Post-School Education and Training Monitor

Post-School Education and Training Monitor MACRO-INDICATOR TRENDS

MARCH 2021

Post-School Education and Training Monitor MACRO-INDICATOR TRENDS

Authors:

Mamphokhu Khuluvhe

Edzani Netshifhefhe

Elvis Ganyaupfu

Vusani Negogogo

MARCH 2021

Department of Higher Education and Training

123 Francis Baard Street Pretoria 0001 Tel: (+ 27) 0800 87 22 22

Published by the Department of Higher Education and Training. www.dhet.gov.za © Department of Higher Education and Training, 2021

The ideas, opinions, conclusions, and policy recommendations expressed in this report are strictly those of the authors and do not necessarily represent those of the Department of Higher Education and Training (DHET). The DHET will not be liable for any incorrect data and for errors in the conclusions, opinions, and interpretations emanating from this information.

Khuluvhe, M., Netshifhefhe, E., Ganyaupfu, E., and Negogogo, V., (2021). Post-School Education and Training Monitor: Macro- Indicator Trends. Department of Higher Education and Training, Pretoria.

ISBN: 978-1-77018-865-5

This report is available on the DHET’s website: www.dhet.gov.za

Enquiries: The Director: System Monitoring and Labour Market Intelligence Tel: +27 (012) 312 5465/5595 Email: [email protected]

POST-SCHOOL EDUC ATION AND TR AINING MONITOR | MACRO - INDICATOR TRENDS | 3

FOREWORD BY THE DIRECTOR GENERAL

It is my pleasure to present to you the second edition of the Post-School Education and Training Monitor report, the Macro-Indicator Trends edition. This report monitors the progress made by the post-school education and training system in relation to the goals articulated in the White Paper on the matter, for the period 2010–2019. As indicated in its subtitle, the report adopts high-level quantitative indicators to track progress on key dimensions of the post-school education and training system. Many of the indicators selected for the report are used by international organisations such as United Nations Educational, Social and Cultural Organisation and

the Organisation for Economic Co-operation and Development to undertake cross-country comparisons of education inputs, outputs, and outcomes.

As such, the report focuses on South Africa and also provides data on how the South African post-school education and training system has progressed in relation to that of other countries.

The report shows that more adults today have secondary education as their highest level of education attained in South Africa compared to a decade ago. Currently, 32.1 percent of adults have secondary schooling as their highest level of education attained, which points to a potential increase in the demand for PSET and the consequent need for a pronounced expansion of the PSET system.

In South Africa, there has been substantial growth in terms of access to both universities and technical and vocational education and training colleges. It is therefore possible for universities to meet the National Development Plan enrolment target of 1.62 million students by 2030, but only if student enrolment increases annually at the same average rate as that obtained over the past decade. Despite a significant growth in enrolment at

4 | POST-SCHOOL EDUC ATION AND TR AINING MONITOR | MACRO - INDICATOR TRENDS

universities, it remains disconcerting that participation rates at universities continue to fare very poorly in comparison to many other countries, thereby compromising South Africa’s international economic competitiveness. Similarly, enrolments at technical and vocational education and training colleges have almost doubled from 2010 to 2019. However, the average annual growth rate recorded from that period would need to be doubled per annum from 2019 to 2030 for the National Development Plan enrolment target to be realised.

The report further demonstrates that access to post-school education and training favours female students considerably more than male students. The Gender Parity Index for post-school education and training in South Africa is one of the highest in the world, suggesting the prevalence of an interplay of complex factors in the South African fabric of society that accounts for other forms of gender inequality in the country.

On a positive note, graduation rates for public universities have continued to grow in the period under review for all race groups and among both females and males. At technical and vocational education and training colleges, certification rates have also increased significantly for all programmes.

The university sector is becoming more efficient in terms of its improved throughput rates and declining dropout rates. However, it still takes too long for a significant proportion of students to complete their degrees, and the percentage of students who drop out before the completion of their degrees remains prohibitive.

The Department of Higher Education and Training welcomes any feedback, including suggestions for improvement, which can be emailed to [email protected].

Mr G. F. QondeDirector-General, Department of Higher Education and TrainingPretoria, South Africa


ACKNOWLEDGEMENTS

The production of this report was made possible by the contributions of several people. We would like to gratefully acknowledge the following individuals:

| Ms Nthabiseng Tema, Ms Jean Skene, Ms Pearl Whittle, Ms Matome Mafa, Mr Izak Joubert, and Mr Bully Sedibe of the Department of Higher Education and Training (DHET), for providing the data that have made this publication accurate.

| Ms Marieke Vandeweyer of the OECD for the provision and interpretation of skills mismatches data.

| Prof Servaas van der Berg of the University of Stellenbosch for his valuable insight and advice.

| External peer reviewers Dr Hersheela Narsee (an independent consulting expert) and Dr Veerle Dieltiens (of Mzabalazo Advisory Services) for their recommendations and positive feedback.

| Ms Elizabeth Ninan, Ms Jutta Franz, Ms Iga Magda, and Ms Aleksandra Posarac of the World Bank for their valuable responses and support.

| All our colleagues from various branches of the DHET for the comments that ensured the report’s true reflection of the post-school education and training system.


