
43.6
26.3
5.0
—
20.8
—
4.8
—
100.0
*
**
***
***
***
The way resources are used highlights potential room for improvement. Indeed, evidence
shows that:
• Basic education focuses too little on spending that directly improves the quality of the
service delivered;
• In secondary education, capitation grant spending is 40 percent lower than the norm,
and student meals absorb four times as much of the budget;
• Teacher training colleges also overspend on student meals, to the tune of 90 percent
of nonsalary expenditures;
• Preprimary and primary pupil to teacher ratios are excessively high, partly because high
salaries constitute a constraint to further recruitment. Secondary PTRs are also well
above par, due to a quantitative and qualitative shortage of teachers; and
• In higher education, social spending is excessive (28 percent of higher education unit
costs not including scholarships for study abroad), and inequitable (almost 48 percent
of students receive a loan, although less than 10 percent are from the poorest quintiles).
3. Households and the private sector contribute considerably to the cost of
schooling, at varying degrees according to the level of education.
Households contribute significantly to education funding; their spending is equivalent to 32.1
percent of public education expenditure. This is however comparatively lower than in other
LICs (48 percent on average). Despite the fee-free primary policy, household contributions
remain important: a quarter of primary public education costs are covered by households.
This raises some concern as for the poorest households, as it might be a major obstacle to
send their children to schools. At the higher education level, the cost-sharing mechanism
seems to be effective, reducing the government’s financial burden. But its effectiveness over
the long run will very much depend on the capacity of the HESLB to recover loans.
Tanzania Education Sector Analysis 17
Secondary Education Public Unit Costs, (FY) 2000/01 - 2008/09
280
260
240
220
200
180
160
140
120
100
2
0
0
0
/
0
1
2
0
0
1
/
0
2
2
0
0
2
/
0
3
2
0
0
3
/
0
4
2
0
0
4
/
0
5
2
0
0
5
/
0
6
2
0
0
6
/
0
7
2
0
0
7
/
0
8
2
0
0
8
/
0
9
T
S
h
(
’
0
0
0
s
)
136
269
248
Thousands of Constant 2008/09 T Sh
Source: Authors’ calculations based on MoFEA and BEST and EMIS data.
Tanzania Education Sector Analysis 18
International Comparison of Household Spending on Education, by Level, 2009 or MRY
Percentage Equivalent of Public Recurrent Education Expenditure
Primary Secondary Higher/Tertiary Average
90
80
70
60
50
40
30
20
10
0
48
32
30
53
83
21
41
26
Mainland Tanzania
African LICs
The role of the private sector varies greatly across sectors. On the one hand it is marginal at
the preprimary and primary levels (where expansion has mainly been supported by the public
sector), and decreasing at O-Level and to a lesser extent at A-Level, following the government’s
policy of increasing secondary access. On the other hand, the expansion of the teacher training
and higher education subsectors increasingly relies on cost-sharing, favoring the development
of private sector contributions. In 2009, 39 percent of students were enrolled in private Teacher
Training Colleges, against five percent in 2004. In technical education, all folk development
courses are government-run, but those delivered through vocational centers are increasingly
private, reflecting the ministry’s policy of diversification to promote the subsector.
Source: Table 3.5 for Tanzania; Rwanda CSR, 2010 and Brossard et al., 2008 for 17 African low-income countries.
Note: 18 African low-income countries are considered here: Benin, Burkina Faso, Cameroon, Chad, Congo, Côte d’Ivoire, Djibouti,
Guinea Bissau, Madagascar, Malawi, Mali, Mauritania, Niger, Rwanda, Senegal, Sierra Leone, Togo and Uganda.
Source: BEST, NACTE, TCU, various years; authors’ computations for Tanzania. World Bank and Pôle de Dakar/UNESCO-BREDA for
other countries.
Note: * Refers to NACTE-registered institutions.
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Preprimary
Primary
O-Level
A-Level
Teacher Training
Technical Education *
VET (VTC Long Courses)
Higher Education
Share of Students Enrolled in Nongovernmental Institutions, 2004-09
Percent
1.3
0.6
38.0
48.6
5.4
—
—
7.4
2.3
1.0
26.6
38.6
9.3
15.5
67.8
19.4
7.8
1.3
14.2
36.4
23.7
16.2
—
23.9
Tanzania
2004 2006 2008 2009 2009 or MRY
Average LIC
5.0
1.5
10.8
32.3
38.6
—
—
28.2
—
16.7
20.4
27.7
—
—
—
19.5
Tanzania Education Sector Analysis 19
4. School enrollment has increased at all levels.
The preprimary sector is comparatively well developed. The policy to mainstream the provision
of preprimary teaching through primary schools (thus controlling unit costs) has enabled a
growing number of young children to benefit from this level. Coverage at the preprimary level
reached 37 percent in 2009, up from 26 percent in 2004. This is a very reasonable level of
preschool attendance compared with the 20 percent average of other countries in the region.
Source: Table 2.1, and census projections for Tanzania.
Note: * TVET includes VTC and FDC long courses, and nonhigher technical education; ** Higher education includes universities,
university colleges and higher technical education.
Tanzania is on the way to reaching universal primary education, but late entry still remains
a major challenge and many children are still out of school. Access to Standard I is almost
universal, although 5.5 percent of children did not have access to primary school in 2006.
The primary completion rate has steadily increased over the past decade, to reach at least
89 percent in 2009. The fee-free primary education policy and extensive classroom
construction have had positive impacts on both primary access and retention levels. The
system is still marked by considerable late entry however: only 36 percent of Standard I
students were of official school-age in 2006.
Source: DHS, 2004; HBS, 2000/01 and 2007; authors’ computations.
Age at Standard I
P
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n
t
1.0 0.4
5.0
3.8
11.0
17.0
22.6
36.0
23.0
30.7
22.0
19.0
20.5
14.0
17.0
11.8
9.0 9.0
5.1
2.0
5.0
3.0
2.0
5.0
2.1
1.0
Age Distribution of Standard I New Entrants, 2000, 2004 and 2006
Percent
5 6 7 8 9 10 11 12 13+
40
35
30
25
20
15
10
5
0
2000
2004
2006
3.0
2003
2004
2005
2006
2007
2008
2009
Preprimary Primary
Secondary
O-Level
GER (%) Per 100,000 inhabitants
A-Level All
TVET *
Higher
Education **
Schooling Coverage, by Level, 2003-09
Percent, and Students per 100,000 inhabitants
—
26.3
29.3
29.8
34.4
36.7
36.6
104.5
109.5
113.1
115.9
117.6
115.4
112.4
10.5
12.8
15.2
19.0
28.3
33.0
38.6
1.9
2.2
2.3
3.0
3.4
3.6
3.9
7.8
9.5
11.2
14.0
20.5
23.8
27.7
—
—
—
235
—
252
250
—
—
—
174
—
291
335
Tanzania Education Sector Analysis 20
This situation tends to inflate out-of-school statistics. Indeed, among the 925,000 estimated
out-of-school (representing 13 percent of primary school-aged children in 2006), 88 percent
had never attended. Should all children enter on time, the number of children estimated to
never attend school would drop to 425,500. Given its detrimental impact on schooling
paths (exposing them to greater risk of early dropout), ensuring that children attend school
at the correct age should be a priority. MoEVT may address both supply and demand
constraints, for instance through sensitization campaigns to alter parents’ perceptions about
the appropriate age for school attendance, assisted further by the expansion of ECCD
programmes.
