HIGHER EDUCATION OVERVIEW
NORTH WEST UNIVERSITY
MARCH 2012
Economic Growth and Human Development
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 two conditions: organizational change in
the form of networking; and enhancement of the quality of human labor,
itself dependent on education and quality of life. (Castells and Cloete, 2011)
The structural basis for the growing inequality, in spite of high growth rates in
many parts of the world, is the growth of a highly dynamic, knowledgeproducing, 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 don’t work
2
Gross Domestic Product (GDP) per capita vs Human Development Index (HDI)
Country
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
South Africa
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
U.S.A.
45 592
9
13
-4
Taiwan (China)
Mozambique
3
Economic Growth in Post Apartheid SA
During the first decade of the post-apartheid era in South Africa, gross
domestic product (GDP) grew at a ‘modest rate’, averaging one percent, though
edging up more recently to three percent. Nevertheless, this has been the
longest period of positive growth in its history How did this growth happen?
The envisaged post-1994 economic policies for the development project stated
that the economy would require steering onto a new development path which,
amongst others, would reduce dependence on resource sectors through
industrial deepening and diversification (Bhorat 2010).
4
Economic Growth and the 2008 Financial Crisis
The worst impact of the 2008crisis, resulted in at least a million job losses, and is
associated with:
• structural industrial weaknesses and de-industrialization as a result of
development centred around mining and minerals
• continued reliance on extractive mining and minerals exports
• consumption led growth and increased investment in services sectors, such as
finance and retail
• speculative asset bubbles in real estate and finance and increased construction
(mainly around the 2010 Soccer World Cup) and car sales
• the role of the financial sector which has emulated the behaviour of US
financial institutions in increasing leverage and misallocation of capital in SA
economy. (Mohamed 2009)
5
Poverty Reduction in Post Apartheid SA
The stated goal of the post-apartheid economic policy was to reduce poverty,
inequality and unemployment. A 2% growth should lead to a 1-7% reduction in
poverty, depending on the country – meaning the success of redistributive
policies (Bhorat 2010a). In South Africa, poverty declined from 52% in 1995 to
49% in 2005 and in the lower poverty group a 7% decline (31% to 24%). In
addition, there were definite gains in poverty reduction, particularly in African
female-headed households (Bhorat 2010a). All people, regardless of race,
experienced increases in expenditure, meaning that growth was ‘pro-poor’.
Despite the modest gains in poverty reduction, the inequality gap did not
decrease; instead, it increased amongst all groups. This led Bhorat (2010a) to
conclude that in 1994 South Africa was ‘one of the world’s most unequal
societies, but by 2005 it may have become the world’s most unequal’.
6
Poverty Reduction in Post Apartheid SA
While spending on education and health remained fairly constant in real terms,
recipients of social grants (excluding administration) now consumes 3.2% of
GDP, up from 1.9% in 2000/01. The total number of beneficiaries increased
from 3 million in 1997 to 15 million in 2010 (Woolard and Leibrandt 2011). The
share of households in the first income decile with access to grant income
increased from 43% in 1995 to almost 65% in 2005 and that even for
households in the sixth decile grant income increased from 19% in 1994 to 50%
in 2005. According to Bhorat (2010a) this suggests that grant income does not
only support the very poor, but also a large number of households in the
middle income distribution.
More recent estimates suggest that 25% of the population are on social grants and
40 per cent of household income in the poorest quintile (Woolard and
Leibbrandt 2011).
Post-1994 South African democratic redistribution model operates through
extensive social grants at the bottom end, few benefits at the middle of the
distribution curve and the main growth is at the de-racialising top end. Based
on this growth path, both Bhorat (unequal income distribution) and Mbeki (the
disempowerment of welfarism) express concern for the future of democracy.