CONTENTS

Foreword by the Director General 3

Acknowledgements 5

List of figures 9

List of tables 10

Acronyms and abbreviations 12

Executive summary 13

Summary of findings 13

Demography 13Level of education in the population 14Education and the labour market 14Access to PSET 14Students living with disabilities participating at PSET institutions 15Foreign students participating at PSET institutions 15Quality of the PSET system 15Success of the PSET system 15Efficiency of the PSET system 15Public spending on the PSET system 15Responsiveness of the PSET system 16

1 BACKGROUND 17

1.1 Introduction 18

1.2 Scope of the report and data sources 19

1.3 Overview of the PSET system 19

2 DEMOGRAPHY 22

3 LEVEL OF EDUCATION IN THE SOUTH AFRICAN POPULATION 24

3.1 What is the highest level of educational attainment in the population? 25

3.2 How does educational attainment affect participation in the labour market? 35

3.3 How does HLEA affect wages? 37


4 ACCESS TO POST-SCHOOL EDUCATION AND TRAINING 39

4.1 To what extent is there access to PSET? 40

4.1.1 Enrolment at PSET institutions relative to the population 40

4.1.2 Enrolment at PSET institutions relative to persons who are NEET 40

4.1.3 Access to universities 41

4.1.3.1 GER – Public universities 414.1.3.2 GER – Private universities 424.1.3.3 GER – Public and private universities 434.1.3.4 Enrolment per 100 000 people 444.1.3.5 International comparison of GER 454.1.3.6 Gender Parity Index – Universities 464.1.3.7 International comparison of GPI 47

4.1.4 Access to TVET colleges 48

4.1.4.1 GER – TVET colleges 484.1.4.2 GPI – TVET colleges 50

4.1.5 Access to private colleges 51

4.1.6 Access to CET colleges 52

4.1.6.1 GER – CET colleges 524.1.6.2 GPI – CET colleges 53

4.1.7 Students living with disabilities participating at PSET institutions 53

4.1.8 Foreign nationals participating at PSET institutions 55

4.1.9 Access to SETA-supported workplace-based learning programmes 60

4.1.10 Persons in the population who have access to the internet 60

5 QUALITY OF PSET PROVISIONING 63

5.1 Quality of the PSET system as measured by student:staff ratio and the qualifications of its lecturing staff 64

6 THE SUCCESS OF THE PSET SYSTEM 66

6.1 Graduate outputs in the PSET system 67

6.1.1 University graduation rates 67

6.1.2 TVET college certification rates 68

6.1.3 Private college certification rates 70


7 THE EFFICIENCY OF THE PSET SYSTEM 72

7.1 How efficient is the PSET system as measured by throughput and dropout rates? 73

7.1.1 Throughput rates for public universities 73

7.1.2 TVET colleges 77

7.2 What is the total spending on education? 78

7.2.1 Consolidated government spending on a select number of functions 78

7.2.2 Overall government spending on the schooling system versus the post-schooling system 79

7.2.3 Overall public spending on PSET 81

7.2.4 Real per capita spending on PSET 83

7.2.5 The National Student Financial Aid Scheme 84

8 A RESPONSIVE PSET SYSTEM 86

8.1 How responsive is the PSET system to the labour market? 87

8.1.1 Graduate employment using findings of the TVET tracer study 87

8.1.2 Skills supply and demand mismatches in South Africa 89

8.1.3 Occupations in high demand 90

8.1.4 Are universities and TVET colleges preparing students for occupations that are in high demand in the labour market? 92

8.1.4.1 TVET colleges – Distribution of students’ completion by qualification and programmes 94

8.1.5 Learners completing artisanal learning programmes 96

9 CONCLUSION 97

10 BIBLIOGRAPHY 100

11 APPENDICES 105

Appendix A: Definitions for international comparability 106

ISCED 3: Upper secondary education 106ISCED 4: Post-secondary, non-tertiary education 106ISCED 5: Short-cycle tertiary education 106ISCED 6: Bachelor’s or equivalent level 107ISCED 7: Master’s or equivalent level 107ISCED 8: Doctoral or equivalent level 107Tertiary education (ISCED Levels 5 to 8) 107

Appendix B: Additional tables 108


LIST OF FIGURES

Figure 1: The PSET system 20

Figure 2: Comparing the size and shape of the PSET system in 2019 and 2030 21

Figure 3: Population pyramid for South Africa, 2020 23

Figure 4: Number of doctoral degree graduates per million people per year, 2010–2019 32

Figure 5: Share of population that attained doctoral degrees or equivalent (ISCED 8) (%), for the population aged 25 years and older, 2017–2018 33

Figure 6: Percentage of the population aged 25 years and over with at least a completed bachelor’s or equivalent degree (ISCED 6 or higher), 2017 34

Figure 7: Percentage of the population aged 25–34 years with tertiary education, 2016–2018 35

Figure 8: Working-age population (15–64 years), growth rate versus PSET enrolment rate, 2010 and 2019 40

Figure 9: Total number of students attending PSET institutions (all age groups) compared to NEET youth (15–24-year-olds) in thousands, 2013–2019 41

Figure 10: Enrolment at tertiary education institutions per 100 000 people, 2010–2019 45

Figure 11: GERs for tertiary education by GDP per capita (PPP US$), 2018 45

Figure 12: GPI for gross tertiary enrolment, 2018 47

Figure 13: Percentage of students enrolled at private colleges by gender, 2010–2019 51

Figure 14: Percentage of students enrolled at private colleges by race, 2010–2019 52

Figure 15: Share of academic staff with a PhD in universities, 2010–2019 65

Figure 16: Graduation rate at public universities by gender, 2010–2019 67

Figure 17: Graduation rates at public universities by race, 2010–2019 68

Figure 18: Percentage of consolidated government expenditure across a select number of functions, 2017/18–2023/24 78

Figure 19: Consolidated government spending on education as percentage of total government expenditure and GDP, 2017/18-2023/24 79

Figure 20: Expenditure on education (both schooling and post-schooling) as a percentage of total government expenditure and GDP by country, 2017 80

Figure 21: Expenditure on tertiary education as a percentage of GDP by country, 2017 80

Figure 22: PSET and schooling expenditure as a share of consolidated government expenditure on education, 2017/18–2023/24 81

Figure 23: Government spending on PSET as a percentage of total consolidated government expenditure and GDP, 2017/18–2023/24 82

Figure 24: Per FTE student expenditure at public universities and TVET colleges, 2010/11–2019/20 83

Figure 25: Labour market status of TVET students after completing their qualifications in 2017 88

Figure 26: Labour market status of TVET college students after completing their qualifications in 2017 by gender 88

Figure 27: Qualification and field-of-study mismatch by country (2020 for South Africa, 2018 for most other countries) 90

Figure 28: Enrolment in tertiary education per 100 000 people, by race, 2010–2019 108

