Makerere University CHET August 2012

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• 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 ADVOCACY The HERANA Gateway An internet portal to research on higher education in Africa The Research-Policy Nexus Investigating the relationship between research evidence and policy-making in selected public policy sectors in South 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.

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Country Botswana Mauritius South Africa Chile Costa Rica Taiwan (China) Ghana Kenya Mozambique Uganda Tanzania Finland South Korea USA GDP per capita (PPP, $US) 2007 13 604 11 296 9 757 13 880 10 842 1 334 1 542 802 1 059 1 208 34 256 24 801 45 592 GDP ranking 60 68 78 59 73 153 149 169 163 157 23 35 9 HDI Ranking (2007) 125 81 129 44 54 152 147 172 157 151 12 26 13 GDP ranking per capita minus HDI ranking -65 -13 -51 +15 +19 1 2 -3 6 6 11 9 -4

GDP per capita (current US$) Predicted GDP per capita (current US$) High Australia Italy Low Tunisia Egypt Mexico Brazil Argentina South Africa India Korea Low

Influence of Scientific Research

(R = 0.714, (R = 0.961, P P = 0.218) = 0.002)* China High United States Japan UK Germany Data source: Thomson Reuters InCites TM (21 September 2010); The World Bank Group (2010) 9

Country Stage of development (2009-2010) Ghana Kenya Mozambique Tanzania Uganda Stage 1: Factor-driven Botswana Mauritius South Africa Finland South Korea United States Transition from 1 to 2 Stage 2: Efficiency-driven Stage 3: Innovation-driven Gross tertiary education enrolment rate (2008) 6 4 2 2 5 20 26 18 94 98 82 Quality of education system ranking (2009-2010) 71 32 81 99 72 48 50 130 6 57 26 Overall global competitive ranking (2010-2011) 114 106 131 113 118 76 55 54 7 22 4

• • • • • • • 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 projects is crucial of national and institutional knowledge policies to the academic core and to development 12

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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

External Groupings Students Business Community Funders Business Government Government departments: Education; Science and Technology; Treasury; Industrial Development; Research Councils Notions and policies Coordination mechanisms 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

Concept of a knowledge economy features in the national development plan A role for higher education in development in national policies and plans

National rating = 4/6

3 Strong

Appears in a number of policies 3 Prevalent Clearly mentioned in development policies

2 Weak

Only mentioned in one policy 2 Weak Concept of a knowledge economy features in university policies and plans A role for higher education in development in national policies and plans

University of Makerere rating = 5/6

3 Strong

Features strongly in strategic plan and/or research policy/strategy

3

Institutional policy

2 Weak

Vague reference in strategic plan or research policy

2

Embedded in strategic plan, research policy

1 Absent

Not mentioned at all 1 Absent

1 Absent

Not mentioned at all

1 Absent

No formal policies

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 Central role for new knowledge in development model Acillary Self-governance Instrument Engine 18

INDICATORS Max. score Botswana Ghana Kenya Mauritius Moz.

South Africa Tanzania Uganda NATIONAL LEVEL 9 Economic development and higher education planning are linked Coordination and consensus building of government agencies involved in higher education Link between universities and national authorities 3 3 3 3 1 1 1 3 1 1 1 6 2 2 2 7 3 2 2 4 1 1 2 6 2 2 2 4 1 1 2 3 1 1 1 19

1.

2.

3.

4.

5.

At national level the importance of knowledge economy and the importance of higher education were rather weakly reflected in national policy statements 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. In contrast, at institutional level a much stronger reference to knowledge economy and the importance of the university in development in the strategic plan.

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 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!!