7
Higher Education and Development
• SA has a development crisis
• Connecting Growth to Human Development
• Castells project of Finland, Chile, Taiwan, Costa Rica, SA and
California
• Two aspects of Higher Education that I want to concentrate on
are Knowledge production (growth) and participation (skills and
equity)
8
The relationship between scientific
excellence and economic development
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
High
Influence of Scientific Research
(R = 0.714, P = 0.218)
(R = 0.961, P = 0.002)*
Data source: Thomson Reuters InCitesTM (21 September 2010); The World Bank Group (2010)
9
Vuyani Lingela, 24 November 2011
Knowledge Production: SA International Performance
According to the NPC:
1. SA produces 28 PhD graduates per million of the population
while UK =288; US = 201; Australia=264; Korea=187; Brazil = 48
2. World Bank: SA has tripled R&D investment since 1994, but the
total number of FTE researchers increased by only 33%. SA has
approximately 1.5 FTE researchers per 1000 employed;
countries with similar ratio of R&D to GDP expenditure like
Portugal = 4.8 and Italy = 3.6
3. NPC goals: Increase PhD graduates from 1420 to 5000 p.a and
increase percentage of staff with PhD’s from 34% to 75%
10
Participation Rate and Development Indicators
Gross tertiary
education
enrolment rate
Quality of
education
system ranking
Overall global
competitive
ranking
(2008)
(2009-2010)
(2010-2011)
Ghana
6
71
114
Kenya
4
32
106
2
81
131
Tanzania
2
99
113
Uganda
4
72
118
20
48
76
26
50
55
17 (8.5)
130
54
94
6
7
98
57
22
82
26
4
Country
Stage of
development
(2009-2010)
Mozambique
Botswana
Mauritius
South Africa
Stage 1:
Factor-driven
Transition from
1 to 2
Stage 2:
Efficiency-driven
Finland
South Korea
United States
Stage 3:
Innovation-driven
11
BRICS: Selected higher education and economic development indicators (WEF 2010)
Country
Stage of
development
(2009-2010)
GDP per capita
(USD)
(2009)
Tertiary
education
enrolment rate
(2008)
Global
Competitiveness
Index ranking
(2010–2011)
Brazil
Stage 2:
Efficiency-driven
8 220
35
58
Russia
Stage 2:
Efficiency-driven
8 694
77
63
India
Stage 1:
Factor-driven
1 031
14 (2007)
51
China
Stage 2:
Efficiency-driven
3 678
23
27
South Africa
Stage 2:
Efficiency-driven
5 824
17
54
12
Gross participation rates in SA higher education by Race, 1986 - 2009
70%
60%
% Participation Rate
50%
40%
30%
20%
10%
0%
1986
1995
2000
2005
2009
African
5%
9%
10%
12%
13%
Coloured
9%
10%
9%
13%
15%
Indian
32%
35%
40%
51%
45%
White
61%
61%
57%
60%
58%
Average
11%
14%
14%
16%
17%
13
Effective Participation: Throughput rates of general academic first-B-degrees
Graduated in regular time (3 years) - general academic first Bdegrees, excluding Unisa
Black
White
52%
All
43%
43%
35%
33%
29%
24%
28%
24%
21%
11%
11%
13%
14%
Source: Fisher and Scott, 2011
13%
Knowledge Economy
Central role of knowledge in government policies
Focus in Knowledge Policies on:
1. Global economic competitiveness
2. Innovative capacity of societies
3. High Level Skills and Competencies of Labour
force (Knowledge workers)
Core issue: Most effective investment of public
funds
Claus Swabe (WEF) Not Capitalis, but Talentism
International Knowledge Policies – Maassen
Starting point = New conditions in the global economy
Growing focus of national (regional – supranational) policy makers
and other central socio-economic actors on the university as a
driver for economic growth through its role as source for innovation
and job creation.
Consequence = Two new university governance aspects
First targeted policies for and investments in universities’ research
capacity are assumed to be needed in order to improve the global
competitiveness of a specific economy.
Second, targeted policies for and investments in connecting the
enhanced research capacity of universities to the knowledge needs
of society (incl. private and public sector companies and
organisations) in order to ensure the link of new knowledge to
economic growth (innovation & new jobs ).