School coverage at secondary and higher education levels is still low compared with other
African countries, but is rapidly increasing, especially at the higher education level. School
coverage is particularly low at A-Level, where only four out of 100 school-aged children
were enrolled in 2009, one of the lowest rates of all African low-income countries. The
situation is less problematic at O-Level, for which the GER reached 39 percent in 2009, up
from a low 10.5 percent in 2003.
Considerable emphasis has been put on higher education, to adequately meet the growing
demand from secondary school leavers and produce skills relevant to current and future
economic growth. University enrollment has grown at an average annual rate of 30 percent
over 2005-09, among the highest annual growth rates registered for all subsectors (although
it started with lower enrollment), allowing Tanzania to rapidly catch up with the levels of
comparable developing countries. In 2009, the number of higher education students in
Tanzania was 36 percent lower than the average, down from 50 percent in 2006. However,
university and technical higher education coverage remains low, at 335 students per 100,000
inhabitants in 2009/10, against 381 students per 100,000 in other low-income countries.
Source: Table 2.8 for Tanzania; World Bank and Pôle de Dakar/UNESCO-BREDA for other countries.
Note: To allow for international comparisons: * TVET includes VET and FDC long courses and NACTE-registered technical nonhigher
education; and ** Higher education includes universities, university colleges and technical higher education.
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Tanzania (2008)
Burundi
Kenya
Rwanda
Uganda
East African Community Average
African Low-income Countries
Average
Min – Max
Preprimary Primary
Lower
Secondary
GER (%) Per 100,000 inhabitants
Upper
Secondary
TVET * Higher
Education **
International Comparison of Enrollment, by Level, 2008 or MRY
Percent, and Students per 100,000 inhabitants
36.7
5.4
54.0
18.0
3.7
23.5
20.4
0.8 – 141
115.4
115.3
114.7
151.0
120.7
122.8
103.1
56.9 – 157.7
33.0
22.9
94.6
28.0
28.1
42.4
43.4
15.9 – 94.6
3.6
6.0
39.6
9.0
10.3
13.7
17.2
2.6 – 39.6
252
156
74
440
115
212
228
35 – 484
291
243
359
474
329
337
381
61 – 1009
Tanzania Education Sector Analysis 21
TVET education coverage in Tanzania is higher than in other low-income countries (250
students per 100,000 inhabitants in 2009, compared with 228 students per 100,000).
Seventy percent of TVET students are registered on vocational courses (in VTCs and FDCs),
whereas 30 percent are in nonhigher technical learning streams. The sector still falls short of
the huge needs in TVET programmes for primary and secondary school leavers. The current
annual flow of students into vocational education represents less than five percent of the
potential demand for VET services, while technical nonhigher education covers about 22
percent of potential demand. This underlines the urgency for the diversification of TVET
provision, offering more short and tailor-made courses to enhance productivity and the quality
of products and services.
The number of teacher trainees has increased over the decade, with the exception of the
2007-08 period that registered a decrease in TTC trainees (places were more limited as a
result of the extension of the curricula from one to two years in 2006). However, given the
growing demand for teachers at all levels, the pursuit of the expansion of teacher training is
to be closely monitored and planned, so as to not jeopardize the development of the primary
and secondary school system.
Literacy programmes cover just a quarter of the target population. Similarly, COBET
programmes only cater for a small fraction of out-of-school children, and their efficiency in
mainstreaming children’s return to school is weak.
Access to postprimary levels still remains challenging for many children. Although strong
improvements in access to secondary have been noted, especially at O-Level, they are still
limited. In 2009, half of children had access to O-Level and 23 percent were able to reach
the last grade of the cycle, against just eight percent in 2003. A-Level access is still strikingly
low, at five percent. Whereas lack of supply is a major hindrance to O-Level and A-Level
access, economic difficulties and cultural issues among certain groups also contribute to
fragile school demand. With respect to the former, the policy to have a secondary school in
each ward has had a very positive impact on secondary access and on primary retention
rates. The pursuit of the policy is expected to improve both O-Level and A-Level access and
retention in the coming years.
Tanzania Education Sector Analysis 22
The increase in primary and secondary school enrollments is already putting a lot of strain
on secondary, TVET and higher education institutions, and enrollment at these levels is
expected to grow more rapidly still over the coming years. An urgent and well-planned
response is required to ensure the smooth and manageable development of the system and
that it remains in line with labor market needs. This raises both financial and practical
challenges (teacher requirements, classroom supply). A sectorwide financial simulation
model may help to explore policy options, assessing both facilities and required resources.
5. Dropout is still a problem at postprimary levels however, despite generally good
internal efficiency levels.
While internal efficiency is generally good, dropout remains a problem, particularly at
postprimary levels. Tanzania’s education system is comparatively efficient at both primary and
O-level, and its A-Level efficiency is in line with the African low-income countries’ average.
The primary IEC was estimated at 88 percent in 2007, implying that 12 percent of resources
are wasted due to repetition or dropout. Repetition being generally low (2.4 percent in primary
and under two percent in secondary, on average in 2009), dropout is the main source of
Education Pyramid for Tanzania, 2009
23%
3%
5%
55%
108%
108%
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Higher Education:
335 Students
per 100,000 inhabitants
TVET:
6% of Secondary
GER = 4%
GER = 39%
GER = 112%
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49%
33%
Source: Tables 2.8 and 2.11 and Figure 2.7.
Note: TVET refers to technical non-higher education and VET courses (both VETA and NACTE-registered).
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Tanzania Education Sector Analysis 23
Improving retention will necessarily require addressing both supply and demand constraints.
This could entail:
• Alleviating schooling direct and opportunity costs. Although most of the interventions
cited above (regarding the expansion of secondary education for instance) should also
favor primary school retention, special attention should be given to costs borne by
parents, that increase with successive grades and levels. School feeding programmes
and cash transfer programmes are being implemented to compensate, but further
cost-benefit analysis is necessary before expanding them, mainly because of their
notoriously high cost;
• Further improving school supply. Schools with incomplete cycles are known to
negatively affect retention. Although this issue appears to be marginal in Tanzania,
scope for improvement nevertheless exists at the primary level: satellite schools, known
to offer incomplete cycles, could possibly be converted into full-cycle schools through
multigrade teaching. At postprimary levels, building more schools will prove decisive;
and
inefficiency, especially at O-Level and A-Level. More efforts are needed to reduce dropout in
order to improve the overall internal efficiency of the system, and reduce resource wastage.
Source: BEST, various years.
Note: * Not provided as 2009 primary schooling patterns are highly affected by the multicohort phenomenon, which tends to
underestimate dropout; ** Because 2007 A-level repetition data were not available, the proportion observed in 2009 was assumed
to have remained constant over the period. The change in the A-Level IEC is therefore only related to the rise in dropout.
