Download Higher Education and Economic Development in Africa: HERANA I

Makerere University
CHET
August 2012
2
• To use a set of analytical concepts to try and better understand the
complex interactions between national economic/education policies and
higher education system development
• To learn from some OECD countries who had been successful in linking
HE and economic growth
• To use 8 African countries as contexts for the study
• To develop an empirical methodology to operationalise the concepts
• Do not assert that the primary/only role for higher education is
development
3
HERANA
Higher Education Research & Advocacy Network in Africa
RESEARCH
Higher Education and Development
Investigating the complex relationships between
higher education and economic development, and
student democratic attitudes in Africa
The Research-Policy Nexus
Investigating the relationship between
research evidence and policy-making in
selected public policy sectors in South
Africa
ADVOCACY
The HERANA Gateway
An internet portal to research on higher
education in Africa
University World News (Africa)
Current news and in-depth investigations
into higher education in Africa
Nordic Masters in Africa (NOMA)
Collaborative research training by the
Universities of Oslo, Makerere, Western
Cape, and CHET
FUNDERS
Carnegie, Ford, Rockefeller, Kresge, DFID, Norad
HERANA 2: Carnegie, Ford, NORAD
4
• Three successful (OECD) systems investigated:
◦ Finland (Europe), South Korea (Asia), North Carolina (US)
• Africa
◦ Botswana – University of Botswana
◦ Ghana – University of Ghana
◦ Kenya – University of Nairobi
◦ Mauritius – University of Mauritius
◦ Mozambique – Eduardo Mondlane
◦ South Africa – Nelson Mandela Metropolitan University
◦ Tanzania – University of Dar es Salaam
◦ Uganda – Makerere University
5
Higher education studies – Peter Maassen and Nico Cloete
Development economist – Pundy Pillay (UWC)
Sociology of knowledge – Jo Muller (UCT), Johann Mouton (US)
Data analysis - Ian Bunting (DoE), Charles Sheppard (NMMU)
Researchers – Tracy Bailey (CHET), Gerald Ouma (Kenya & UWC), Romulo
Pinheiro (Oslo), Patricio Langa (Mozambique & UCT), Samuel Fongwa
(Cameroon, UWC)
External commentators
• Manuel Castells (USC, Open University, Barcelona)
• John Douglas (CHES, Berkeley)
Makerere contributors
• Prof. Vincent Ssembatya (Director, Quality Assurance)
• Dr Florence Nakaywa (Director, Planning)
• Prof. Baryamureeba (Acting VC)
6
A substantial body of academic and technical literature provides evidence of the
relationship between informationalism, productivity and competitiveness for
countries, regions and business firms. But, this relationship only operates under three
conditions: information connectedness, organizational change in the form of
networking; and enhancement of the quality of human labour, itself dependent on
education and quality of life. (Castells and Cloete, 2011)
The structural basis for the growing inequality, in spite of high GDP growth rates in
many parts of the world, is the growth of a highly dynamic, knowledge-producing,
technologically advanced sector that is connected to other similar sectors in a global
network, but it excludes a significant segment of the economy and of the society in
its own country. The lack of human development prevents what Manuel Castells calls
the ‘virtuous cycle’, which constrains the dynamic economy. (Castells and Cloete,
2011)
Connecting growth to human development – trickle down doesn’t work.
Key connectors are education (Higher Education) and ICT.