Figure 29: Public expenditure on tertiary education per student as a percentage of GDP per capita by country, 2015 109


LIST OF TABLES

Table 1: Number and share of persons in the population aged 25–64 years by highest level of educational attainment, 2010 and 2020 26

Table 2: Number and share of persons in the population aged 25–64 years by highest level of educational attainment and gender, 2010 and 2020 27

Table 3: Number and share of persons in the population aged 25–64 years by highest level of educational attainment and race, 2010 and 2020 29

Table 4: Share of persons in the population by highest level of educational attainment and age group, 2010 and 2020 31

Table 5: Number and share of persons in the population aged 25–64 years by highest level of educational attainment and employment status, Q3 2010, Q3 2019, and Q3 2020 36

Table 6: Unemployment rates of 25–34-year-olds by highest level of educational attainment, as a percentage, 2019 37

Table 7: Median wages per month by race, gender, and highest level of educational attainment, 2019 38

Table 8: Public universities: Total headcounts and GER by race, 2010–2019 42

Table 9: Private universities: Total headcounts and GER by race, 2011–2019 43

Table 10: Public and private universities: Total headcounts and GER by race, 2011–2019 44

Table 11: Trends in GPI, 2011–2019 46

Table 12: Public and private universities: GPI by race, 2011–2019 46

Table 13: Public universities: GPI by race, 2010–2019 47

Table 14: TVET colleges: Total enrolment and GER by race, 2010–2019 49

Table 15: TVET colleges: GER by race and gender, 2010–2019 (%) 50

Table 16: TVET college: GPI by race, 2010–2019 50

Table 17: CET colleges: GER by gender, 2010–2019 (%) 53

Table 18: CET colleges: Trend in GPI, 2010–2019 53

Table 19: Enrolment of students living with disabilities at PSET institutions, 2016–2019 54

Table 20: Number and share of the population for persons and students living with disabilities, 2019 54

Table 21: Number of foreign students enrolled at South African PSET institutions by type of institution, 2019 55

Table 22: Number and share of foreign students enrolled at public universities by country, 2016–2019 56

Table 23: Number and share of foreign students enrolled at public HEIs by attendance mode and country, 2016–2019 57

Table 24: Number and share of foreign students enrolled at private universities by country, 2016–2019 58

Table 25: Number and share of foreign students enrolled at TVET colleges by country, 2016–2019 59

Table 26: Number of workers and unemployed persons registered and certificated at SETA-supported learning programmes by programme type, 2011/12–2019/20 60

Table 27: Percentage of the population who have access to the internet by age and gender, 2014–2019 60


Table 28: Percentage of the population who have access to mobile phones, by gender and age, 2014–2019 62

Table 29: Public universities: FTE students to FTE staff ratio, 2010–2019 65

Table 30: Examination candidates, passes, and certification rates for N3 at TVET colleges, 2013–2019 69

Table 31: Examination candidates, passes, and certification rates for N6 at TVET colleges, 2013–2019 69

Table 32: Examination candidates, passes, and certification rates for NC(V) Level 4 at TVET colleges, 2013–2019 70

Table 33: Examination candidates, passes, and certification rates for Report 191 N3 at private colleges, 2013–2019 70

Table 34: Examination candidates, passes, and certification rates for N6 at private colleges, 2013–2019 71

Table 35: Examination candidates, passes, and certification rates for NC(V) Level 4 at private colleges, 2013–2019 71

Table 36: Throughput rates for first-time-entering student cohort in three-year degree programmes through contact and distance learning modes, 2009–2016 intake years 74

Table 37: Throughput rates by intake year of first-time-entering students in three-year undergraduate degree programmes (contact mode only), 2009–2016 intake years 74

Table 38: Throughput rates by intake year of first-time-entering students in three-year undergraduate degree programmes (distance mode only), 2009–2016 intake years 75

Table 39: Dropout rates by intake year of first-time-entering students in three-year undergraduate degree programmes (contact mode only), 2009–2017 intake years 76

Table 40: Dropout rates by intake year of first-time-entering students in three-year undergraduate degree programmes (distance mode only), 2009–2017 intake years 76

Table 41: Overall throughput rate of NC(V) Level 2 students enrolled at TVET colleges in 2016 77

Table 42: Throughput rate by gender, 2016–2018 77

Table 43: Government spending, including skills levy, on PSET (R million), 2017/18–2019/20 82

Table 44: Distribution of the skills development levy, 2011/12–2019/20 84

Table 45: Total and per student NSFAS allocation to public universities and TVET colleges 2011/12–2019/20 85

Table 46: Share of employed persons aged 16–64 years by qualification and field-of-study mismatch, 2019 and 2020 89

Table 47: Occupations in high demand 90

Table 48: Public HEIs: Enrolment in major field of study by gender, 2010–2019 92

Table 49: Public HEIs: Graduates by major field of study by gender, 2010–2019 92

Table 50: Percentage distribution of students who completed NC(V) Level 4 qualification by programme and gender, 2019 94

Table 51: Percentage distribution of students who completed N6 qualification by programme and gender, 2019 95

Table 52: Percentage of learners completing artisanal learning programmes by trade and gender, 2017/18–2019/20 96

Table 53: Number of students enrolled at PSET institutions compared to youth aged 15–24 years who are not in education, employment, or training, 2013–2019 108

Table 54: Private universities: GPI by race, 2015–2019 109


ACRONYMS AND ABBREVIATIONS

AU African Union

CET Community education and training

DHET Department of Higher Education and Training

DPME Department of Planning, Monitoring and Evaluation

ENE Estimates of national expenditure

FTE Full-time equivalent

GDP Gross domestic product

GER Gross Enrolment Ratio

GPI Gender Parity Index

HEIs Higher education institutions

HLEA Highest level of educational attainment

HRDC Human Resource Development Council

ISCED International Standard Classification of Education

n/a Not applicable or not available

NAMB National Artisan Moderation Body

NATED National Technical Education Diploma

NC(V) National Certificate (Vocational)