«Balancing academic excellence with economic relevance»
HERANA: 8 African Countries and Flagship Universities
Higher Education Research and Advocacy Network in Africa
• Starting point is to increase understanding of the complex links/interactions
between higher education and economic development – at national and
institutional levels
• Three successful systems – Finland, South Korea and North Carolina (USA)
• Eight African countries and their national universities: Botswana, Ghana,
Kenya, Mauritius, Mozambique, South Africa (Nelson Mandela Metropolitan
University/UCT), Tanzania, Uganda
• Network consists of 50 people from 15 countries, include Manuel Castells,
Peter Maassen (Oslo) John Douglas (Berkeley) and Pundy Pillay (Wits)
Funded by: Ford, Carnegie, Rockefeller, Kresge and Norad
Findings from Three Successful Systems
Finland, South Korea, North Carolina (USA)
• As part of reorganising their ‘mode of production’, a pact was reached about a
knowledge economy (high skills and innovation) as development driver
• Close links between economic and education planning
• High participation rates with differentiation
• Strong ‘state’ steering (projects)
• Higher education linked to regional development
• Responsive to the labour market
• Strong coordination (prime ministers office) and networks
Pundy Pillay (2010) Linking higher education to economic development:
Implications for Africa from three successful systems (CHET)
HERANA Findings on 8 African Countries and Flagship Universities
1. There is a lack of agreement (pact) between national and university
stakeholders about a development model, and about the role of higher
education in development
2. Only one of the eight countries (Mauritius) has accepted knowledge, and the
associated human capital and research development, as a key driver for
economic growth
3. Linking higher education to development requires considerable coordination
within government, and between government, the university and external
funders, and all three must contribute
4. The absence of a pact about the role of the university in development affects
negatively implementation and resource allocation – which raises the
possibility that we a have double problem; lack of capacity and a lack of
agreement
19
Dis-coordinated Knowledge Policies
1. Department of Higher Education and Training
a) Shocked by Chet’s finding of 3 million NEET’s and have
become ‘overwhelmed’ with FET and training
b) In Ministers budget speech referred to research on page 12
of 13 and never used knowledge economy and Africa, not to
mention the globe (a local communist)
2. Department of Science and Technology
b) Opening line knowledge economy and global competitive
c) Presses all the knowledge production buttons
d) Never spoke beyond pleasantries to DHET advisor
3. Two Departments focus on different and over-lapping aspects
of the system, without any co-ordination
20
National Planning Commission (Nov 2011): Functions of HE (1)
Higher education is the major driver of the information-knowledge
system, linking it with economic development...Universities are
key to developing a nation. They play three main functions in
society:
Firstly, they educate and train people with high-level skills for the
employment needs of the public and private sectors.
Secondly, universities are the dominant producers of new
knowledge, and they critique information and find new local and
global applications for existing knowledge. Universities also set
norms and standards, determine the curriculum, languages and
knowledge, ethics and philosophy underpinning a nation's
knowledge-capital. South Africa needs knowledge that equips
people for a society in constant social change
21
NPC: Functions (2)
"Thirdly, given the country's apartheid history, higher education
provides opportunities for social mobility and simultaneously
strengthens equity, social justice and democracy. In today's
knowledge society, higher education underpinned by a strong
science and technology innovation system is increasingly
important in opening up people's opportunities." (p262)
For the first time knowledge production and equity are linked by
stating that "high quality knowledge production cannot be fully
realized with a low student participation rate" (p274).
22
Also universities are not mainly fro individual mobility or for
equity redress - equity is mentioned last and transformation
in the Castells sense
NPC: Knowledge Enthusiasm
The NPC is so enthusiastic about knowledge that it declares that
"knowledge production is the rationale of higher education"
(p271) - indeed a radical departure from the traditional
'rationale' of higher education in Africa, that is, disseminating
(teaching) knowledge from somewhere else.
Posters outside Parliament for Thursday’s State of the Nation:
Knowledge Economy and Development Opportunities.
At ANC 100th Zuma said: “Education and skills are the key priority
for our people”
These are huge steps away from HE as individual mobility and an
equity instrument – but in State of Nation announced the
biggest infrastructure project in history – not a word of KE
23
NPC Knowledge Policies
1. the notion of knowledge production consists of a combination of
PhD education and research output.
2. a target of tripling the number of doctoral gradates from 1,420 to
5,000 per annum, and increasing the proportion of academic staff
with PhDs from 34% to 75%
3. a number of world-class centres and programmes should be
developed within the national system of innovation and the higher
education sector.