7
GDP per capita
(PPP, $US) 2007
GDP ranking
HDI Ranking
(2007)
GDP ranking per
capita minus HDI
ranking
Botswana
13 604
60
125
-65
Mauritius
11 296
68
81
-13
9 757
78
129
-51
Chile
13 880
59
44
+15
Costa Rica
10 842
73
54
+19
Ghana
1 334
153
152
1
Kenya
1 542
149
147
2
802
169
172
-3
Uganda
1 059
163
157
6
Tanzania
1 208
157
151
6
Finland
34 256
23
12
11
South Korea
24 801
35
26
9
USA
45 592
9
13
-4
Country
South Africa
Taiwan (China)
Mozambique
GDP per capita (current US$)
Predicted GDP per capita (current US$)
United States
Economic development
Australia
Japan
UK
High
Germany
Italy
Korea
Mexico
Brazil
Low
Argentina
South Africa
Tunisia
China
Egypt
India
Low
(R = 0.714, P = 0.218)
(R = 0.961, P = 0.002)*
High
Influence of Scientific Research
Data source: Thomson Reuters InCitesTM (21 September 2010); The World Bank Group (2010)
9
Gross tertiary
education
enrolment rate
(2008)
Quality of
education system
ranking
(2009-2010)
Overall global
competitive
ranking
(2010-2011)
Ghana
6
71
114
Kenya
4
32
106
2
81
131
Tanzania
2
99
113
Uganda
5
72
118
20
48
76
26
50
55
18
130
54
94
6
7
98
57
22
82
26
4
Country
Mozambique
Botswana
Mauritius
South Africa
Finland
South Korea
United States
Stage of
development
(2009-2010)
Stage 1:
Factor-driven
Transition from
1 to 2
Stage 2:
Efficiency-driven
Stage 3:
Innovation-driven
Finland, South Korea, North Carolina (USA)
• As part of reorganising their ‘mode of production’, they developed a
(pact) around a knowledge economy model (high skills training,
research and innovation)
• Close links between economic and education planning
• High participation rates with differentiation
• Strong ‘state’ steering (different methods)
• Higher education linked to regional development
• Responsive to the labour market
• Strong coordination and networks
Pundy Pillay (2010): Linking higher education to economic development:
Implications for Africa from three successful systems. (CHET)
11
Higher education’s role in / contribution to development is influenced by
three inter-related factors:
• The nature of the pact between the university leadership, political
authorities, and society at large
• The nature, size and continuity of the academic core
• The connectedness and coordination of national and institutional
knowledge policies to the academic core and to development
projects is crucial
12
13
A ‘pact’ is defined as a fairly long-term cultural, socio-economic and
political understanding and commitment between universities, university
leadership, political authorities and society at large of the identity or vision
of universities, what is expected of universities, and what the rules and
values of the universities are.
Pacts are not only between society and higher education, but also important
within the institution.
14
Government
Government departments: Education; Science and Technology;
Treasury; Industrial Development; Research Councils
Notions and policies
Coordination mechanisms
External
Groupings
Students
Business
Community
Funders
Business
Pact
Academic Core
Connectedness
University
Leadership/
planning
Faculties
Academics
15
1. Narrative, intent and structures for the Role of HE in development
2. Visions and plans, i.e. Development Visions (2025-2035)
3. Policies – development, science and technology, higher education
4. Methods and structures for co-ordination
16
Role for knowledge and universities in development
National rating = 4/6
Concept of a knowledge
economy features in the
national development
plan
3 Strong
2 Weak
Appears in a number of Only mentioned
policies
in one policy
A role for higher
3 Prevalent
education in development Clearly mentioned in
in national policies and
development policies
plans
2 Weak
1 Absent
Not mentioned
at all
1 Absent
University of Makerere rating = 5/6
Concept of a knowledge
economy features in
university policies and
plans
3 Strong
Features strongly in
strategic plan and/or
research
policy/strategy
A role for higher
3
education in development Institutional policy
in national policies and
plans
2 Weak
1 Absent
Vague reference Not mentioned
in strategic plan
at all
or research policy
2
Embedded in
strategic plan,
research policy
1 Absent
No formal
policies
Knowledge
Connectedness
University not part of
national development
model/strategy
University part of
national development
model/strategy
No or marginal role
for new knowledge
in development model
Acillary
Instrument
Central role
for new knowledge in
development model
Self-governance
Engine
18
Max. score
Botswana
Ghana
Kenya
Mauritius
Moz.
