SOUTH AFRICAN PUBLIC HIGHER EDUCATION Key statistics 13577064788361230463714563284289654446577211113584176899718546351037601832163463181305468416335 13577064788361230463714563284289654446577211113584176899718546351037601832163463181305468416335 13577064788361230463714563284289654446577211113584176899718546351037601832163463181305468416335 13577064788361230463714563284289654446577211113584176899718546351037601832163463181305468416335 1357706478836123046371456328428965444657721111358417689971854 13577064788361230463714563284289654446577211113584176899718546351037
About the CHET Key Statistics on South African Public Higher Education Calendar In a submission to the National Planning Commission for the National Development Plan 2030, CHET argued that two central problems facing higher education in South Africa at present are: 1. to increase participation and 2. to increase knowledge production. Two related policy issues for planners are system efficiency and differentiation. These key issues provide the framework for the data selected and presented in this calendar. Note about Open Data on the CHET website CHET has made three data sets available on its website: 1. Performance indicator data on the 23 public universities in the South African higher education system. Data is from the 2010 HEMIS data and includes DHET-approved 2013 targets; 2. Data on the South African post-secondary eduation sector drawn from the CHET publication, Shaping the Future of South Africa s Youth. The data is available via Google s Public Data service; and 3. Performance indicator data on eight African universities drawn from the CHET publication, Cross-National Performance Indicators: A case study of eight African universities. The data presents a set of cross-national, comparative data on the performance of eight African universities. The data is available free of charge on the CHET website. See www.chet.org.za/data Data analysis Data analyses for CHET is undertaken by Ian Bunting, retired planner in the Department of Education and former Dean at the University of Cape Town; by Dr Charles Sheppard, Director: Management Information at the Nelson Mandela Metropolitan University and consultant to the Department of Higher Education and Training; and by Prof. Johann Mouton, Director: Centre for Research on Evaluation, Science and Technology (CREST), Stellenbosch University. Data sources Data are drawn from sources both locally and internationally. In particular, data for the South African system are drawn from the HEMIS and FETMIS databases. Please consult the back of the calendar for detailed notes and sources for the data presented. Concept and data visualisation Prof. Jo Muller and François van Schalkwyk
The South African Post-school System 2010 new additional university places available in 2013 42 776 Government-set 2013 public university enrolment target of 935 712 students less actual enrolments in public universities in 2010 University students 986 559 College students 404 849 Public 326 889 Private 77 960 18 to 24-year-olds Not in education, employment or training 2 781 185 Public 892 936 Private 93 623 At its first meeting in 1995 the National Commission on Higher Education identified the inverted pyramid shape of the SA system as a central problem it still is. The 2012 Draft Green Paper proposes that by 2030 there should be 1.5 million university and 4 million students in other forms of post-school education; even if overambitious, this is the first post-1994 government policy that directly addresses the inverted pyramid. Achieving these projections will require a huge expansion of private provision as well as distance education offerings in universities, and in the college sector in particular. Shape of the US public post-secondary system 2009, number of institutions 615 1092 3660 4-year college/university degree 2-year college/university degree Post-secondary technical qualification
Population and post-school enrolments by province 2010 Western Cape Northern Cape Gauteng Gauteng North West Free State Eastern Cape Limpopo Mpumalanga KwaZulu-Natal Population 23 universities colleges 50 = 2 million University enrolments = 10 000 College enrolments = 10 000 /4 = no. of institutions At provincial level, both the number of institutions and the post-school student enrolment patterns are unequally distributed in relation to population sizes. The highest post-school attendance according to Census 2011 was in Gauteng, followed by the Western Cape and the Free State. This is also reflected in the qualification profile of those 20 years and older. In Gauteng 18% of the population had a post-secondary qualification, followed by the Western Cape (14.4%) and the Free State (9.8%). The Northern Cape (7.5%), North West Province (7.7%) and the Eastern Cape (8.7%) had the lowest percentages of people with a postsecondary qualification.