4. a new future scholars programme needs to be developed, both to
increase the proportion of staff with PhDs and to meet the
increasing demand for professional PhDs in the non-university
research, financial and services sectors
5. role of science councils should be reviewed in light of the worldwide tendency to align, or merge, research councils with universitie
24
NPC: Differentiation
1. deals with the worldwide policy debate about the
concentration of resources by proposing world-class centers
and programmes across institutions (High science - Ska)
2. advises the Ministerial Committee for the Review of the
Funding of Universities that such revisions should be based on
the needs of a differentiated system with adequate provision
for both teaching and research
3. requires flexible pathways for student mobility between
institutions
4. the Higher Education Quality Committee should finally start
developing a core set of quality indicators for the whole
system;
25
DHET Green Paper
Research and innovation
1. Economic depends on innovation and technology absorption
2. While investment in research has tripled, there has not been a
commensurate increase in personnel
3. Total knowledge output has increased 64% (2000-2009) but the
system must become more productive
4. Poverty is a significant constraint on masters and Phd studies –
students under pressure to obtain jobs??
5. Drastically increase number and quality of masters and PhD’s
6. Need for increased coordination between DHET and DST
7. Caliber and workload of academic staff must be addressed
8. Long term plan for renewing the academic profession doctorates for academics and professions
26
NPC and DHET: The Good, the Bad and the Incomprehensible
27
1. Differentiation (whatever form) is official
2. Knowledge production (PhD and research output must increase – different
counts of research outputs) – at last recognising the knowledge producing
role of the university
3. Big focus on doctorate – for academics (target more than 60%), professions
research councils and other sectors (finance)
4. Good quality undergraduate education – including infrastructure funds for
labs, libraries, housing
5. Improvement of through put – efficiency
6. Dramatic increase in participation rate – mainly in FET
7. Mission and profile differentiation
8. Creation of a connected system
9. Improved Coordination between DSHT and DHET (HESA meeting)
10. More funding for higher education
Ten Year Innovation Plan
 The Government of South Africa is implementing the Ten Year
Innovation Plan which includes five “Grand Challenges” that
build on and expand the country’s research capabilities
(Minister Naledi Pandor, 2009).
• The first grand challenge is to tap the potential of the bio-economy
for the pharmaceutical industry.
• The second grand challenge is to build on investments in space
science and technology.
• The third grand challenge is to move towards the use of renewable
energy.
• The fourth grand challenge is to play a leading, regional role in
climate change.
• The fifth and final grand challenge is termed “human and social
dynamics”.
28
Vuyani Lingela, 24 November 2011
The rise of doctorates
45.0%
40.0%
40.0%
Major expansion of higher education has
boosted PhD output in many countries,
shown here as average annual growth of
doctoral degrees across all disciplines.
1998 - 2006
35.0%
30.0%
25.0%
20.0%
17.1%
15.0%
10.0%
10.0%
8.5%
7.1%
6.4%
6.2%
6.2%
6.1%
5.2%
5.0%
2.5%
1.0%
0.0%
0.0%
-2.2%
-5.0%
China
Mexico Denmark
India
Korea
South
Africa
Japan
Australia Poland
Source: Nature. International weekly journal in Science
United
Kingdom
United
States
Canada Germany Hungary
HERANA - Total PhD enrolled and total PhD graduates, 2001 - 2007
7,000
6,080
6,000
5,000
4,000
3,000
2,000
1,759
1,103
1,000
931
187
299
34
126
0
Botswana
Makerere
6
0
Eduardo
Mondlane
854
674
648
83
Ghana
47
*Mauritius
163
90
Nairobi
Dar es
Salaam
203
NMMU
University of
Cape Town
* Mauritius enroll large numbers of students as MPhil students, and depending on their performance only some graduate as PhD
students
KP outputs: Universities of Sao Paolo, Pretoria and Cape Town
10000
9109
9000
8206
8000
7000
6000
5000
4000
3000
2244
2000
1187
1000
196
1184
1390
178
0
USP 2010
UP 2009
Doctoral graduates
UCT 2009
SA totals 2009
Research publications
31
Summary
1. Unprecedented shift from HE as instrument to advance equity and individual
mobility to HE as crucial part of development
2. Policy recognition of importance of coordination of policy and
implementation, but little sign of positive cooperation yet
3. SA a Medium knowledge producing system, rated around 30th in the world
4. SA has a few global high visibility big science projects
5. SA seems to be doing better in research output than in producing doctorates
6. Over –enthusiasm about dramatic increase in doctoral production
7. Next session on the Doctoral Project will explore this ‘doctoral exuberance’
through different empirical prisms
(Alan Greenspan initially attributed the 2008 crash to ‘irrational market exuberance’).