South
Africa
Tanzania
Uganda
NATIONAL LEVEL
9
3
3
6
7
4
6
4
3
Economic
development and
higher education
planning are linked
3
1
1
2
3
1
2
1
1
Coordination and
consensus building
of government
agencies involved in
higher education
3
1
1
2
2
1
2
1
1
Link between
universities and
national authorities
3
1
1
2
2
2
2
2
1
INDICATORS
19
1. At national level the importance of knowledge economy and the
importance of higher education were rather weakly reflected in national
policy statements
2. The Poverty Eradication Plan recognises the need for higher economic
growth (currently around 6%) and human capital development and
Science and Technology. Important to shift from higher education for
social mobility and training the professions, to higher education as
‘engine” for development.
3. In contrast, at institutional level a much stronger reference to knowledge
economy and the importance of the university in development in the
strategic plan.
4. Regarding notions of the role of the university, at national level strong
Instrumental expectation, while institutional level increasing support for
engine of development (innovation) - faculty differences
5. Not strong enough incentives to translate ‘increasing support’ into
action
20
6. There did not seem to be a strong agreement between national and
institutional levels that higher education is key to development – different
discourses
7. Development aid agencies needs to become part of the Pact - while in
their own countries there is a ‘engine of development’ notion, in Africa
the universities are often regarded as ‘development agencies’, meaning a
narrow ‘instrumental’ role
8. Poor policy coordination – the problem of Capacity and Agreement
9. In both the development of a Pact and Coordination, the National Council
on Higher Education could play and important role to connect
stakeholders - needs to be capacitated to do this in addition to other
tasks
10. The importance of Institutional leadership stability – between institution
and society and within the institution
11. The road pact!!
21
22
• Burton Clarke refers to the ‘academic heartland’ and a ‘stronger
steering core’
• The universities in the HERANA sample are public and ‘flagship’
universities which claim in mission statements that they:
◦ have high academic ratings,
◦ are centres of academic excellence engaged in high quality
research and teaching
◦ and contribute to development
• They are the key “knowledge institutions” in these countries
• Assumption: For a university to contribute to development it needs
a strong academic core – universities are ‘weak ‘ development agencies,
23
1. Increased enrolments in science, engineering and technology (SET)
– AU regards SET as a development driver (importance and
weakness of social sciences, humnaities and education)
2. Increased postgraduate (PG) enrolments – knowledge economy
requires increasing numbers of workers with PG qualifications
3. Favourable academic staff to student ratio – workload should
allow for research and PhD supervision
4. High proportion of academic staff with PhDs – high correlation
(0.82 in South Africa) between doctorates and research output
5. Adequate research funding per academic – and from multiple
sources
24
1. High graduation rates in SET fields – not only must enrolments
increase, but also graduate output
2. Increased knowledge production (doctoral graduates) – for
reproduction of academic core, to produce academics for other
universities and for demand in other fields
3. Increased knowledge production – research publications in ISI
peer-reviewed journals (problem of counting ‘publication’s which
is not the only knowledge output
25
Science & technology
Business & management
Humanities and social sciences
Target = 40% enrolments in science & technology
100%
33%
80%
51%
37%
50%
52%
65%
60%
26%
40%
22%
10%
27%
27%
20%
41%
41%
19%
40%
22%
21%
Botswana
Botswana
Cape Town
Cape Town
Makerere
Makerere
2001/2
2009/102
2001/2
2009/10
2001/2
2009/10
16%
0%
26
Qualification levels of permanent academic staff members
UDSM, Highest qualification level of permanent
Makerere, Highest qualification level of
academic staff members (2007)
permanent academic staff members (2007)
17%
25%
31%
Doctorate
50%
Doctorate
Masters
Masters
Other
Other
25%
52%
Ghana, Highest qualification level of permanent
UCT, Highest qualification level of permanent
academic staff members (2007)
academic staff members (2007)
11%
12%
47%
Doctorate
Masters
42%
Other
Doctorate
30%
Masters
58%
Other
Research funding
Research funding resources (in US$) available in 2007 to the
academic staff members of each university.