Gross enrolment ratios and global competitiveness Gross enrolment ratio (%) 110 100 90 80 70 60 50 40 30 20 10 Ghana Uganda Mozambique Stage 3 economy: Innovation-driven Stage 2 economy: Efficiency-driven Transition from Stage 1 to Stage 2 economy Stage 1 economy: Factor-driven Kenya Tanzania Botswana Mauritius South Africa South Korea Finland USA There is a correlation between a country s gross enrolment ratio in higher education and its global competitiveness. Innovation-driven economies have high gross enrolment ratios while factor-driven economies have very low participation rates. South Africa and Brazil both had participation rates of around 8% in 1994; Brazil, with private mass-orientated institutions now exceeds 35% while South Africa is at just over 20%. In Brazil the gini-coefficient is on a downward trend while in South Africa the trend is slightly upward. 130 120 110 100 90 80 70 60 50 40 30 20 10 1 World Economic Forum Global Competitiveness Index (overall ranking 2010 or most recent)
Race composition of public universities 1996 vs 2010 67 61 57 Gross participation rates % head-count enrolments Female students 48% 57% 53 45 1996 2010 % 34 35 9 14 20 7 7 6 6 1996 2010 1996 2010 1996 2010 1996 2010 African White Indian Coloured Race 10 15 While 67% of students in the current university system are African, their participation rate is still low (14%). In order to increase the participation rate of Africans significantly, the system has to massify and the major growth will have to be in the college sector.
Graduates by broad fields of study 2000 to 2010 80 000 70 000 60 000 50 000 40 000 Science and technology (S&T) Business and management (B&M) Humanities Education Education Humanities 2010 2000 42 760 41 657 37 892 S&T B&M Despite policy suggestions to increase S&T enrolments, the mix of fields of study in the system has remained remarkably resistant. The exception is the increase in education graduates (at the expense of the humanities); education is a national priority area. 30 000 28 581 24 136 31 016 Africa comparison (universities) Science and technology graduates 2007 (%) Global comparison (systems) Science and technology graduates 2009 (%) 20 000 19 912 48 43 42 48.6 40.3 35.9 31.5 15 568 36 32 31 22 18 27.9 10 000 2000 2002 2004 2006 2008 2010 Eduardo Mondlane U U of Mauritius U of Cape Town U of Dar es Salaam Makerere U U of Nairobi U of Botswana U of Ghana GERMANY UK JAPAN USA SOUTH AFRICA
Undergraduate throughput rates 2005 cohort new entrants 32 178 students registered 3 years 4 years 5 years 6 years Graduate (end of the year) graduate 51% Re-register (beginning of the year) Drop out (end of the year) drop out 49% 2005 2006 2007 2008 2009 2010 30% of the 2005 cohort of students dropped out after their first year. Only 27% of the 2005 cohort of students graduated in the minimum time and only 51% complete their studies after 6 years. Two proposals to increase success are a 4-year degree and diploma structure, and/or a shift from input (enrolment) funding to output (graduation) funding.