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• 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

100% 80% 60% 40% 51% 27% 20% 0% 22% Botswana 2001/2 Science & technology Business & management Humanities and social sciences Target = 40% enrolments in science & technology 52% 27% 21% Botswana 2009/102 33% 26% 41% Cape Town 2001/2 37% 22% 41% Cape Town 2009/10 65% 19% 16% Makerere 2001/2 50% 10% 40% Makerere 2009/10 26

Qualification levels of permanent academic staff members UDSM, Highest qualification level of permanent academic staff members (2007) Makerere, Highest qualification level of permanent academic staff members (2007) 25% 25% 50% Ghana, Highest qualification level of permanent academic staff members (2007) 11% 47% Doctorate Masters Other 42% Doctorate Masters Other 17% 31% Doctorate Masters Other 52% UCT, Highest qualification level of permanent academic staff members (2007) 12% 30% 58% Doctorate Masters 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 UDSM 3,3 3,1 Makerere 3,1 1,4 Ghana 1,4 UCT 29,7

1200 1000 800 600 400 200 0 10 16 32 51 Botswana 2001/2 706 783 2003/4 970 1002 Cape Town 2005/6 31 41 54 32 Makerere 2007/8 92 102 110 120 Ghana 29

200 180 160 140 120 100 80 60 40 20 0 4 6 6 3 6 Botswana 2001/2 2003/4 182 2005/6 178 142 86 103 Cape Town 2007/8 12 16 18 30 55 Makerere 2009/10 8 9 20 11 17 Ghana 30

1200 1000 800 600 400 200 0 78 72 85 120 Botswana 2001/2 700 564 893 2003/4 1014 Cape Town 2005/6 73 107 118 233 Makerere 2007/8 66 71 68 101 Ghana 31

400 350 300 250 200 150 100 50 0 72 11 73 12 Doctoral graduates 76 21 107 16 131 25 118 18 Research publications 139 23 233 30 230 38 338 55 2000/1 2001/2 2002/3 2003/4 2004/5 2005/6 2006/7 2007/8 2008/9 2009/10 32

1,20 1,10 1,00 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 1,14 0,15 Cape Town Doctoral graduates Research publications 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.

18000 16000 14000 12000 10000 8000 6000 4000 2000 0 13449 5164 5622 685 13098 5528 5456 761 1996 1998 Doctoral enrolments 14184 6394 5936 961 14673 7763 6483 969 2000 2002 Doctoral graduates 15423 8790 6660 1104 15809 9800 8003 1100 2004 2006 Research publications 15936 9939 8353 1182 2008 16684 11468 9748 2010 Permanent academics Doctoral enrolments Research publications 1421 Doctoral graduates 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.

40% 30% 20% 10% 0% 90% 80% 70% 60% 50% 78% 62% 13% 9% 1996 African 25% 13% 2000 55% 33% 12% White 2004 49% 41% 10% 44% 42% African White 14% Coloured+Indian 2008 Coloured +Indian 2010 35

100% 80% 60% 40% 20% 0% South African Universities – PhD graduates by nationality South African International 100% 80% 60% 40% 20% 0% 29% 71% 30% 70% 34% 66% 34% 66% 2007 2008 2009 2010 Norwegian Universities - PhD graduates by nationality Norwegian International 23% 77% 25% 75% 26% 74% 28% 72% 33% 67% 2007 2008 2009 2010 2011 Enrolments 2007 2008 2009 South African International Total 7 195 6 959 7 213 2 853 3 035 3 316 2010 7 841 3 749 Graduates South African International 2007 900 374 10 048 9 994 10 529 11 590 Total 1 274 2008 2009 2010 829 908 931 353 470 489 1 182 1 378 1 420 South African PhD students graduation rate by South African nationality International 15% 14% 13% 13% 13% 12% 13% 13% 12% 11% 12% 2007 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 Norwegian International 2007 2008 2009 2010 2011 789 937 851 858 889 241 308 297 326 438 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 2.

from three successful systems (Pillay) Universities and Economic Development in Africa: Pact, academic core and 3.

coordination (Cloete, Bailey, Maassen) Universities and Economic Development in Africa: Key findings 4.

5.

6.

7.

8.

9.

(Cloete, Bailey, Bunting & Maassen) Country and University Case Studies: Botswana (Bailey, Cloete, Pillay) Country and University Case Studies: Ghana (Bailey, Cloete, Pillay) Country and University Case Studies: Kenya (Bailey, Cloete, Pillay) Country and University Case Studies: Mauritius (Bailey, Cloete, Pillay) Country and University Case Studies: Mozambique (Bailey, Cloete, Pillay) 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