Research income in 2007 per permanent academic staff member
35
29.7
30
25
20
15
10
5
0
US$ thousands
3.3
3.1
UDSM
Makerere
Ghana
UCT
3.3
3.1
1.4
29.7
1.4
2001/2
1200
2003/4
1000
970
2005/6
2007/8
1002
783
800
706
600
400
200
0
10
16
32
Botswana
51
31
Cape Town
41
54
Makerere
32
92
102 110
120
Ghana
29
2001/2
200
2003/4
2005/6
182
180
160
2007/8
2009/10
178
142
140
120
103
100
86
80
55
60
40
20
30
4
6
6
3
12
6
16
20
18
8
9
11
17
0
Botswana
Cape Town
Makerere
Ghana
30
2001/2
1200
2003/4
2005/6
2007/8
1014
1000
893
800
700
564
600
400
233
200
78
72
85
120
73
107 118
66
71
68
101
0
Botswana
Cape Town
Makerere
Ghana
31
400
350
Doctoral graduates
338
Research publications
300
233
250
230
200
131
150
100
50
107
72
73
11
12
2000/1
2001/2
139
118
76
21
16
2002/3
2003/4
25
18
23
30
2004/5
2005/6
2006/7
2007/8
38
55
0
2008/9
2009/10
32
1.20
1.10
1.14
1.00
Doctoral graduates
Research publications
0.90
0.80
0.70
0.60
0.50
0.40
0.30
0.20
0.10
0.00
0.01
0.12
Botswana
0.15
Cape Town
0.02
0.11
Makerere
0.02
0.09
Ghana
33
•Graph 1 offers summaries for the 15-year period 1996-2010.
Doctoral enrolments were 1.3% of national total of 893 000 students in 2010.
1 8000
1 6000
1 4000
1 3449
1 4184
14673
1 5423
1 5809
1 5936
1 3098
1 2000
1 0000
4 000
2000
9800
9 939
8003
8 353
1100
1 182
8 790
7763
8 000
6 000
5 164
5622
6 85
1 6684 Permanent
academics
5 528
5456
7 61
6 394
5 936
9 61
6483
6 660
9 69
1 104
11468 Doctoral
enrolments
9748
Research
publications
1 421
0
1996
1998
Doctoral enrolments
2000
2002
Doctoral graduates
2004
2006
R esearch publications
2 008
Doctoral
graduates
2010
Permanent academics
34
Graph 4 shows how the % of doctoral enrolments by race group changed
between 1996 to 2010. African doctoral students rose from 13% in 1996 to
33% in 2004, and 44% in 2010.
9 0%
8 0%
78%
7 0%
62%
55%
6 0%
49%
5 0%
41%
4 0%
33%
13%
13%
12%
10%
2004
2 008
1 0%
0%
42%
African
White
25%
3 0%
2 0%
44%
14%
Coloured+Indian
9%
1996
2 000
African
White
Coloured +Indian
2010
35
Enrolments
South African Universities – PhD graduates by
nationality
South African
International
100%
80%
29%
30%
34%
34%
71%
70%
66%
66%
60%
40%
South African International
2007
7 195
2 853
2008
6 959
3 035
2009
7 213
3 316
2010
7 841
3 749
Graduates South African International
2007
900
374
2008
829
353
2009
908
470
2010
931
489
South African PhD students graduation rate by
20%
15%
nationality
South African
International
14%
2007
2008
2009
2010
Norwegian Universities - PhD graduates by nationality
Norwegian
International
Graduation Rate
0%
13%
13%
23%
25%
26%
28%
33%
77%
75%
74%
72%
67%
2007
2008
2009
2010
2011
20%
0%
12%
13%
13%
12%
11%
2007
60%
40%
13%
12%
100%
80%
Total
10 048
9 994
10 529
11 590
Total
1 274
1 182
1 378
1 420
2008
2009
2010
It is important to note that the two countries
produce almost the same number of PhD
graduates but that South Africa’s population is in
the order of 48 million whilst Norway’s population
is 4.8 million
Graduates
2007
2008
2009
2010
2011
Norwegian
789
937
851
858
889
International
241
308
297
326
438
Total
1030
1245
1148
1184
1327
General:
• None of the universities (except Cape Town) seem to have moved from
their traditional undergraduate teaching role
• Considerable diversity amongst input indicators, with postgraduate
enrolments and inadequate research funds the weakest
• The strongest input indicators are manageable student-staff ratios
(Except Ghana) and staff with doctorates (comparable to SA)
• On the output side, SET graduation rates are positive, but all institutions
(except Cape Town) have low knowledge production
• From the weak knowledge production output indicators it seems the