Throughput rates for all qualification levels 2005 cohort Qualification level Entrants Year 1 Year 3 Year 5 Total Graduate - 16% 19% 35% 3-year diplomas 37 330 Drop out 33% 18% 5% 56% Graduate - 27% 21% 48% Undergraduate degrees 32 178 Drop out 30% 12% 4% 46% Graduate 6% 25% 12% 33% Masters 15 479 Drop out 28% 15% 13% 57% At all levels, the first year of study seems to be the crucial hurdle. The drop-out figures look considerably worse if the drop-outs from UNISA are included. The World Bank classifies South Africa as a low participation, high drop-out system. Doctorates 2 140 Graduate 1% 14% 20% 35% Drop out 22% 15% 4% 41%
Doctoral enrolments versus graduates 1996 to 2010 Doctoral enrolments Doctoral graduates 11 468 South Africa producess 28 doctoral graduates per million of the population. To achieve the National Planning Commission s target of 100 doctoral graduates per million, the number of graduates will have to increase 4-fold to 5 000 per annum. 9800 6394 5164 1421 1100 961 685 1996 2000 2006 2010 Despite government funding incentives for doctoral enrolments and graduates, the number of doctoral graduates relative to enrolments has remained flat. In 2010, for the first time in history, South Africa enrolled more African than Doctoral graduation rates 2010 white PhD candidates; but over 50% of the coutry s 2.4 2.3 1.6 African PhD candidates 1.3 are from elsewhere on the African continent. CHINA FINLAND USA KOREA 0.4 0.4 0.1 BRAZIL RUSSIA SOUTH AFRICA
Research output of academic staff 1996 to 2010 25 000 20 000 15 000 10 000 Research publications Permanent academic staff Permanent academic staff with doctorates The output of research publications of South African universities has increased significantly over the past 8 years. The introduction of the current funding framework in 2005 seems to have resulted in large annual increases in the publication output: total output in 2010 is close to 10 000 publication units. The increase in publication units has come during a period where the number of academic staff with PhDs has remained static. 5000 1996 2000 2006 2010
The citation impact of South African science 2000 to 2010 1.00 0.95 0.90 0.85 0.80 0.75 0.70 0.65 0.60 0.55 World Mean Normalised Citation Score South African Mean Normalised Citation Score Top 1% highly cited papers Top 10% highly cited papers Top 20% highly cited papers The citation impact of South African science has increased significantly from 0.77 in 2000 2003 to 0.92 in 2007 2010. (It is still below world average but approaching it rapidly.) Given that 60% of the world average is determined by the USA and Europe, one could argue that South Africa is on track to become one of the more advanced science nations. The increase in citation impact owes a lot to the rise of South Africa among the top 1% most highly cited publications worldwide South Africa is actually relatively wellrepresented in the world s top performing publications. 0.50 2000 to 2003 2001 to 2004 2002 to 2005 2003 to 2006 2004 to 2007 2005 to 2008 2006 to 2009 2007 to 2010
Higher education income 2000 vs 2010 Private Student fees Government 3.59bn 26.4% 3.38bn 24.6% 6.63bn 48.7% 2000 2010 Income (nominal ZAR) 6.69bn 29.6% 6.71bn 29.7% 9.21bn 40.7% 0.2bn 0.7% 0.5bn 2.1% 1.9bn 8.4% 3.4bn 14.0% 1.7bn 6.8% 2.2bn 9.2% 2.5bn 10.5% 11.7bn 48.3% Actual distribution of DHET budget to HEIs 2012/13 (real ZAR) Other Student loans (NSFAS) Infrastructure & efficiency Research development Research outputs Teaching development Teaching outputs Teaching inputs Higher education income has increased in real terms across all three revenue streams but government s proportional contribution to university income has declined by 8%. Only 9.9% of direct expenditure by government is research orientated (research outputs 9.2% and research development 0.7%). South Africa s spending on education compares favorably internationally, but not its percentage spent on higher education. If in 2011 South Africa spent the same proportion of education expenditure on higher education as the world average, then it would have to add R15 billion to the R22 billion spent. Expenditure on tertiary education % of GDP Public sources only 2009 1.82 Finland 1.26 1.18 India Russia 1.01 USA 0.83 0.73 0.71 Brazil Mauritius Korea 0.58 South Africa 0.41 Botswana
