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

4 HERANA Higher Education Research & Advocacy Network in Africa RESEARCHADVOCACY 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 University World News (Africa) Current news and in-depth investigations into higher education in Africa The HERANA Gateway An internet portal to research on 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

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

Country GDP per capita (PPP, $US) 2007 GDP ranking HDI Ranking (2007) GDP ranking per capita minus HDI ranking Botswana Mauritius South Africa Chile Costa Rica Taiwan (China) Ghana Kenya Mozambique Uganda Tanzania Finland South Korea USA

9 Data source: Thomson Reuters InCites TM (21 September 2010); The World Bank Group (2010) (R = 0.714, P = 0.218) (R = 0.961, P = 0.002)*

Country Stage of development ( ) Gross tertiary education enrolment rate (2008) Quality of education system ranking ( ) Overall global competitive ranking ( ) Ghana Stage 1: Factor-driven Kenya Mozambique Tanzania Uganda Botswana Transition from 1 to Mauritius Stage 2: Efficiency-driven South Africa Finland Stage 3: Innovation-driven 9467 South Korea United States82264

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

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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

15 Government External Groupings University Pact Academic Core Connectedness

1.Narrative, intent and structures for the Role of HE in development 2.Visions and plans, i.e. Development Visions ( ) 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 Appears in a number of policies 2 Weak Only mentioned in one policy 1 Absent Not mentioned at all A role for higher education in development in national policies and plans 3 Prevalent Clearly mentioned in development policies 2 Weak1 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 2 Weak Vague reference in strategic plan or research policy 1 Absent Not mentioned at all A role for higher education in development in national policies and plans 3 Institutional policy 2 Embedded in strategic plan, research policy 1 Absent No formal policies

18 Connectedness University not part of national development model/strategy University part of national development model/strategy Knowledge No or marginal role for new knowledge in development model AcillaryInstrument Central role for new knowledge in development model Self-governanceEngine

19 INDICATORSMax. scoreBotswanaGhanaKenyaMauritiusMoz. South Africa TanzaniaUganda NATIONAL LEVEL 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

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

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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

26 Target = 40% enrolments in science & technology

Qualification levels of permanent academic staff members

Research funding Research funding resources (in US$) available in 2007 to the academic staff members of each university.

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Graph 1 offers summaries for the 15-year period Doctoral enrolments were 1.3% of national total of students in Permanent academics Doctoral enrolments Research publications Doctoral graduates

Graph 4 shows how the % of doctoral enrolments by race group changed between 1996 to African doctoral students rose from 13% in 1996 to 33% in 2004, and 44% in

Enrolments South AfricanInternationalTotal GraduatesSouth AfricanInternationalTotal Graduates NorwegianInternationalTotal 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

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