32
Graph 1 sets out data on key elements of SA’s high-level knowledge
production for the period 1996-2010 expressed as doctoral enrolments,
doctoral graduates and research publication units. Average annual changes
in these totals are reflected in Graph 2.
14000
11468
12000
9 800
1 0000
8790
4 000
2 000
Research pubs
7763
8 000
6 000
PhD enrolments
9939
5 622
5528
9 748
6 394
8 003
6483
6660
8 353
5 164
5456
5 936
6 85
761
961
9 69
1 104
1100
1 182
1 421
1996
1998
2000
2 002
2004
2006
2 008
2010
PhD graduates
0
Doctoral enrolments
Doctoral graduates
R esearch publications
33
Graph 2 divides Graph 1 growth rates into the period between (a) 1996 and
2002, which covered the period of the 1997 HE White Paper and the 2001
National Plans, and (b) 2004-2010 which covered the introduction and
implementation of the new 2003 government funding framework.
8.0%
7.0%
6.0%
7.0%
6.6%
6 .0%
5.9%
5 .4%
5.0%
4.5%
4 .3%
4.0%
4.0%
3.0%
2.4%
2.0%
1 .0%
0 .0%
1996-2002
Doctoral enrolments
2004-2010
Doctoral graduates
1996-2010
R esearch publications
34
Graph 3 divides the doctoral enrolment totals for 1996-2010 into race
groupings. The main change has been in African doctoral enrolments, which
increased from 663 in 1996 to 5066 in 2010, when African doctoral
enrolments exceeded that of White enrolments for the first time.
6000
4861
5 000
4486
4 020
4000
3 875
4819
3993
3583
5066
African
White
4 853
4 568
4 022
2 933
3 000
2239
2000
1610
1 053
1000
0
683
197
264
1996
344
256
1998
African
464
3 27
2000
7 68
8 13
774
8 68
419
5 29
585
575
6 81
2 002
2004
2006
2 008
2010
6 19
Coloured
Indian
White
Indian
Coloured
35
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
36
Graph 5 offers a first picture of the doctoral output efficiency of
SA’s public HE system, based on output ratios which appear in the
2001 National Plan. The National Plan set this as an output norm:
•
•
The ratio between doctoral graduates in a given year and doctoral
enrolments should = 20%. So, if 10 000 doctoral students were
enrolled in the HE system in year X, then at least 200 of these
students should graduate in year X.
This norm was based on a further target norm that at least 75% of
any cohort of students entering doctoral studies for the first time
in (say) year Y, should eventually graduate. Calculations had shown
that if the cohort output norm was to be achieved, then the 20%
ratio of total graduates to total enrolments would have to be met
over a period of time.
37
Graph 5 shows that, as far as doctoral outputs are concerned, the Public HE
system has failed to meet the National Plan’s efficiency targets. Calculations
show that over the period 1996–2002, less than 50% of students entering
doctoral programmes in SA will eventually graduate.
8 0%
75%
7 0%
6 0%
52%
5 0%
45%
45%
4 0%
3 0%
2 0%
20%
14%
12%
12%
1998-2002
2 002-2006
2006-2008
1 0%
0%
R atio of graduates to enrolments
Cohort graduation equivalent
National target
38
Graph 6 offers estimates of the effects of inefficiencies in SA’s doctoral
programmes. For example, over the period 2005-2010, SA should, on the
National Plan’s norms, have produced a total of 12 285 doctoral graduates
but in fact produced only 7 711, leaving a “shortfall” of 4 739 graduates
(who would have been drop outs from the system).
2005 - 2010
-4 739
Shortfall
-2735 2000 - 2004
2005 - 2010
National Plan target
2000 - 2004
2005 - 2010
Actual graduates produced
-6000
-4000
-2000
2000 - 2004
0
2000
4000
T otal 2005-2010
12285
7 711
7 546
4976
6000
8000
T otal 2000-2004
10000
12000
14000
39
Doctoral degree cohorts (2001, 2002, 2003): Average dropout &
graduation by Race
New
entrants
Race
2117
African
Academic year
Registered at beginning of
year
274
555
281
26
655
860
860
41%
Dropped out (Cumulative)
606
1017
1257
1257
59%
Registered at beginning of
year
274
119
44
4
91
130
130
47%
Dropped out (Cumulative)
45
108
144
144
53%
Registered at beginning of
year
555
193
101
4
202
254
254
46%
Dropped out (Cumulative)
116
216
301
301
54%
Registered at beginning of
year
3040
1034
441
58
1213
1523
1523
50%
Dropped out (Cumulative)
538
1158
1517
1517
50%
Registered at beginning of
year
5986
2011
867
92
2161
2767
2767
46%
1305
2499
3219
3219
54%
Graduated (Cumulative)
White
3040
Graduated (Cumulative)
Total
5986
Graduated (Cumulative)
Dropped out (Cumulative)
•
*Year 7
665
Graduated (Cumulative)
Indian
Year 5
2117
Graduated (Cumulative)
Coloured
Year 1
Total graduates &
dropouts for cohort
The End of year 7 dropping out numbers also include students that may have registered
in future years to complete their studies.