UKZN A differentiated university system 2010 Academic staff input CLUSTER 1 AVERAGES Undergraduate to masters output High-level knowledge output 3.6 3.5 3.2 Academic staff input CLUSTER 2 AVERAGES Undergraduate to masters output High-level knowledge output 2.3 3.0 1.7 Academic staff input CLUSTER 3 AVERAGES Undergraduate to masters output High-level knowledge output 1.6 2.1 1.5 4 3 TUT CUT UZ UL WSU 2 1 UV Unisa UFS MUT DUT VUT 4 3 2 1 1 2 CPUT 3 4 UCT Rhodes NMMU SU UJ NWU UP 1 2 3 4 FH UWC Wits Empirically South Africa has a differentiated system that is more unequal than what it is diverse. Cluster 1 (blue) shows that the traditional Top 5 is changing, while Cluster 2 (orange) shows that institutional positions are changing. Despite the high statistical correlation between having a doctorate and publishing, high staff inputs do not in all institutions translate into high undergraduate throughput or knowledge output. CPUT: Cape Peninsula University of Technology CUT: Central University of Technology DUT: Durban University of Technology FH: Fort Hare University MUT: Mangosuthu University of Technology NMMU: Nelson Mandela Metropolitan University NWU: North West University Rhodes: Rhodes University SU: Stellenbosch University TUT: Tshwane University of Technology UCT: University of Cape Town UFS: University of the Free State UJ: University of Johannesburg UKZN: University of KwaZulu-Natal UL: University of Limpopo Unisa: University of South Africa UP: University of Pretoria UV: University of Venda UWC: University of the Western Cape UZ: University of Zululand VUT: Vaal University of Technology Wits: University of the Witwatersrand WSU: Walter Sisulu University
Notes and sources South African post-school system 2010 (January) Notes: Enrolments are head-count enrolments for public universities (including the University of South Africa) and further education and training colleges. Sources: University enrolments: Centre for Higher Education Transformation from the Higher Education Management Information System (HEMIS), Department of Higher Education and Training. www.chet.org.za/data. Further education and training colleges enrolments: Perold H, Cloete N & Papier J (2012) Shaping the Future of South Africa s Youth: Rethinking post-school education and skills training. Cape Town: African Minds. Data available at www.chet.org.za/data. NEET data: Cloete N (ed.) (2009) Responding to the Needs of Post-school Youth. Cape Town: CHET. Shape of the US public post-secondary system 2009 (January) Sources: College/university data: http://chronicle.com/free/ almanac/1999/nation/nation.htm. Post-secondary data: http:// nces.ed.gov/surveys/peqis/publications/2000023/images/tab1.gif Population and post-school enrolments by province 2010 (February) Notes: Enrolments are head-count enrolments for public universities (excluding the University of South Africa) and further education and training colleges. Sources: Population data: StatsSA Mid-year Population Estimates 2009; Census 2011. University enrolments: 2010 data, Centre for Higher Education Transformation from the Higher Education Management Information System (HEMIS), Department of Higher Education and Training. www.chet.org.za/data. Further education and training colleges enrolments: Perold H, Cloete N & Papier J (2012) Shaping the Future of South Africa s Youth: Rethinking post-school education and skills training. Cape Town: African Minds. Data available at www.chet.org.za/data Gross enrolment ratios and global competitiveness (March) Notes: GER = total tertiary enrolment as a percentage of the population aged 20 to 24 years. South Africa GER data includes college enrolments. Years are closest to 2010 and comparative by country: Country GER Source and Year Global Competiveness Index Year South Korea Unesco 2010 WEF 2009-2010 US Unesco 2010 WEF 2009-2010 Finland Unesco 2010 WEF 2009-2010 South Africa CHET 2008 WEF 2008-2009 Mauritius TEC 2010 WEF 2009-2010 Botswana CHET 2008 WEF 2007-2008 Ghana Unesco 2009 WEF 2008-2009 Kenya Unesco 2009 WEF 2008-2009 Uganda Unesco 2009 WEF 2008-2009 Mozambique CHET 2008 WEF 2007-2008 Tanzania Unesco 2010 WEF 2009-2010 Sources: Global Competitiveness Index data: http://www. weforum.org/issues/competitiveness-0/gci2012-data-platform/ GER data: Unesco, http://stats.uis.unesco.org/unesco/tableviewer/ tableview.aspx GER for Mauritius: Mauritius Tertiary Education Commission, http://www.tec.mu/tesm_rvw.php. Excludes students studying abroad. GERs for Mozambique & South Africa: Centre for Higher Education Transformation (CHET). Race composition of public universities 1996 vs 2010 (April) Source: Centre for Higher Education Transformation from the Higher Education Management Information System (HEMIS), Department of Higher Education and Training. www.chet.org.za/data Female students in public universities 1996 vs 2010 (April) Source: Centre for Higher Education Transformation from the Higher Education Management Information System (HEMIS), Department of Higher Education and Training. www.chet.org.za/data Graduates by broad fields of study 1996 to 2010 (May) Notes: Science & technology includes agriculture, architecture, computer sciences, engineering, health sciences, life and physical sciences. Business and management includes accounting, auditing, finance, taxation, insurance, marketing, human resource management. Humanities and education includes visual and performing arts, education, languages and literature, social services, social sciences. Source: Centre for Higher Education Transformation from the Higher Education Management Information System (HEMIS), Department of Higher Education and Training. www.chet.org.za/data