NSA National Skills Authority

NSC National Senior Certificate

NDP National Development Plan

NEET Not in employment, education, or training

NSF National Skills Fund

NSFAS National Student Financial Aid Scheme

OECD Organisation for Economic Co-operation and Development

PSET Post-school education and training

QCTO Quality Council for Trades and Occupations

QLFS Quarterly Labour Force Survey

SADC Southern African Development Community

SAQA South African Qualifications Authority

SDPs Skills development providers

SET Science, engineering, and technology

SETA Sector Education and Training Authority

Stats SA Statistics South Africa

TVET Technical and vocational education and training

UIS UNESCO Institute for Statistics

UN United Nations

UNESCO United Nations Educational, Scientific and Cultural Organization

WBL Workplace-based learning


EXECUTIVE SUMMARY

This report provides an overview of the macro-indicator trends in the South African post-school education and training (PSET) system. It tracks the progress made between 2010 and 2019 against key systematic goals aimed at achieving an expanded, responsive, quality, efficient, and successful PSET system, as envisaged in the White Paper on Post-School Education and Training.

Many of the indicators selected for this report are used internationally to monitor global educational goals and how countries are progressing in the attainment of educational outcomes. This report is guided by the Global Monitoring Report produced by the United Nations Educational, Scientific and Cultural Organization (UNESCO) and the Education at a Glance report produced by the Organisation for Economic Co-operation and Development (OECD). These projects track educational progress across countries, allowing them to benchmark and compare their performances against each other.

By compiling macro-indicators in one place, this Post-School Education and Training Monitor: Macro-Indicator Trends report can address the needs of a range of users, from government workers to researchers, who require data for further analysis. The data presented provide evidence for improvements in the design and implementation of educational policies, alert policymakers to prevailing problems, and hint at some of the causes of these problems. The report also serves as a source document for reporting on the progress made on national and international commitments, such as South Africa’s National Development Plan (NDP), the African Union’s Continental Education Strategy, and the United Nations’ Sustainable Development Goals.

The report focuses on the five key subsectors of the PSET system: namely, public and private universities, technical and vocational education and training (TVET) colleges, community education and training (CET) colleges, private colleges, and Sectoral Education and Training Authorities (SETAs).

SUMMARY OF FINDINGS

Demography | Demographic changes have a direct bearing on the PSET system, since student flows determine the

resources required to provide educational services. In South Africa, the number of youth within the 15–19 and 20–24 age categories, which are the PSET-entering age categories, is smaller than the number of youth in the age group 25–29 who have recently left the PSET system.

| However, the pipeline leading to PSET has been producing increasing numbers of school leavers with the qualifications required to enter PSET, indicating that demand for PSET opportunities will continue increasing in the coming years, as the proportion of PSET age groups that qualify to enter PSET continues to rise.


Level of education in the population | More adults1 are completing secondary education in South Africa today than a decade ago. In 2020,

32.1 percent of adults had completed secondary schooling, thus pointing to a potential increase in the demand for PSET and the consequent need for a pronounced expansion of the PSET system.

| Although the education levels of the South African population have increased significantly over the past decade, only 6 percent of adults have a degree. In this regard, South Africa fares very poorly in comparison to other middle-income countries, thereby compromising its international economic competitiveness.

| Among those South African adults who have degrees, many more females than males are degree-holders (52.3 percent versus 47.7 percent). Predictably, less black African people have degrees compared to other race groups.

| Although the number of doctoral graduates in the population has increased consistently and significantly over the past decade, reaching 59 graduates per million in 2019, given the current trends it is unlikely that the NDP target of more than 100 doctoral graduates per million of the population will be reached by 2030.

| Similarly, compared to European nations, the share of South Africa’s adult population that had attained a doctoral qualification in 2018 was considerably low, at 0.2 percent.

Education and the labour market | Over the last decade, the highest level of educational attainment among South African adults

correlated with higher employment rates. | PSET qualifications provide good returns to individuals. They improve their chances of attaining

employment and accessing better wages. The median wages of workers with a degree are more than six times as large as those of workers without a matric qualification. While the gender gap in median wages favours males over females at all levels of education, this gap is proportionally smallest among workers who are more educated. A similar pattern applies in terms of race.

Access to PSET | Access to universities and TVET colleges has grown substantially over the past 10 years. However,

while universities are likely to meet the NDP enrolment target of 1.62 million by 2030 (if student enrolment increases annually at the same average rate as that obtained over the past decade), the same does not apply to TVET colleges.

| Despite significant growth in enrolment rates at universities, university participation rates in South Africa remain well below those of many other countries.

| Although enrolments at TVET colleges almost doubled from 2010 to 2019, the average annual growth rate recorded in that period needs to double per annum from 2019 to 2030 for the NDP enrolment target to be realised.

| CET enrolment numbers are still far below the NDP 2030 target and will have to more than triple in the remaining nine years for the target to be met.

| Access to PSET favours females over males, with the Gender Parity Index for PSET being among the highest in the world.

| Although black African students comprise over 80 percent of total student enrolment at public universities, and although the participation rates of black African students have increased significantly over the past decade, racial inequality continues to plague the PSET system. The Gross Enrolment Ratio for black African students at public universities sits at 20 percent, while that of white students sits at about 49 percent.

1 For the purpose of this document, ‘adult’ refers to the 25–64 age group within the South African population.


Students living with disabilities participating at PSET institutions | From 2016 to 2019, the proportion of students living with disabilities participating at PSET institutions

remained consistently low, ranging between 0.6 percent and 0.8 percent.

Foreign students participating at PSET institutions | In 2019, approximately 80 000 foreign students enrolled at South African PSET institutions,

constituting about 4.1 percent of all students enrolled at these institutions. The majority of these students were nationals from the Southern African Development Community region.