Primary
Internal Efficiency Coefficient
Dropout-Related (no Repetition)
Repetition-Related (no Dropout)
Years Required to Completion
O-Level
Internal Efficiency Coefficient
Dropout-Related (no Repetition)
Repetition-Related (no Dropout)
Years Required to Completion
A-Level
Internal Efficiency Coefficient
Dropout-Related (no Repetition)
Repetition-Related (no Dropout)
Years Required to Completion
Primary and Secondary Schooling Internal Efficiency Coefficients, 2000-09
67
69
97
10.5
82
83
98
4.9
—
—
—
—
88
92
96
7.9
83
85
98
4.8
83
84
99
2.4
2000 2007 2009
—
—
—
—
81
82
98
5.0
72
73
99
2.8
**
**
*
Percent and Number of Years
Tanzania Education Sector Analysis 24
• At the primary level, closely monitoring repetition would be helpful, especially for
Standard I, that has the highest proportion of repeaters. However, as ECCD
programmes expand and the school preparedness of children improves, this issue
should resolve itself. Assessing the relevance and quality of teaching would be
worthwhile, as dropout is often justified by a lack of interest in school.
6. Important disparities persist in access to formal schooling according to gender,
area of residence and especially families’ income levels; and, they tend to be
cumulative.
Beyond the primary level, girls’ participation in education is systematically lower than that of
boys. Gender parity indexes decrease from 1.04 (girls’ enrollment is greater than boys’) in
primary school to 0.65 at the higher/tertiary level. TVET is still slightly gender-oriented: male
students accounted for 55 percent of trainees in 2008. At the higher education level, female
enrollment has barely reached 34 percent: girls are doubly prejudiced by their lower chances
of reaching secondary school, and by their comparatively lower results in the ACSEE exam.
Schooling inequalities are particularly unfair to children from rural areas. Children from
urban areas have better access probabilities to all levels of education than their rural peers,
in part due to the inadequate supply of rural schools. The gap in the probability of access
reaches 23 percentage points for O-Level entry, and eight percentage points for A-Level
entry.
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Gender
Male
Female
Gender Parity Index (Female/Male)
(Memo: Index, 2000)
Area of Residence
Urban
Rural
Location Parity Index (Rural/Urban)
(Memo: Index, 2000)
Income Group
Q5 (The wealthiest)
Q1 (The poorest)
Wealth Parity Index (Q1/Q5)
(Memo: Index, 2000)
Total Tanzania
GERs and Parity Indexes, by Socioeconomic Characteristic, 2006
29.9%
27.2%
0.91
0.89
45.9%
23.8%
0.52
0.53
48.1%
23.0%
0.48
0.21
28.6%
114.6%
118.8%
1.04
0.95
119.6%
115.8%
0.97
0.79
125.3%
117.1%
0.93
0.82
116.6%
31.7%
30.2%
0.95
1.13
56.6%
21.9%
0.39
0.13
64.8%
19.1%
0.30
0.23
30.9%
7.2%
6.0%
0.83
0.95
16.2%
2.6%
0.16
0.09
26.8%
1.6%
0.06
0.19
6.6%
2.9%
1.9%
0.65
0.75
n.a. *
7.9%
0.0%
0.00
0.15
2.4%
Preprimary Primary O-Level A-Level Higher
Source: HBS, 2007, authors’ calculations.
Note: The location parity index is irrelevant to higher learning institutions, that are all located in urban areas.
Reading Note: A gender parity index of 0.83 (2006, A-Level) indicates that for every 100 boys enrolled, there were 83 girls.
Tanzania Education Sector Analysis 25
The unavailability of a school nearby is often a major hindrance (in some rural areas, 22
percent of children live over five kilometers away). There is clearly potential to build more
schools in underserved areas, compensating the cost by offering multigrade teaching under
close supervision. Lack of interest in school is also a major reason for nonattendance
(mentioned by 12 percent) that might be counter arrested by improving the relevancy and
quality of teaching.
Disparities in access increase sharply with successive levels of education, especially those
related to income. Wealth parity indexes decrease from 0.94 in primary school to 0.09 at
A-Level, and are virtually nil at the higher/tertiary level. Retaining the poorest students in
primary schools and ensuring their transition to postprimary cycles is a major challenge.
Although the abolition of school fees has been a major measure in alleviating education
expenses, the poorest households still face prohibitive schooling costs (uniforms, stationery,
books, and so on). Interventions specifically targeting these households, such as cash
transfers, may help to remove economic and financial barriers. Better coverage of the
scholarship grants and remedial classes should make schooling more equitable for the poor.
Furthermore, disadvantages tend to be cumulative. Poor rural girls face the worst access
conditions, and disparities tend to broaden as of the end of primary (for every 100 rich urban
boys completing primary, only 53 poor rural girls do). They then explode at postprimary levels,
leaving poor rural girls with virtually no opportunities to pursue secondary education.
Finally, literacy programmes targeted at parents should give positive results, mainly by
gradually overcoming cultural barriers to education. The encouragement of families and
schools to ensure that all children have birth certificates (although not strictly an education
sector intervention), may also have a positive impact on school access and retention.
Access disparities by region are equally marked. For instance, primary access and retention
are particular issues in Rukwa, Tabora and Dodoma regions. Beyond school supply
constraints, economic, cultural and environmental issues (agro-pastoral activities, cultural
beliefs, tobacco production and climate conditions) shape demand and keep children out
of school. In 2006, secondary access probabilities were as low as four percent in one region,
and were just 16 percent in five others, well below the national average of 27 percent.
Extensive primary and secondary school construction has contributed to loosen school supply
constraints in many of those regions since.
Source: HBS, 2007: authors’ calculations.
Primary Access
Primary Completion
O-Level Access
O-Level Completion
A-Level Access
A-Level Completion
Cumulated Disparities in Schooling Profiles, by Extreme Group, 2006
Percent
98.8
94.2
55.4
36.5
21.3
12.8
Male/Urban/Q5 Female/Rural/Q1 Parity Ratio
92.5
50.1
7.1
1.1
0
0
0.94
0.53
0.13
0.03
—
—
Socioeconomic Status
Q1
Q2
Q3
Q4
Q5
Area of Residence
Rural
Urban
Gender
Girls
Boys
Benefit Incidence of Public Education Resources, by Level of Income,
Area of Residence, and Gender, 2009
Percent, and Appropriation Index
27.0
23.8
20.0
17.3
11.9
74.0
26.0
52.3
47.7
Share of the
Population
(%)
(a)
12.7
15.4
21.1
18.0
32.8
47.1
52.9
45.7
54.3
Public
Resources
Absorbed (%)
(b)
0.5
0.6
1.1
1.0
2.8
0.6
2.0
0.9
1.1
Appropriation
Ratio
(b)/(a)
1.0
1.4
2.2
2.2
5.9
1.0
3.2
1.0
1.3
Appropriation
Index
Tanzania Education Sector Analysis 26
TVET and higher education opportunities are also unequal across areas and regions. Just
five regions (Dar es Salaam, Iringa, Arusha, Kilimanjaro and Mwanza) are home to almost
55 percent of VTCs. HLIs are also particularly present in cities and the eastern part of the
country. The expansion of open distance learning will be crucial in breaking the urban/rural
fracture.