Notes and sources continued Africa comparison (universities): Science & technology graduates 2007 (May) Source: Bunting I & Cloete N (2012) Cross-National Performance Indicators. Cape Town: African Minds. www.chet.org.za/data Global comparison (systems): Science & technology graduates 2009 (May) Source: World science and technology graduates: Eurostat 2009 http://epp.eurostat.ec.europa.eu/statistics_explained/index. php?title=file:graduates_from_tertiary_education,_by_field_of_ education,_2009_%281%29.png&filetimestamp=20111117133355 South Africa science and technology graduates: Centre for Higher Education Transformation from the Higher Education Management Information System (HEMIS), Department of Higher Education and Training. www.chet.org.za/data Undergraduate throughput rates (June) Notes: General and professional 3-year degrees (excluding Unisa). A drop-out is recorded when a student s record on the Higher Education Management Information System (HEMIS) becomes inactive; it is not equivalent to a student failing and excludes cases where students transfer to other universties. Source: Council on Higher Education and Department of Higher Education and Training cohort analysis 2012. Throughput rates for all qualifications (July) Notes: General and professional 3-year degrees (excluding Unisa). A drop-out is recorded when student s record on the Higher Education Management Information System (HEMIS) becomes inactive; it is not equivalent to a student failing and excludes cases where students transfer to other universties. Source: Council on Higher Education, and Department of Higher Education and Training cohort analysis 2012. Doctoral enrolments versus graduates 1996 to 2010 (August) Source: Centre for Higher Education Transformation from the Higher Education Management Information System (HEMIS), Department of Higher Education and Training. www.chet.org.za/data Doctoral graduation rates 2010: global comparison (August) Source: OECD: www.oecd.org/edu/eag2012). India: UNESCO Institute for Statistics (World Education Indicators programme). South Africa: UNESCO Institute for Statistics. Table B2.3. Research output of academic staff 1996 to 2010 (September) Notes: Academic staff are full-time academic staff. Research publications are publications accepted by the Department of Higher Education and Training for funding subsidy purposes. Source: Centre for Higher Education Transformation from the Higher Education Management Information System (HEMIS), Department of Higher Education and Training. www.chet.org.za/data The citation impact of South African science (October) Notes: The impact of SA science can be measured by examining the contents of the footnotes or reference lists within Web of Science (WoS)-indexed journal publications. This citation impact analysis, as far as it concerns citing and cited sources within the WoS, is a fairly objective and internationally accepted method of determining the impact of science. Correcting for field-specific differences world-wide produces a field-normalised Mean Normalised Citation Score (MNCS) of South African science that can be compared against the world average impact scores. The world MNCS average is set equal to 1.00. Source: CWTS Web of Science database (Robert Tijssen 2012). Higher education income 2000 & 2010 (November) Source: Centre for Higher Education Transformation from the Higher Education Management Information System (HEMIS), Department of Higher Education and Training. www.chet.org.za/data Expenditure on tertiary education % of GDP: Public sources only 2009 (November) Source: OECD www.oecd.org/edu/eag2012 A differentiated system 2010 (December) Notes: Refer to the CHET website for detailed notes on how the ratings and clusters were calculated http://www.chet.org.za/ resources/differentiated-south-african-university-system-2012 Source: Centre for Higher Education Transformation calculations using data from the Higher Education Management Information System (HEMIS), Department of Higher Education and Training. Designed by COMPRESS.dsl www.compressdsl.com