Quality of the PSET system | The quality of education provided at universities is at risk in terms of two key measures of quality:

lecturer qualifications and student:staff ratios. Despite significant gains made over the past 10 years, currently less than 50 percent of university academic staff hold PhD degrees. The NDP target of 75 percent is therefore unlikely to be reached by 2030.

| The average student:staff ratio at universities has been increasing over the past few years, thereby compromising not only the quality of education but also the capacity of universities to produce research outputs.

Success of the PSET system | Graduation rates at public universities grew in the period under review for all race groups and for

both females and males. However, more female than male students graduated, and black African students were less likely to graduate relative to students in other race groups.

| At TVET colleges, certification rates also increased significantly for all programmes. However, the throughput rate for students enrolled in NC(V) programmes remains far below the target of 75 percent set by the NDP. This contradiction between high certification rates and poor throughput rates could be attributed to high levels of student dropouts.

Efficiency of the PSET system | The university sector is becoming more efficient in terms of its improved throughput rates and

declining dropout rates. However, it still takes too long for a significant proportion of students to complete their degrees, and the percentage of students who drop out before the completion of their degrees remains fairly high.

| The disturbingly low throughput rate of NC(V) students at TVET colleges is cause for great concern. Less than 10 percent of all students enrolled in the TVET NC(V) Level 2 programme in 2016 completed this qualification within the expected time frame.2 The low throughput rates are likely the result of a combination of high levels of repetition and dropout. The reasons for this phenomenon need to be interrogated further so that appropriate solutions can be found to address the challenge.

Public spending on the PSET system | By UNESCO standards, South Africa continues to spend a large share of its national budget and

wealth on education (both schooling and post-schooling). Spending on education as a proportion of overall government expenditure (22.7 percent in 2019/20) and GDP (7.2 percent in 2019/20) far exceeds the benchmarks set by UNESCO, which recommends allocating 15–20 percent of public spending to education and 4–6 percent of GDP to education. Government expenditure on total education even exceeded that of several other Brazil, Russia, India, China, and South Africa (BRICS) coalition countries, as well as the average for OECD countries.

2 Since data for throughput rates at TVET colleges were only available for one year, a trend in this regard cannot be observed.


| However, government expenditure on tertiary education in particular does not compare in a similar manner. South Africa spends significantly less on tertiary education than most other countries. Moreover, the nation’s spend of 0.9 percent of its GDP on tertiary education in 2017 falls short of the 1% recommended by the Commission of Inquiry into Higher Education.

| The South African government spent more on the schooling system (70 percent in 2019/20) than on the post-schooling system (30 percent in 2019/20). This fact is not surprising given that student enrolment in schools is over 12 million, almost six times higher than enrolment in the PSET system.

| The government spent more on public universities (70 percent) than it did on TVET (10.9 percent) and CET (1.8 percent) colleges in 2019/20. This disparity is expected, since universities currently have the largest enrolment among these institution types, while CET colleges have the lowest enrolment, and student per capita costs at universities are generally higher than those at other PSET institutions.

| In 2018, the cost of training a full-time university student for a year was R88 600. By contrast, the cost per full-time-equivalent TVET student was only R44 000 in the same year. This difference is unsurprising given the different kinds of programmes offered by the two types of institutions, as well as the rapid and massive expansion of enrolment at TVET colleges in the absence of concomitant budget increases.

| The National Student Financial Aid Scheme (NSFAS) has played an increasingly important role in supporting students from poorer backgrounds attending university and TVET colleges, and this role is likely to expand further. In 2019, over one-third of university students, and just over half of TVET college students, benefitted from a NSFAS bursary. When taking into account the differences in TVET college and university enrolments, though, it is logical that more than half of all NSFAS beneficiaries are from universities.

Responsiveness of the PSET system | As Rogan and Papier (2020) conclude, many TVET college graduates do not get absorbed into the

labour market. Rogan and Papier’s DHET tracer study found that, while more than half of TVET college graduates were involved in some kind of employment or studying, the balance were not working. The co-existence of high levels of unemployment in the country with significant skills shortages suggests that more needs to be done to ensure that the programmes offered in the PSET system are responsive to the needs of the economy and of the labour market.

| The report observes that the extent of mismatches between education and the labour market in South Africa is higher than in many other countries. Although this problem can only be partly attributed to the PSET system not providing programmes that are responsive to the needs of the labour market, it remains imperative that the PSET system continuously identify, develop, and deliver programmes that are flexible and relevant to the ever-changing needs of the economy and the labour market.

| Labour market research has consistently pointed to the need for more skills in the science, engineering, and technology (SET) fields of study. It is therefore encouraging that the number of students enrolling in and graduating from SET programmes is increasing every year and that this number has remained consistently high compared to other fields of study. Although female enrolments continue to be in the majority in all major fields of study except SET, the gender gap in SET enrolments is narrowing.

| The number of learners completing artisanal learning programmes required for occupations in high demand is considerably low, which is a cause for concern.

Background

1


1.1 Introduction

The Department of Higher Education and Training (DHET) recognises the importance of using robust and reliable data, information, and research to support decision-making on the post-school education and training (PSET) system. This report, which the DHET publishes biennially, contributes to the evidence required by the department to aid, among other things, its policy, planning, and resource allocation processes. As suggested by the subtitle, this report tracks high-level quantitative indicators to monitor the performance of the PSET system. More specifically, the Post-School Education and Training Monitor: Macro-Indicator Trends report provides an overview of macro trends in the South African PSET system and monitors the progress made from 2010 to 2019 against key goals envisioned for PSET, as reflected in the White Paper for Post-School Education and Training and the government’s National Development Plan (NDP) while also serving as a summary of the findings of the past decade.