Regional Disparities in Primary Access and Retention Probabilities, 2006
Primary Access Probability (%)
P
r
i
m
a
r
y
R
e
t
e
n
t
i
o
n
P
r
o
b
a
b
i
l
i
t
y
(
%
)
110
100
90
80
70
60
50
40
88 90 92 94 96 98 100 102
Tabora
Kigoma
Arusha
Kilimanjaro
Dar
Iringa
Mara
Ruvuma
Kagera
Mbeya
Tanga
Mwanza
Shinyanga
Lindi
Morogoro
Mtwara
Singinda
Dodoma
Manyara
Rukwa
Pwani
Source: Authors’ calculations based on probabilistic profiles using HBS, 2007 data.
Source: Authors’ calculations based on Annex Table 5.8.
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Tanzania Education Sector Analysis 27
The distribution of public education resources is therefore unequal, benefiting the most
privileged students. Indeed, the 10 percent most educated benefit from 47 percent of public
education resources, in line with the LIC average. The benefit incidence analysis further
shows that boys benefit from 30 percent more public education expenditure than girls. Due
to longer schooling, 33 percent of public resources are allocated to the 12 percent of
students from the most privileged households, and those belonging to the poorest families
only benefit from 13 percent of these resources, despite representing 27 percent of the
population.
Further action is required to support pro-poor schooling, ensure a more equitable
development of the education system and ultimately of society. The opportunity cost may
be to favor future iniquities and the intergenerational transmission of poverty.
7. Quality continues to represent an important challenge to the sector, as
demonstrated by the modest level of learning outcomes.
Although the dynamic of improvement in learning outcomes observed in primary education
between 2000 and 2007 is very encouraging, and good compared to neighboring countries,
learning achievements are modest by international standards.
SACMEQ Reading and Mathematics Scores, 2007
SACMEQ Scores
SACMEQ Score
Mauritius
Kenya
Tanzania
Seychelles
Swaziland
Botswana
Zimbabwe
SACMEQ
South Africa
Zanzibar
Mozambique
Uganda
Lesotho
Namibia
Malawi
Zambia
300 400 500 600 700
623
574
434
Math: 553
Reading: 578
Math: 510
Reading: 512
Math
Reading
Source: SACMEQ 2007 data; IIEP, 2010.
Tanzania Education Sector Analysis 28
National examination pass rates are dropping, and the results of those who graduate are
low, especially at primary and O-Level, implying that too few leave the cycle with an
adequate level of mastery of the programme. In 2009, barely 50 percent of candidates
passed the PSLE, down from 70 percent in 2006. This could be explained by the increase in
the number of students with learning difficulties following the implementation of the fee-
free primary education policy, that was not followed by adequate measures (no sufficient
classes and remedial courses, rising PTRs, lack of textbooks) or by the more strict secondary
school access criteria. At O-Level, the share of graduates is also declining, and reached 66
percent in 2009.
Scores are skewed toward Grade C at PSLE, and toward Division IV (the minimum level) for
81 percent of O-Level graduates. Performance is particularly poor in mathematics and
sciences.
PSLE Core Subjects’ Grade Distribution, by Gender, 2009
Math English Kiswahili Social Studies Sciences
M
a
l
e
F
e
m
a
l
e
M
a
l
e
F
e
m
a
l
e
M
a
l
e
F
e
m
a
l
e
M
a
l
e
F
e
m
a
l
e
M
a
l
e
F
e
m
a
l
e
100%
80%
60%
40%
20%
0%
Fail
C Grade
B Grade
A Grade
75
19
13
83 62
24
21
68
29
39
40
33
35
39
33
48
40
36
53
40
Source: NECTA statistical yearbooks; authors’ computations.
Source: Department of Secondary Education - MoVET, 2010; authors’ computations.
Note: Divisions I to IV are considered as a pass.
O-Level results were also found to be strikingly poor in community schools, which enroll
the majority of students, and represent the pillar of MoEVT’s policy to increase secondary
school access. More analysis is required to adequately assess O-Level quality issues, for which
improved EMIS data will first be required.
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Public
Community
Nongovernmental
Seminaries
Total Mainland
School Candidates’ CSEE Pass Rates and Score Distribution, by Type of School, 2009
12,046
161,277
52,131
5,223
230,677
82.2
67.7
82.0
89.3
72.2
6.8
1.1
4.5
13.7
2.6
Number of
Candidates
Pass
Rate (%)
I II III IV
Distribution of Pass Grades/Divisions (%)
9.2
4.3
8.5
15.4
6.0
22.9
13.6
19.5
25.4
16.1
61.1
81.0
67.5
45.5
75.3
Tanzania Education Sector Analysis 29
At A-Level, the situation is generally better, although pass rates have fallen slightly, to 89
percent in 2009. School candidates systematically outperform private ones, both in quantity
(with respective pass rates of 93 percent and 74 percent in 2009), and in quality (12 percent
and 38 percent reached the minimum level). Half of school candidates score a Division III
grade, a quarter scores a Division II grade and 14 percent a Division I grade, a result almost
never attained by private candidates. Gender disparities are minimal. The globally good
scores could be due to only the best and most fortunate students reaching A-Level.
Implementing mechanisms to adequately monitor learning outcomes will be important given
the rising number of O-Level graduates to enroll and the introduction of the new A-Level
curriculum in 2010.
In VET, 78 percent of long course students completed their year in 2008; 58 percent entered
an exam, 80 percent of whom passed. As far as technical education and higher education
examination results are concerned, high levels of success (above 82 percent) are observed,
although the low number of candidates sitting the exam implies that those who do are the
best performers. The fact that many students bear the cost of their studies has probably
encouraged greater care in the choice of courses, and greater responsibility in learning. No
gender differences are apparent in success rates or the quality of results, although relatively
fewer girls sit higher examinations, and their participation drops the higher the award
involved.
The objective that all children should achieve acceptable levels of learning is made all the
more elusive by the disparities in achievements, although these have narrowed over the
years. At both primary and O-Level, disparities in results exist according to gender, wealth
and area of residence. Although the analysis of SACMEQ scores over 2000-07 shows that
disparities are narrowing, it also pinpoints that: (i) the poorest children’s performance is
starkly below that of their wealthier peers; and (ii) disadvantages tend to be cumulative:
poor rural girls perform the worst. Girls underperformance at CSEE is of particular concern.
Share of Students Reaching Minimum SACMEQ Levels in Reading
(Kiswahili) and Math, by Socioeconomic Characteristic, 2000-07
2000 2007 2000 2007
100%
80%
60%
40%
20%
Reading
Math
Urban
25% Richest (Q4)
Boys
Girls
Rural
25% Poorest (Q1)
Source: SACMEQ, 2000, 2007 data; MoEVT.
Tanzania Education Sector Analysis 30
8. Education does nevertheless have an important impact on social and human
development.
Education, especially primary education, has an important impact on literacy, poverty,
fertility, and maternal and child health. From 7.7 percent for uneducated individuals, the
probability of being literate increases to 87.3 percent for those with full primary education
and to 99 percent for O-Level leavers. Women who have never attended school benefit
from antenatal care from a health professional for only 73 percent of pregnancies, whereas
Raising the quality of basic education will require a multipronged strategy. Based on the
factors found to have a significant impact on learning, and pending further data on and
analysis of learning outcomes and the school/class environment, some policy orientations
can be formulated.