Source: DHET. 2011,
CHET PhD analysis
Doctoral degree cohorts (2001, 2002, 2003): Average dropout & graduation by
University Group
New
entrants
Academic year
Year 1
Year 5
Total graduates & dropouts
for cohort
*Year 7
High Productive Universities : University of Cape Town,
University of Pretoria, Rhodes University, University of Stellenbosch, University of the Witwatersrand
3098
Registered at beginning of year
Graduated (Cumulative)
3098
1230
509
29
1179
1532
1532
49%
495
1130
1566
1566
51%
Dropped out (Cumulative)
Other Universities : University of Fort Hare, University of the Free State, University of Limpopo, North-West University, University of the
Western Cape
978
Registered at beginning of year
Graduated (Cumulative)
978
10
316
372
144
485
485
50%
210
388
493
493
50%
Dropped out (Cumulative)
Comprehensive Universities : University of Johannesburg, Nelson Mandela Metropolitan University, University of South-Africa, University of
Venda,
Walter Sisulu University, University of Zululand
1702
Registered at beginning of year
Graduated (Cumulative)
1702
407
187
50
554
672
672
39%
530
869
1030
1030
61%
Dropped out (Cumulative)
Universities of Technology : Cape Peninsula University of Technology, Central University of Technology, Durban University of Technology,
Mangosuthu University of Technology, Tshwane University of Technology, Vaal University of Technology
208
Registered at beginning of year
Graduated (Cumulative)
Dropped out (Cumulative)
208
3
58
56
27
78
78
38%
70
112
130
130
63%
5986
2011
867
92
2161
2767
2767
46%
1305
2499
3219
3219
54%
Total
5986
Registered at beginning of year
Graduated (Cumulative)
Dropped out (Cumulative)
Source: DHET. 2011, CHET PhD analysis
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
Academic staff with doctoral degrees are a key input for high-level
knowledge production is. Permanent academic staff in this category should
be the major producers of research outputs, and at an input level the main
supervisors of doctoral students. Graph 7 shows how the totals of permanent
academic staff with doctoral degrees changed between 1996 and 2010.
18000
16000
1 4000
1 3449
13098
4647
4658
14184
14673
15423
1 5809
15936
5 146
5403
1 6684
T otal permanent
12000
10000
8 000
6 000
4561
4572
4485
5957
Highest
qualification
PhD
4 000
2 000
0
1 996
1998
2000
2002
Doctorate as highest qualification
2004
2 006
2008
Total permanent
2010
43
Graph 8 divides public HE institutions into the 3 categories used for
national planning purposes, and sub-divides the 11 universities into
a group of 6 which produces 60% of the HE system’s total high-level
knowledge products and the remaining 5. The groups are:
High productive universities
UCT, UKZN, Pretoria, Rhodes,
Stellenbosch, Wits
Other universities
Fort Hare, Free State, Limpopo,
North West, UWC
Comprehensive universities
UJ, NMMU, Unisa, Venda,
WSU, Zululand
Universities of technology
Cape Peninsula, Central, Durban,
Mangosuthu, Tshwane, Vaal DUT
44
Graph 8
60%
50%
40%
45%
36%
48%
41%
29%
2 0%
5%
Other
35%
38%
28%
29%
High productive
44%
40%
36%
30%
10%
44%
27%
7%
8%
2002
2 004
28%
10%
29%
40%
Comprehensive
28%
13%
15%
2008
2010
UoT
0%
2000
High productive universities
Other universities
2 006
Comprehenives
Universities of technology
45
The low proportions permanent academic staff with doctoral degrees
must have an impact on the numbers of doctoral students which can
be enrolled and supervised. Graph 9 shows what the ratios have
been between doctoral enrolments and permanent academic staff
with doctorates.