Many of the indicators selected for this report are also used internationally to monitor global educational goals. These indicators are modelled after practices adopted by various international institutions such as the United Nations Educational, Scientific and Cultural Organization (UNESCO) and the Organisation for Economic Co-operation and Development (OECD). UNESCO’s Global Monitoring Report and the OECD’s Education at a Glance are examples of highly rated reports on education indicators that address the needs of a range of users, from government workers to researchers, who require data for further analysis. Such reports are also used by the general public to monitor how their countries are progressing in educational outcomes in relation to other countries. The indicators used in this report are based on the following PSET system goals:

1. Expanded access to PSET opportunities2. Improved quality of PSET provisioning3. Improved success of the PSET system4. Improved efficiency of the PSET system to ensure the resources are used optimally5. Enhanced responsiveness of the PSET system

It is important to note that the goals stated above are deeply interdependent and interconnected and have been stated separately for ease of reporting. In addition, equity and transformation are considered cross-cutting goals that underpin all other goals in the system. Therefore, in monitoring the performance and progress made against the abovementioned goals of the PSET system, this report will also provide an analysis of the proportional representation of historically and currently disadvantaged populations in all staff, student, and graduate components of the PSET system, in terms of age, race, gender, and disability, where the data are available.

By compiling these data in one place, the report provides suggestions for improvements in the design and implementation of educational policies, alerts policy makers to prevailing problems, and hints at some of the causes of the problems. In addition, this indicator report allows the tracking and benchmarking of educational progress against that of international comparator countries. It also serves as a source document for reporting on the progress made on national and international commitments, such as the NDP, the Department of Planning, Monitoring and Evaluation’s (DPME) development indicators, the African Union’s (AU) Continental Education Strategy and the United Nations (UN) Sustainable Development Goals.

This is the second report on this topic to be produced and published by the DHET. The first report was published in 2019.

1 | BACKGROUND | 19

1.2 Scope of the report and data sources

Given that this report intends to portray a macro picture of PSET system trends, only quantitative indicators were selected for analysis. It is hoped that researchers will draw on these macro trends to further interrogate the drivers and explanations behind the trends. The report monitors progress made by the PSET sector in relation to its goals for the period 2010 to 2019. The period selected for this report is primarily a reflection of the availability of data and statistics. Where 2020 data were available, these were used, especially to take into account the impact of COVID-19 on the PSET system. Most of the data used in this report were sourced from the DHET Statistics on Post-School Education and Training in South Africa reports. Additional information was sourced from Statistics South Africa’s (Stats SA) Quarterly Labour Force Survey (QLFS), mid-year population estimates, and the General Household Survey, the South African Reserve Bank, the World Bank, the UNESCO Institute for Statistics (UIS), the OECD national accounts data, and the National Treasury Estimates of National Expenditure (ENE).

1.3 Overview of the PSET system

The PSET system comprises all education and training provision for those who have completed primary and secondary schooling, those who did not complete their schooling, and adults who never attended school. It is the vision of the DHET to lead PSET for economic growth and to provide national strategic leadership in support of an integrated PSET system, for societal development and an improved quality of life for all South Africans.

Figure 1 sets out the current structure of the PSET system, which comprises a range of institutions. Funding flows within the system differ depending on the type of institution involved. For example, while public education and training institutions are funded directly from taxes, skills levy organisations are primarily funded by private sector contributions (via the National Skills Fund [NSF]), with only some funds channelled through the DHET.


FIGURE 1: The PSET system

Education and training institutions

National Institute for Humanities and

Social Sciences

National Student Financial Aid Scheme

Human Resource Development Council

(HRDC)

HRDC Secretariat5Qualifications and quality assurance

bodies

Quality Council for Trades and

Occupations (QCTO)

Approved workplaces for workplace-based learning (WBL)

Notes: 1. The Skills Development Act makes

provision for SDPs.2. NAMB is envisaged to be part of QCTO in

the future.3. The DHET manages the personnel budget

for TVET and CET colleges (since their staff are DHET employees); however, universities employ their own staff, and therefore manage their own personnel and other budgets.

4. The NSA Secretariat is located inside the Department and services the NSA.

5. The HRDC Secretariat is located within the DHET and provides services to the HRDC.

Education and training institutions/

institutes of other government departments

Private skills development

providers (SDPs)1

PrivatecollegesPrivate HEIsCET

colleges3TVET

colleges3Universities(public HEIs)

National Artisan Moderation Body

(NAMB):2

INDLELA

Trade test centres

Sector Education and Training Authorities

National Skills Authority (NSA)

NSA Secretariat4

National Skills Fund (NSF)

Council on Higher Education

South African Qualifications

Authority(SAQA)

UMALUSI

Other support organisations

DEPARTMENT OF HIGHER

EDUCATION AND TRAINING

Skills levy organisations

Professional bodies

LEGEND:

Organisations that are located within the DHET.

Organisations that are located outside of the DHET, and that receive funds from the DHET sourced from the fiscus and the skills levy.

Organisations that are located outside of the DHET, that do not receive funds from the DHET, but for which the DHET has certain legislative functions.

Organisations that do not receive funds from the DHET, nor does the DHET have legislative functions in relation to these organisations. However, DHET entitities may have certain legislative responsibilities in relation to these organisations (for example, QCs quality assure formal programmes offered by other government departments, SAQA registers professional bodies, and QCTO accredits workplaces for WBL).

Source: DHET (2019a)

1 | BACKGROUND | 21

The focus of this report is on the following five key subsectors: public and private universities (also referred to as higher education institutions [HEIs]), technical and vocational education and training (TVET) colleges, community education and training (CET) colleges, private colleges, and Sector Education and Training Authorities (SETAs).

Figure 2 compares the size and shape of the PSET system and component sectors in 2019 along with their expected size and shape in 2030, with the differences reflecting the intended impact of the white paper. Achieving the white paper’s envisaged growth in enrolments across the PSET system to 5.4 million students by 2030 requires growth in both public and private PSET provision.

As depicted by Figure 2, the total number of enrolments in the university education, TVET, and CET sectors of the PSET system stood at 2 129 522 students in 2019. The largest share of these enrolments was in the university sector at 60.3 percent (1 283 890), while 31.6 percent (673 490) and 8.1 percent (172 142) were enrolments in the TVET and CET sectors, respectively. Out of the total 1 283 890 enrolments in the university sector, public universities accounted for the bulk proportion at 83.7 percent (1 074 912), and private universities accounted for the remaining 16.3 percent (208 978) of the students.