A national student learning assessment system will also prove crucial in the current context
of curricula changes and decentralization. This should track individual exam results and link
data to past performance and school/class inputs. Setting clear benchmarks for early grades
core learning outcomes (especially in math and literacy) will help teachers and parents to
monitor pupils’ progress and weaknesses, and enable timely remedial measures.
Finally, the use of English as the main teaching language in secondary education could be
reviewed in favor of a more gradual phasing in throughout schooling careers, to ensure that
students master the language adequately by the level they are expected to use it to learn.
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Increase student learning time
Set up remedial classes to reduce repetition
Promote preschool attendance
Support poorer children
Involve communities in school management
Favor girls’ education activities
Upgrade teachers’ qualifications to set standards
Provide students with textbooks in key subjects
Improve the coherence of teacher allocation
Equip schools with latrines
Potential Measures to Improve Basic Education Learning Achievements
++
+++
++
++
+++
+++
++
+++
Impact Cost Impact Cost
Primary O-Level
$ (1)
$
$ to $$$ (2)
$ to $$$ (3)
$
$
$ to $$ (4)
$
+++
+++
+++
+++
$ to $$ (4)
$
$ to $$$ (5)
$$
Source: Synthesis of Tables 4.5 and 4.8.
Note: + Low impact, ++ medium impact, +++ high impact; $ low cost, $$ costly, $$$ very costly. The level of impact has been assessed
based on the regression results; the level of cost is based on estimated unit costs. Costs may vary greatly according to the type of
services offered. (1) Improving teacher and student attendance records could reduce absenteeism at a fairly low cost; (2) Community-
based preschool attendance will be much cheaper than enrollment in the regular preschool system; (3) Depending on the type and
amount of support/transfers provided; (4) In-service training would be a low-cost option; (5) costs may be very much inflated whether
the incentive packages require the construction of teachers’ quarters or not, or if the recruitment of additional teachers is needed.
Tanzania Education Sector Analysis 31
The primary level thus has the greatest impact on social outcomes, contributing to almost
60 percent of the total impact of education on social development, which further reinforces
the justification for efforts made to ensure that all Tanzanian children complete at least the
primary cycle. At equal investment, the efficiency of the primary cycle in enhancing human
development is 2.4 times higher than that of the secondary cycle.
9. The sector also has a direct connection to labor market requirements.
Tanzania’s labor force has a better education profile today than in 2001, although highly
qualified human capital remains limited. The share of individuals aged 15 to 60 years with
secondary education and above increased from 5.6 percent to just seven percent between
2001 and 2006. Although progress is slow, the number of individuals with tertiary or higher
education has more than doubled over the period. Over the same period, the average
number of salaried jobs created has increased by about 10.3 percent per year, casting some
doubts on the absorptive capacity of the salaried employment sector (the main supplier of
jobs for higher education leavers), to adequately absorb the growing number of higher
education leavers. To maintain this growth rate, policy makers should assess the ability of
those who have completed primary education are assisted in 81 percent of all cases, and
those who have completed O-Level do so for 85 percent of pregnancies. Age at first
childbirth ranges from 18 years for uneducated women to 21 years for those with complete
secondary, a three year difference.
Source: Authors’ calculations based on TDHS, 2004/05 data.
Note: * Literacy: based on 5,107 men and women aged 22 to 44 years, assessing the probability of being literate; ** Poverty:
based on 6,838 household heads, assessing the relationship between the probability of a household belonging to the first poverty
quintile (Q1) and the level of schooling of the head of household. The poverty measure is based on a wealth index derived from
available assets in the household; *** Child health: based on 6,650 children aged under five years, assessing the relationship
between women’s schooling and the probability that their child is given vitamin A; # Other indicators: based on 4,020 to 5,684
women aged 15 to 49 years, with at least one childbirth for the probability of being assisted at delivery by a qualified health
professional, and at least two childbirths otherwise.
Reading Note: Figures are not simple descriptive statistics of the different phenomenon according to the highest education level
completed; they result from econometric models that identify the net impact of education with all other variables (gender, age,
area of residence, income level) held constant. So, the simulated net probability of literacy for a person having completed A-Level
is 99.7 percent. This rate being simulated means that it is for a theoretical individual with the same socioeconomic characteristics
as an average Tanzanian person, but with complete secondary education.
Literacy
Extreme Poverty
Woman’s Age at First Childbirth (Years)
Total Births (Number)
Probability of Receiving Antenatal Care
Probability of Professionally Assisted Birth Delivery
Probability of Receiving Vitamin A Treatment
Simulated Net Impact of Education on Social Behavior, 2004/05
81.9%
23.3%
19.0
4.0
80.8%
47.4%
22.1%
7.7%
62.9%
17.9
4.5
73.5%
31.6%
8.7%
87.3%
21.9%
19.5
3.8
81.2%
53.3%
18.6%
98.8%
9.1%
20.5
3.4
84.8%
75.5%
27.3%
99.7%
5.6%
20.9
3.2
86.3%
85.3%
32.5%
None
Average
Primary O-Level A-Level
Highest Level Completed
Tanzania Education Sector Analysis 32
higher education leavers to join the nonwage sector and become self-employed, for
instance. Indeed, according to the regional pattern, Tanzania should have about 570,000
higher education students in 2025. This should require enrollment growth of 8.8 percent
per year, much lower than in recent years. These issues should be discussed in the
framework of a simulation model relating the development of secondary education to that
of higher education.
Nevertheless, improved education leads to higher income. The wage premium for workers
with secondary education is particularly high, especially among A-Level leavers. This pattern
suggests that there is a severe shortage of secondary qualifications in the economy. The
average income of tertiary education (technical nonhigher) leavers depends very much on
their sector of employment, being close to that of O-Level leavers in the public sector, but
30 percent higher in the private sector (although still barely half the income of an A-Level
leaver). Individuals who never pursued their education beyond primary earn more in self-
employment than in the private sector.
Source: Authors' computations based on ILFS, 2006 data.
Note: * Too few individuals to compute reliable average income.
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Labor Force
Employed
Public Sector - Salaried
Private Sector - Salaried
Self-Employed or Family Business
Agriculture and Other
Unemployed
Inactive
Employment Status of the Labor Force (25-35 Years), by Level of Education, 2006
98.4
97.5
0.7
8.8
24.5
63.5
0.9
1.6
97.6
97.3
0.2
2.1
14.6
80.4
0.3
2.5
98.1
96.2
16.8
21.6
37.7
20.1
1.9
1.9
95.7
88.0
37.5
33.6
13.2
3.7
7.7
4.3
100.0
100.0
53.3
27.2
4.0
15.5
0.0
0.0
98.2
97.3
2.1
8.8
23.6
62.8
0.9
1.8
Average
No
Schooling
Tertiary/
Higher
Total
O-Level A-Level
Secondary
Percent
No Schooling
Primary
O-Level
A-Level
Technical Nonhigher
Higher education
Annual Income, by Education Attainment and Employment Sector, 2006
1,426
1,663
2,125
5,361
1,921
5,682
526
713
1,453
4,100
1,881
5,413
585
902
1,831
4,906
1,915
5,592
700
1,060
1,548
4,029
—
—
Public
Self-
Employment
(Nonagricultural)
Private Average
Wage Sector
Thousands of T Sh
Source: Authors' computations based on ILFS, 2006 data.