A ratio of two doctoral enrolments per permanent academic with a
doctorate could be used as an indicator of institutional capacity.
Graph 9 shows that the high productive group of universities and the
comprehensives had ratios above 2 in 2010, which could be taken to
imply that they have reached capacity as far as doctoral enrolments
are concerned. Increases in their doctoral enrolments should depend
on more academic staff obtain their own doctoral degrees.
The 2:1 norm suggests that the other group of 5 universities and the
universities of technology may have spare supervisory capacity, but
their ability to deal with this depends on their current financial and
efficiency levels.
46
Graph 9
2 .5
2 .2
2 .0
1 .7
2 .1
1 .8
1 .5
2.1
1.7
1.7
2.1
2.1 Other
1.7
1 .2
1.0
0.5
1.1
1 .2
High productive
Comprehensive
UoT
1.1
1.2
0 .8
0.0
2 000
High productive universities
2 004
Other universities
2 008
Comprehenives
2 010
Universities of technology
47
Government’s funding incentives for research outputs are complex
because of the 2-year time lag between the completing of an
output and the receipt of a funding allocation, and the weightings
applied to research outputs.
Graph 10 shows what research funding totals were generated by each output
category.
Graph 11 shows what the Rand values can be assigned to research output
units.
48
Graph 10
R 'millions
2500
2225
2000
Total
1837
1540
1500
1000
500
845
474
192
0
1245
1237
179
2004/05
919
489
228
202
2005/06
Publications units
1225
505
265
Pub. units
1 048
1024
652
596
310
343
253
298
282
2006/07
2007/08
2008/09
Research masters grads
796
379
4 14
365
375
2009/10
2010/11
Doctoral graduates
539
461
PhD graduates
Research M grads
2011/12
Total
49
Graph 11
R'000
450
393
400
Per PhD graduate
3 50
2 86
3 00
251
250
200
191
150
1 00
50
87
66
91
82
110
1 02
1 10
134
Per publication unit
Per research M grads
0
2005/06
Per publication unit
2007/08
2009/10
Per research masters graduate
2 011/12
Per doctoral graduate
50
It could be argued that the high Rand values for doctoral graduates
should have functioned as strong incentives to institutions to expand
these outputs. The data in Graph 12 suggest these financial
incentives have not yet affected doctoral graduate growth, which was
3.5% pa between 2000 & 2004, and 3.6% pa between 2005 and
2010.
There are likely to be a number of reasons why doctoral graduate
totals have not yet responded to the output funding incentives
introduced for the first time in the 2004/5 financial year. One
explanation is that only a few universities have been able to benefit
from the introduction of government research output incentives. A
second explanation is that doctoral processes in SA have been
characterised by high levels of inefficiency, as has been seen in
Graphs 5 and 6.
51
Graph 12
6.7%
7.0%
6 .2%
5.8%
6.0%
5.0%
4.4%
4.4%
4 .0%
3.5%
3.6%
3 .0%
2.0%
1.5%
1.0%
0.0%
Publication units
Masters graduates:
Research masters
coursework + research
graduates
2 000-2004
Doctoral graduates
2 005-2010
52
Graph 13 shows that government output funding can be related to staff
capacity. In 2011/12 the high productive university group generated
R290 000 in government research funds per permanent academic, which
was considerably higher than the averages for the other groupings.
R'000
350
290
3 00
High productive
250
2 15
192
200
1 50
135
58
0
Other
94
100
50
130
39
68
46
60
66
Comprehensive
8
13
19
25
2 005/06
2 007/08
2 009/10
2 011/12
High productive universities
Other universities
Comprehenives
UoT
Universities of technology
53
Graph 14 relates doctoral graduate funding to permanent academic
staff, but also compares this doctoral funding to research publication
funding per permanent academic. The graph shows that in 2011/12
the high productive universities group generated R82 000 in doctoral
funding per permanent academic, and R126 000 in research
publications. The amounts are lower, but similar wide differences
can be seen in the other institutional categories.
These lower amounts generated by doctoral graduates could be
related to institutional inefficiencies, but also to institutional
incentives. Some institutions distribute publication output funds to
authors, but few (if any) distribute doctoral graduate funds to
supervisors. Academic staff members are therefore likely to gain
more direct personal benefits from research publications than from
doctoral graduates.