Based on the white paper on the topic (DHET, 2013a), the size and composition of enrolments in the system are envisaged to be transformed by 2030. The white paper describes the intent to both strengthen and expand the TVET sector and for the system to have a total of 5 444 541 enrolments, out of which the largest share of 45.9 percent (2.5 million) should be in the TVET sector, while the university education and CET college sectors should account for 29.4 percent (1.6 million) and 18.4% (1 million), respectively. The remaining 6.3 percent (344 541) of the enrolments should be at SETA-supported programmes. Out of 1.6 million enrolments expected in the university education sector, 87.5 percent (1.4 million) should be at public universities, while the remaining 12.5 percent (200 000) should be at private universities.

FIGURE 2: Comparing the size and shape of the PSET system in 2019 and 2030

2019

University education enrolment1 283 890 (54.6%)

CET college enrolment172 142 (7.3%)

TVET enrolment673 490 (28.6%)

Enrolment in SETA-supported programmes

222 210 (9.4%)

2030

TVET enrolment2 500 000 (45.9%)

CET college enrolment1 000 000

(18.4%)

University education enrolment

1 600 000 (29.4%)

Enrolment in SETA-supported programmes

344 541 (6.3%)

Public: 1 074 912 (83.7%)

Private: 208 978 (16.3%)

Private colleges:151 136

TVET colleges and private colleges to

be decided at operational level

Public: 1 400 000 (87.5%)Private: 200 000 (12.5%)

Source: DHET White Paper for Post-School Education and Training (2013a); DHET Statistics on Post-School Education and Training in South Africa (2019b)

Demography

2

2 | DEMOGRAPHY | 23

Demographic changes have a direct bearing on the PSET system, since student flows determine the resources required to provide educational services.

South Africa’s mid-year population estimate for 2020 revealed that the population grew by 7.8 percent over the 2015–2020 period compared to a slightly higher 8.0 percent in the previous five-year period, 2010–2015. The population pyramid depicted in Figure 3 shows a very large cohort in the age category 25–29. This category primarily denotes the youth who have recently left the PSET system, depending on the type and number of years it takes for them to complete the programmes they might have enrolled in. Figure 3 shows that the age categories 15–19 and 20–24 (the PSET entering age categories) are smaller than the succeeding age categories, 25–29 and 30–34, implying a slight reduction in the PSET entering-age categories. On the other hand, the pipeline leading to PSET has been producing increasing numbers of school leavers with the qualifications to enter PSET. For instance, despite COVID-19, the number of matriculants who passed the 2020 National Senior Certificate (NSC) examinations increased by roughly 31 000 to 440 702, a 7.5 percent expansion, while the 210 820 learners who obtained bachelor’s passes are almost 25 000 higher than in 2019, a 13.3 percent increase (Department of Basic Education, 2021). This growth in numbers illustrates that the demand for PSET opportunities will continue to increase in the coming years, as a proportion of the PSET age groups that qualify to enter PSET continue to rise.

FIGURE 3: Population pyramid for South Africa, 2020

80+

75–79

70–74

65–69

60–64

55–59

50–54

45–49

40–44

35–39

30–34

25–29

20–24

15–19

10–14

5–9

0–4

3 2 1 0 1 2 34 4

Millions

Female Male

Source: Stats SA mid-year population estimates (2020)

Level of Education in the

South African Population

3Level of

Education in the South African

Population

3 | LEVEL OF EDUCATION IN THE SOUTH AFRICAN POPULATION | 25

3.1 What is the highest level of educational attainment in the population?

The South African government has always expressed its commitment to the development of a skilled and capable workforce, as reflected in its previous Medium Term Strategic Framework (DPME, 2014). A frequently used proxy measure of the skills and capability of South Africa’s workforce is its highest level of educational attainment (HLEA). The HLEA measure is often used internationally to compare the education levels of persons in terms of their race, gender, age, and employment status as well as across various countries. Such comparisons serve as a barometer for how countries perform in terms of their education systems. Most importantly, however, the comparisons also serve as indicators that investors draw on to assess the investment potential of a chosen country (World Economic Forum, 2019).

Table 1 shows that, today, significantly more South African adults have primary and secondary education as their HLEA compared to a decade ago. The share of the population aged 25–64 years who have secondary education (Grade 12 and equivalent) as their HLEA increased from 24.7 percent in 2010 to 32.1 percent in 2020. However, despite some progress, only 6.0 percent of South African adults had a degree as their HLEA in 2020.


TABLE 1: Number and share of persons in the population aged 25–64 years by highest level of educational attainment, 2010 and 2020

HIGHEST LEVEL OF EDUCATIONAL ATTAINMENTQ3 2010 Q3 2020

THOUSANDS % THOUSANDS %

No schooling 1 255 5.4% 639 2.2%

Less than primary schooling 2 948 12.8% 2 031 7.0%

Primary schooling 1 410 6.1% 1 156 4.0%

Some secondary schooling 8 524 36.9% 11 119 38.5%

Secondary (Grade 12 or equivalent) schooling 5 708 24.7% 9 281 32.1%

Certificate 546 2.4% 991 3.4%

Diploma 1 274 5.5% 1 737 6.0%

Degree 1 112 4.8% 1 730 6.0%

Other 305 1.3% 224 0.8%

Total 23 082 100.0% 28 908 100.0%

Source: Stats SA QLFS 2010–2020 (2021)

Notes:1. No schooling includes Grade R/0.2. Less than primary schooling includes the following categories: Grade 1/Sub A, Grade 2/Sub B, Grade 3/Standard 1/

AET 1 (Kha Ri Gude, SANLI), Grade 4/Standard 2, Grade 5/Standard 3/AET 2, Grade 6/Standard 4.3. Primary as HLEA refers to Grade 7/Standard 5/AET 3.4. Some secondary schooling as HLEA includes the following categories: Grade 8/Standard 6/Form 1, Grade 9/Standard 7/

Form 2/AET 4, Grade 10/Standard 8/Form 3, Grade 11/Standard 9/Form 4, NTC l/N1/NIC/(v) Level 2, NTC II/N2/NIC/(v) Level 3, a certificate with less than Grade 12/Standard 10, and a diploma with less than Grade 12/Standard 10.