Tanzania Education Sector Analysis 33
VET training is particularly valued by the market. A tracer study conducted in April 2010 by
VETA documented the employment and income status of about five thousand VET graduates.
It showed that VET leavers’ average employment rate is close to 85 percent; their likelihood
of finding permanent employment is slightly higher still, and in about 87 percent of cases,
there was a direct connection between graduates’ training and their job. These results suggest
that the quality of skills and qualifications is reasonable, and that the main challenge is
unemployment. Indeed, VET graduate unemployment is close to 15 percent, mainly attributed
to a mismatch between training and the availability of related jobs and to the lack of resources
to start a business. This situation calls for policies both on the supply-side (improving the
relevance and professionalism of training for selected sectors) and the demand-side (assisting
graduates in mobilizing the required resources and assets). The possibility of devoting a share
of the skill development levy to business start-up funds should be assessed.
Strikingly, some VET education offers no significant added value over primary or O-Level. In
general, the income of VET graduates compares favorably with that of self-employed
individuals with primary education or O-Level. However, graduates with clothing and textile,
and hospitality and tourism sector skills appear to earn at best the same amount as primary
school leavers, which is worthy of more detailed analysis. On the other hand, VET courses
have provided significant added value to electricity or agriculture and food processing
graduates.
10. Education management needs to be improved, particularly on the administrative
and pedagogical fronts.
Tanzania has a shortage of teachers at both the primary and secondary levels. The pupil to
teacher ratio was 55 to 1 in government primary schools in 2009, well above the SADC
average and the national target (45 to 1). On the basis of the latter, the accumulated
shortfall of primary school teachers was 30,405. The secondary level PTR stood at 43 to 1,
Employment Rate of VET Graduates, by Sector, 2010
Agriculture & Food Processing
Construction
Clothing and Textile
Mechanics
Hospitality and Tourism
Electricity
Automotive
Business Administration
Other
60% 70% 80% 90% 100%
94%
92%
91%
88%
86%
82%
78%
75%
74%
Source: Preliminary results of the April 2010 VET Tracer Study, on 4,569 VET graduates (VETA, 2010).
Note: Other sectors include: ICT, laboratory technology, printing, mining, education (pedagogy, adult learning strategies, training
of trainers) and general subjects.
O-Level Only
Both Levels
A-Level Only
Total
Secondary Level PTRs and PqTRs, by Level and School Type, 2009
52:1
19:1
20:1
46:1
26:1
23:1
23:1
25:1
48:1
21:1
21:1
41:1
74:1
20:1
21:1
61:1
37:1
27:1
24:1
32:1
68:1
22:1
22:1
54:1
Nongvt. Gvt. Total Nongvt. Gvt. Total
PTR PqTR
Schools offering
Tanzania Education Sector Analysis 34
The proportion of qualified teachers has increased at the primary level, but has plummeted
at the secondary level, reaching 90 percent and 76 percent in 2009, respectively. The teacher
training system has shown difficulties to respond to the growing demand for teachers
following the surge in secondary enrollment. The lack of language, mathematics and science
teachers is a particular issue. Only 28 percent of teachers specialized in sciences in 2009 for
instance, down from 40 percent in 2004.
Analyses show poor consistency in teacher allocation across schools, both at the primary
and secondary levels, highlighting management flaws. The average degree of consistency
for school teacher allocation was 40 percent in 2007, meaning that 60 percent of teachers
were allocated according to criteria other than the level of enrollment. The results underline
the limits of current management practices and raise the issue of the need for new
monitoring tools to ensure more equitable deployment.
Primary Level PTRs, by School Type, 2000-09
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
70
60
50
40
30
20
10
0
48
21
56
25
53
24
54
22
56
55
23
47
59
57
21
46
28
53
46
41
Government Schools Nongovernmental Schools
P
T
R
Source: Regional BEST, 2000-07, BEST, 2008 and 2009.
Source: BEST.
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up from a low 19 to 1 in 2004, government schools accounting for most of the increase,
with the average PTR reaching 49 to 1 (against 23 to 1 in nongovernmental schools).
Tanzania Education Sector Analysis 35
The primary teaching profession is more financially attractive in Tanzania than in the
subregion. A Tanzanian primary school teacher earns about US$ 6,560 per year (in 2005
purchasing power parity, or 6.1 times GDP per capita), against an average of US$ 4,320 for
other African LICs (4.5 times GDP per capita). Although this should facilitate recruitment, it
also imposes a constraint on resources. Tanzania is however close to achieving universal
primary education, and as teacher requirements drop in line with the demographic pressure,
reducing the primary PTR should be more feasible, improving learning conditions, and
ultimately, the quality of service.
Secondary school teachers on the other hand are comparatively underpaid, despite their
shortage. Their low compensation (5.9 times GDP per capita, against 7.5 times in
comparable countries) is partly due to the high proportion of unqualified teachers at this
level. MoEVT developed a multipronged Teacher Development and Management Strategy
in 2008, focusing mainly on supply-side issues. The attractiveness of the profession should
also be reviewed to better retain candidates, inspired by labor market surveys and cross-
country comparisons.
The loose school-level relationship between learning outcomes and school resources points
to weaknesses in pedagogical management. Students from schools that cost the most do
not perform the best, and the least endowed schools do not always achieve the worst
results. These patterns show that beyond the issue of resource allocation, the way resources
are used seems to have a major influence on the level of learning outcomes. Improving
supervision and accountability at the local level is known to be an effective remedy, through
greater information on school inputs and performance, favoring school-based management
and teacher incentives.
Coherence in the Allocation of Primary Teachers among Government Schools, 2007
0 500 1,000 1,500 2,000 2,500 3,000 3,500
80
70
60
50
40
30
20
10
0
y = 0.0178x + 1.5023
R
2
= 0.5947
Number of Pupils
N
u
m
b
e
r
o
f
T
e
a
c
h
e
r
s
Source: SACMEQ, 2007, authors' computations.
Tanzania Education Sector Analysis 36
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11. The strong disparities in the allocation of education inputs further illustrates
management shortcomings.
Significant geographical disparities exist in teacher deployment, with particular allocation
issues in remote rural areas. This is striking at the district-level: primary PTRs range from a
low 28 to 1 in Iringa district, to levels in excess of 80 to 1, such as in the districts of Ukerewe
(129 to 1), Ilala (115 to 1), Chato (95 to 1), Manyoni (91 to 1) and Uyui (89 to 1). In the
Sikonge district, one school reported an extraordinary PTR of 313 to 1 (PEDP II, 2009). The
average urban district-level PTR was 43 to 1, compared with 60 to 1 in rural districts.
Relationship between CSEE Pass Rates and Secondary Level Unit Costs, 2009
- 100 200 300 400 500 600 700 800 900
100
80
60
40
20
0
Unit Costs (Thousands of T Sh)
C
S
E
E
P
a
s
s
R
a
t
e
(
%
)
R
2
= 0.042
Source: Cost of teachers and textbooks from BEST, 2009; Salaries from Table 3.18; CSEE results from NECTA.