54
Graph 14
R'000
1 40
126
1 20
1 00
82
80
61
60
42
40
40
20
5
5
11
0
High productive
Other universities
Comprehenives
Universities of technology
universities
Doctorates
Publications
55
Modes of coordination – (Braun 2008; Herana 2011)
1. Coordination of knowledge policies needs to take place at the
level of both policy formulation and policy implementation
(Braun)
2. Negative coordination is a non-cooperative game that leads … to
the mutual adjustment of actors, but not to concerted action nor
to cohesiveness of policies
3. Positive coordination goes beyond mutual adjustment… policy
integration’ (the coordination of goals) and ‘strategic
coordination’
4. Positive coordination require a Pact, does not absolutely need a
whole-government perspective, but a perspective that is agreed
upon by a number of relevant political actors.
5. Methods: Departmental Mergers, Coordination Structures,
Networks and Visions
56
Defining the ‘pact’
A ‘pact’ is a fairly long-term cultural commitment to and
from the University, as an institution with its own
foundational rules of appropriate practices, causal and
normative beliefs, and resources, yet validated by the
political and social system in which the University is
embedded. A pact, then, is different from a contract
based on continuous strategic calculation of expected
value by public authorities, organised external groups,
university employees, and students – all regularly
monitoring and assessing the University on the basis of
its usefulness for their self-interest, and acting
accordingly.
Knowledge and development
> The key findings of the three OECD systems were that
knowledge was regarded as a key driver for development, and
that education in general, but higher education in particular, is
important
> Is there agreement about the importance of knowledge for
development?
> Is there agreement about the role of the university in
development?
> We looked at national development plans, policies in different
departments such as education, science and technology,
planning commissions and interviewed some senior officials
> At the institutions we looked at the strategic plan and
interviewed a selection of leadership and academics
Findings: The pact
> There is a lack of agreement (pact) about a development model
and the role of higher education in development – at both
national and institutional levels
> There is an increasing awareness, particularly at government
level, of the importance of universities in the knowledge
economy
> The lack of a pact means that what is often explained as a
capacity problem could also be because of a lack of agreement
> This is a major cause of ‘policy instability’, of a lack of
coordination of policies across departments and of
implementation, and affects long-term planning and institutional
stability
SLIDE 1:
HIGH LEVEL KNOWLEDGE INPUTS AND OUTPUTS
Slide 1 uses averages for 2008-2010 for 4 input and 4 output variables, which reflect
the state of high level knowledge production in the HE system, as a way of clustering
HE institutions. These indicator averages are summarised in the Slide 1 data table.
• Inputs
Masters enrolments as % of total head count enrolments
Doctors enrolments as % of total head count enrolments
% of permanent academic staff with doctoral degrees
Ratio of doctoral enrolments to permanent academic staff
• Outputs
Ratio of masters graduates to masters enrolments (throughput proxy)
Ratio of doctoral graduates to doctoral enrolments (throughput proxy)
Ratio of doctoral graduates to permanent academics (measure of
academic staff research output efficiency)
Ratio of research publications to permanent academics (further
measure of academic staff research output efficiency)
60
61
Knowledge Production Input and Output Indicators (standardised): 2010
SLIDE 1
Averages (2008 – 2010)
2.00
Cluster 1
1.50
1.00
0.50
Cluster 2
0.00
-0.50
Cluster 3
-1.00
-1.50
Masters enrol Doctors enrol
%
%
Cluster 1:
1. University of Cape Town
2. Rhodes University
3. University of Stellenbosch
4. University of the Witwatersrand
Staff PhD
Ratio Phd
M Grad Rate PhD Grad Rate Ratio PhD
enrol to staff
grads to staff
Cluster 2:
1. University of Fort Hare
2. University of the Free State
3. University of Johannesburg
4. University of KwaZulu-Natal
5. Nelson Mandela Metropolitan University
6. North-West University
7. University of Pretoria
8. University of the Western Cape
9. University of Zululand
Pub Outpu
Cluster 3:
1. Cape Peninsula University of
Technology
2. Central University of Technology
3. Durban University of Technology
4. University of Limpopo
5. University of South Africa
6. Tshwane University of Technology
7. University of Venda
8. Vaal University of Technology
9. Walter Sisulu University
62