academic cores are not strong enough to make a sustainable contribution
to development
37
• Makerere on the UP – dramatic increase in SET, doctorates and
particularly ISI publications, but knowledge production from a very low
base
• Major concern to increase the enrolment and graduation rate of
doctorates (balance staff and young graduates, funding, post docs and
“productive” departments
•
• Incentive structure (double and triple teaching, consultancies and
bureaucracy in institutional and national research funds) do not
encourage knowledge production
• Working on improving data definition, systematic institution-wide
capturing and processing, and strengthen evidence-based strategic
planning and leadership
38
• A focus should be to strengthen the academic cores of the ‘flagship’
universities
• Key areas to improve are:
◦ masters throughput to PhDs
◦ doctoral enrolments and graduation, with scholarships and post docs
◦ research funding and the incentives around research funding
• Examine incentives and address perverse incentives
• Consider an Africa Research Fund with some of the features of the
European Research Fund
• Funders and governments must build conditions into consultancies
that strengthen rather than weaken the academic core
39
> There is a clearly identified need to improve and
strengthen the definition of performance indicators,
as well as the systematic, institution wide capturing
and processing (institutionalisation) of key indicators
> Capacity needs to be built about the analysis of data
at both planning, management and leadership levels,
and linking these analyses to planned reforms – at
institutional and national levels
> Revitalising African higher education is amongst
other things going to require more comparative,
evidence based approaches than declarative missions
and intentions
> Important role of National Commissions
> Role of Incentives in Knowledge Production
40
Books and reports
1.
Linking Higher Education and Economic Development: Implications for Africa
from three successful systems (Pillay)
2. Universities and Economic Development in Africa: Pact, academic core and
coordination (Cloete, Bailey, Maassen)
3. Universities and Economic Development in Africa: Key findings
(Cloete, Bailey, Bunting & Maassen)
4. Country and University Case Studies: Botswana (Bailey, Cloete, Pillay)
5. Country and University Case Studies: Ghana (Bailey, Cloete, Pillay)
6. Country and University Case Studies: Kenya (Bailey, Cloete, Pillay)
7. Country and University Case Studies: Mauritius (Bailey, Cloete, Pillay)
8. Country and University Case Studies: Mozambique (Bailey, Cloete, Pillay)
9. Country and University Case Studies: South Africa (Bailey, Cloete, Pillay)
10. Country and University Case Studies: Tanzania (Bailey, Cloete, Pillay)
11. Country and University Case Studies: Uganda (Bailey, Cloete, Pillay)
> There is a clearly identified need to improve and strengthen the
definition of performance indicators, as well as the systematic,
institution wide capturing and processing (institutionalisation) of
key indicators
> Capacity needs to be built about the analysis of data at both
planning, management and leadership levels, and linking these
analyses to planned reforms – at institutional and national levels
> Revitalising African higher education is amongst other things
going to require more comparative, evidence based approaches
than declarative missions and intentions
> Important role of National Commissions
> Impact of engagement activities on the academic core
> Role of Incentives in Knowledge Production
42