Note: Unit costs for the CSEE analysis include teacher salaries and textbook prices.
Tanzania Education Sector Analysis 37
The situation is more critical still as far as qualified teachers are concerned. The pupil to
qualified teacher ratio (PqTR) ranges from above 100 to 1 (Ilala, Bahi, Ulanga, Nanyumbu,
Ukerewe, Manyoni, Urambo and Uyui districts) to under 35 to 1. This situation implies a
very heavy workload for some teachers, potentially negatively affecting their motivation and
willingness to stay in remote areas. This major issue will need to be adequately addressed
through the implementation of an incentive package that could include cash benefits, a
hardship or relocation allowance, fast-track career progression, and/or preferential access
to training and learning materials and improved school environment facilities (including
teachers’ quarters).
Textbooks are generally in short supply in government schools, especially at the secondary
level, and suffer from misallocation. One textbook is shared by three students on average
in primary and between four to nine students at O-Level, according to the subject. Although
many possible explanations exist, the timely transfer and amount of school capitation grants
are definitely related to the lethargic supply. Regional disparities reveal the kind of extremes
Government School Pupil to Teacher Ratios, Primary Level, by Region, 2009
Lake Natron
Arusha
45 Kilimanjaro
37
Tanga
54
Manyara
52
Singida
56
Tabora
68
Shinyanga
73
Mara
62
Lake Victoria
Kagera
61
Kigoma
59
Rukwa
65
Mbeya
55
Lake
Tangyanika
Dodoma
56
Pwani
42
DSM
49
Lindi
55
Mtwara
52
Ruvuma
48
Iringa
45
Morogoro
48
Iringa
45
Lake Natron
Arusha
45 Kilimanjaro
37
Tanga
54
Manyara
52
Singida
56
Tabora
68
Shinyanga
73
Mara
62
Lake Victoria
Kagera
61
Kigoma
59
Rukwa
65
Mbeya
55
Lake
Rukwa
Lake
Tanganyika
Lake
Nyasa
Dodoma
56
Pwani
42
DSM
49
Lindi
55
Mtwara
52
Ruvuma
48
Morogoro
48
Source: BEST, 2009.
Legend: Light grey – PTR under 45:1; Medium grey – PTR between 46:1 and 65:1; Dark grey – PTR above 65:1.
Tanzania Education Sector Analysis 38
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a
r
y
that averages can conceal, showing ratios of more than 3.6 pupils per textbook in Kagera
and Lindi regions, against 1.3 in Tanga region. The coherence of textbook availability across
districts is weak, with R
2
values ranging from 57 percent for math books to 67 percent for
English books.
The allocation of capitation grants is also fraught with inefficiencies. They are mainly due
to amounts allocated often being lower than planned budgets, and to delays in the
reception of funds by schools. The allocation formula is currently based on expected
enrollment; a more equitable formula would take the different needs of schools into
account. Timely fund transfers might be facilitated by the option of sending block grants
for nonwage spending directly to schools. Finally, to ensure that the funds are spent as
planned, a reliable and sustainable accounting system is to be implemented. School
management committees and boards could provide valuable oversight of such functions.
Strengthening their capacity in planning, budgeting, monitoring and evaluation is becoming
critical.
These disparities highlight the need for effective planning and monitoring tools to allocate
education inputs more efficiently. In addition to an EMIS system, financial and human
resource management systems would improve fiscal management and accountability. A first
response to this challenge was given in 2009, with the development of a pilot decentralized
Basic-Education Management Information System (BE-MIS), which was tested in 28 district
councils in 14 regions, and is to be scaled up to all councils nationwide by 2014.
3.6
2.7
1.4
Availability of English Books in Government Primary Schools, by Region, 2009
Pupil - Textbook Ratio
4.0
3.5
3.0
2.5
2.0
1.5
1.0
N
u
m
b
e
r
o
f
P
u
p
i
l
s
p
e
r
B
o
o
k
T
a
n
g
a
K
i
l
i
m
a
n
j
a
r
o
R
u
k
w
a
T
a
b
o
r
a
M
w
a
n
z
a
K
i
g
o
m
a
N
a
t
i
o
n
a
l
S
i
n
g
i
d
a
S
h
i
n
y
a
n
g
a
M
a
n
y
a
r
a
I
r
i
n
g
a
D
o
d
o
m
a
D
a
r
e
s
S
a
l
a
a
m
R
u
v
u
m
a
M
t
w
a
r
a
A
r
u
s
h
a
M
b
e
y
a
M
o
r
o
g
o
r
o
P
w
a
n
i
M
a
r
a
K
a
g
e
r
a
L
i
n
d
i
2.7
3.6
1.4
Source: BEST, 2009.
Tanzania Education Sector Analysis 39
12. Higher education is in a favorable position to adequately manage the
development and diversification of the subsector’s supply.
The government has deployed a series of strategies to ensure the adequate and more
concerted development of both higher education and the TVET subsectors, to supply the
economy with the increasing number of skilled and knowledgeable professionals it needs
to sustain its growth. A solid and modern institutional framework has been established for
higher education’s development: the sector was integrated into MoEVT in 2008 to promote
more integration across education subsectors, and the Tanzania Commission for Universities
has been strengthened to comply with quality assurance requirements. Various mechanisms
have been implemented or are under consideration to improve equity and access, including:
(i) a streamlined admissions procedure and centralized admissions system; (ii) an extended
national qualifications framework, building bridges between vocational and university
education; (iii) cost-sharing policies; and (iv) student loans, provided to 81 percent of all
higher education students via the HESLB.
Many HLIs are still not running at full capacity, allowing for the expansion of the system at
limited cost. In the sample of HLIs used in this report, the total intake capacity was 50,508,
of which only 37,142 places were effectively occupied, or 74 percent. Nevertheless, if the
current enrollment trend continues, the need for greater capacity will require imminent
attention, considering subject specializations.
University teaching conditions are favorable. Although staff are predominantly male, female
teachers accounting for just a fifth of HLI teachers in 2009/10: (i) half are aged 40 years
and under, and 30 percent are aged over 50 years; (ii) 25 percent of the teaching staff were
highly ranked (professor, associate professor or senior lecturer); (iii) almost all lecturers had
the required level of qualifications; (iv) 87 percent of teachers were full-time; (v) higher
education teaching salaries were very attractive; and (vi) student to teacher ratios averaged
15 to 1.
However, the high level of administrative staff in higher learning institutions is an issue. The
ratio of administrative staff to teaching staff in the sample used was 1 to 1 on average, in
some cases reaching 2.4 to 1, underlining the scope for efficiency gains.
In theory, the country is today adequately equipped to cater for the expected growth in the
intake of students. However, to ensure the smooth and coherent development of the sector,
attention must be paid to course requirements, and to the likely timescale in which the
subsector is going to expand. The existing state institutions and parastatal agencies should
be able to orient this policy both from its supply and its demand side.
Tanzania Education Sector Analysis 40
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13. The TVET system is also endowed with an improved and solid institutional
framework, including regulatory and quality assurance bodies.
TVET coordination is being improved through a new institutional set-up, incorporating
vocational education and training and technical education under MoEVT. The sometimes
incoherent development of trainings by individual institutions is being addressed through
the development of a TVET development programme. Yet, technical and vocational
education are still separately managed.
Quality assurance processes have been greatly improved under both NACTE and VETA, through:
• Registration and accreditation standards and procedures. At the end of 2009, 96 percent
of the 221 physically recorded technical education institutions were fully or provisionally
registered, up from 41 percent in 2002. Thirty nine percent were given accreditation;
• Education qualification frameworks, including the National Technical Awards;
• An outcome-based training approach;
• The registration of all technical education teachers. In June 2009, 1,574 out of 2,970
had full or provisional registration (53 percent); and
• VETA’s rigorous registration and accreditation guidelines. In 2008, 78 percent of VTC
centers were registered (50 percent provisionally, and 28 percent fully), and
underperforming or unoperational centers’ registration was revoked.
An effective monitoring and evaluation mechanism to make the technical and vocational
education more responsive to labor market demands has been put in place. Under VETA,
zonal labor market analysts regularly collect data that is then compiled at the national level,
and complemented with mini market surveys to track current and prospective industry
needs. FDC training programmes are also demand-driven; curricula are developed after
conducting community training needs assessments. However, labor market surveys are still
limited by technical education institutions’ capacities and resources, creating a mismatch
between the development of needed skills and current institutional service delivery.
Source: NACTE.
Note: Includes Zanzibar. Out of a total number of 221 HLIs.
Preparatory / Candidacy
Provisional
Full
Total (Full + Provisional)
% (Out of 221 HLIs)
Registration and Accreditation Status of Technical HLIs, 2009
8
35
178
213
96%
33
36
50
86
39%
Registered Accredited
Number
Stage of
Tanzania Education Sector Analysis 41
14. TVET nevertheless faces a series of challenges.
Technical and vocational education institutions are facing increasing pressure to support
new socioeconomic developments and ensure that a growing number of basic and
secondary school leavers are provided with adequate skills to enable them to develop their
full potential in the workplace. Although regulatory and quality assurance bodies provide
important guarantees for the controlled development of the TVET subsector, it faces a series
of challenges:
(i) The diversity of training demand linked to the heterogeneity of the target population
(school leavers, technicians wanting to upgrade or change jobs, low skilled/educated
people from urban and rural areas);
(ii) The variety of TVET programs and providers (ministries, parastatal agencies, faith-
based organizations, NGOs, private institutions, vocational training centers, Folk
Development Colleges, and so on);
(iii) The institutional fragmentation of the TVET system, involving two ministries and three
different parastatal agencies;
(iv) The practical continuity between VET and TE curricula/programmes, although
theoretical bridges do exist between both sectors, as defined in the national
qualifications’ framework;
(v) The lack of practical mechanisms for vertical academic promotion within VET. The
competency-based qualifications framework should facilitate the transition between
levels. In 2008 however, only 13 percent of the 889 VTCs offered the CBET.
To date, the training of tutors has not been given enough attention and support. The
training of vocational training centre staff is still a major challenge. The shortage of quality
teaching staff and FDC tutors is acute. Trainers’ competencies are focused on methodology,
and their practical industrial competencies need reinforcing and updating. Preservice and
in-service training opportunities will need to be adequately set up to improve teaching
quality.
The TVET system seems to have adequate monitoring tools (such as labor market surveys
and tracer surveys) to adequately develop and update curricula according to changing
market demand and forthcoming economic needs. However, a dynamic connection
between TVET training institutions and industry is desirable to sustain and facilitate the
smooth and coherent development of relevant workforce skills.
Tanzania Education Sector Analysis 42
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Adequately diversifying the sources and level of funding will prove key to enable the TVET
subsector and its institutions to meet their goals. Technical institutions particularly lack
modern training equipment and sufficient and relevant learning materials. Cost-sharing
mechanisms and granting trainees access to higher education loans should be considered.
VET resources are also insufficient to adequately cater for institutions’ operational needs.
To complement trainee fees, government grants, the proceeds from fund-raising activities
and the development and skills levy, the subsector could seek funds from the private sector
or communities, and implement short-term cost-efficiency measures.
15. The way forward should involve more balanced and efficient sector policies.
Important progress has been registered as much on the institutional front (through
coordination and piloting mechanisms) as on the school coverage one. This has been greatly
helped by the additional resources devoted to education over the decade. The possibility that
this trend not be sustained due to competing sectors’ needs calls for more effective education
policies and the removal of major inefficiencies. In this context, the Education Sector Analysis
(ESA) has helped to identify the following options that are available to policy makers:
• Increase the public resources allocated to secondary education, especially for capitation
grants and more teachers;
• Improve higher education funding mechanisms, by better targeting loan beneficiaries
and better taking advantage of potential economies of scale;
• Ensure children enter primary school at the right age;
• Improve secondary access and retention;
• Support pro-poor schooling, starting at primary level;
• Take affirmative action to enhance girls’ participation in school and ensure gender
parity at postprimary levels;
• Improve pedagogical management to raise the quality of basic education;
• Reduce disparities in the allocation of education inputs between regions, districts and
schools;
• Strengthen the development of literacy programmes targeted at parents, women and
active adults;
Tanzania Education Sector Analysis 43
• Revise TVET budget trade-offs and strengthen TVET coordination mechanisms to
better respond to the strong and heterogeneous demand;
• Define a funding formula to rationalize the allocation of resources among technical
institutions;
• Adequately plan the expansion of TVET and higher education. University students’
career objectives and the distribution of graduates by subject area must be adjusted
on the basis of the results of relevant tracer surveys;
• Strengthen the EMIS to further improve the coverage and quality of education data at
school and district levels;
• Scale-up the BE-MIS, including decentralized financial and human resource databases
to improve fiscal management and accountability systems.
This education sector analysis (ESA) for mainland Tanzania is a detailed analytical
document that offers a comprehensive picture of mainland Tanzania’s education
sector. This ESA is part of an on-going series of education country-specific reports
being prepared by government teams, technically supported by UNESCO, the World
Bank and other development partners. The main purpose of an ESA (also known as
a Country Status Report, or CSR) is to provide an evidence-based diagnosis of an
education sector to enable decision-makers to orient national policies. It also
provides relevant analytical information to nourish the dialogue between the
government and education sector stakeholders, including development partners.
In the current development context, marked by the necessity for countries to
develop sound, sustainable and credible strategies and plans in which education is
embedded, ESAs represent a valuable and essential tool.
This is the second ESA for Tanzania; the first one having been conducted in 2001.
Although its main objective is to provide a comprehensive picture of the education
system in 2009 (the last year for which statistics were available), it also provides
some analysis of the evolution of the system over the decade, when feasible and
relevant. This second report is also more than an update. It provides more in-depth
analysis on certain aspects of the system: detailed unit costs by subsector, external
efficiency, quality and out-of-school, and technical education and vocational
training and higher education in particular. It provides key monitoring and
evaluation inputs on the education sector as a whole, that are particularly
valuable in the framework of the implementation of the Education Sector
Development Programme.
Regional Bureau
for Education in Africa
doc_312165113.pdf