5. Secondary schooling (Grade 12 or equivalent) as HLEA refers to the following categories: Grade 12/Standard 10/ Form 5/Matric (no exemption), Grade 12/Standard 10/Form 5/Matric (exemption or bachelor’s pass), and NTC III/N3/ NIC/(v) Level 4.

6. Certificate refers to the following categories: N4/NTC 4, N5/NTC 5, N6/NTC 6, and a certificate with Grade 12/Standard 10.7. Diploma refers to the following categories: A diploma with Grade 12/Standard 10 and a higher diploma. 8. Degree refers to the following categories: A post-higher diploma (master’s or doctoral diploma), a bachelor’s degree,

a postgraduate diploma, an honours degree, and a higher degree (master’s or PhD).9. Other includes the following categories: Do not know.

Table 2 shows gendered differences in HLEAs. In South Africa, more male persons have secondary education as their HLEA than female persons. 50.8 percent of males and 49.2 percent of females attained this level in 2020. In contrast, more female persons (52.3 percent) had a degree as their HLEA than male persons (47.7 percent) in 2020.


TABL

E 2:

Num

ber a

nd sh

are

of p

erso

ns in

the

popu

latio

n ag

ed 2

5–64

year

s by

high

est l

evel

of e

duca

tiona

l atta

inm

ent a

nd g

ende

r, 20

10 a

nd 2

020

HIG

HES

T LE

VEL

OF

ED

UCAT

ION

AL A

TTAI

NM

ENT

Q3

2010

Q3

2020

MAL

EFE

MAL

ETO

TAL

MAL

EFE

MAL

ETO

TAL

THO

USAN

DS

%TH

OUS

AND

S%

THO

USAN

DS

%TH

OUS

AND

S%

No sc

hool

ing

496

39.5

%76

060

.5%

1256

277

43.3

%36

256

.7%

639

Less

than

prim

ary

scho

olin

g1

410

47.8

%1

538

52.2

%2

948

1 01

650

.0%

1 01

550

.0%

2 03

1

Prim

ary

scho

olin

g64

545

.7%

765

54.3

%1

410

558

48.3

%59

751

.7%

1 15

5

Som

e se

cond

ary

scho

olin

g4

082

47.9

%4

442

52.1

%8

524

5 50

249

.5%

5 61

750

.5%

11 1

19

Seco

ndar

y (G

rade

12

or e

quiv

alen

t) sc

hool

ing

2 87

250

.3%

2 83

649

.7%

5 70

84

718

50.8

%4

563

49.2

%9

281

Cert

ifica

te26

849

.2%

277

50.8

%54

548

348

.7%

508

51.3

%99

1

Dipl

oma

561

44.0

%71

456

.0%

1 27

575

343

.4%

984

56.6

%1

737

Degr

ee60

354

.2%

509

45.8

%1

112

826

47.7

%90

452

.3%

1 73

0

Oth

er18

259

.7%

123

40.3

%30

512

857

.1%

9642

.9%

224

Sour

ce: S

tats

SA Q

LFS 2

010–

2020

(202

1)

Note

s:1.

No

scho

olin

g in

clude

s Gra

de R

/0.

2.

Less

than

prim

ary s

choo

ling

inclu

des t

he fo

llow

ing

cate

gorie

s: Gr

ade

1/Su

b A,

Gra

de 2

/Sub

B, G

rade

3/S

tand

ard

1/AE

T 1

(Kha

Ri G

ude,

SANL

I), G

rade

4/S

tand

ard

2, G

rade

5/S

tand

ard

3/AE

T 2,

Gr

ade

6/St

anda

rd 4

.3.

Pr

imar

y as H

LEA

refe

rs to

Gra

de 7

/Sta

ndar

d 5/

AET

3.4.

So

me

seco

ndar

y sch

oolin

g as

HLE

A in

clude

s the

follo

win

g ca

tego

ries:

Grad

e 8/

Stan

dard

6/F

orm

1, G

rade

9/S

tand

ard

7/Fo

rm 2

/AET

4, G

rade

10/

Stan

dard

8/F

orm

3, G

rade

11/

Stan

dard

9/F

orm

4,

NTC

l/N1/

NIC/

(v) L

evel

2, N

TC II/

N2/N

IC/(v

) Lev

el 3

, a ce

rtific

ate

with

less

than

Gra

de 1

2/St

anda

rd 1

0, an

d a d

iplo

ma w

ith le

ss th

an G

rade

12/

Stan

dard

10.

5.

Seco

ndar

y sch

oolin

g (G

rade

12

or e

quiva

lent

) as H

LEA

refe

rs to

the

follo

win

g ca

tego

ries:

Grad

e 12

/Sta

ndar

d 10

/For

m 5

/Mat

ric (n

o ex

empt

ion)

, Gra

de 1

2/St

anda

rd 1

0/Fo

rm 5

/Mat

ric (e

xem

ptio

n or

ba

chel

or’s

pass

), an

d NT

C III/

N3/N

IC/(v

) Lev

el 4

.6.

Ce

rtific

ate

refe

rs to

the

follo

win

g ca

tego

ries:

N4/N

TC 4

, N5/

NTC

5, N

6/NT

C 6,

and

a cer

tifica

te w

ith G

rade

12/

Stan

dard

10.

7.

Dipl

oma r

efer

s to

the

follo

win

g ca

tego

ries:

A di

plom

a with

Gra

de 1

2/St

anda

rd 1

0 an

d a h

ighe

r dip

lom

a. 8.

De

gree

refe

rs to

the

follo

win

g ca

tego

ries:

A po

st-hi

gher

dip

lom

a (m

aste

r’s o

r doc

tora

l dip

lom

a), a

bac

helo

r’s d

egre

e, a p

ostg

radu

ate

dipl

oma,

an h

onou

rs de

gree

, and

a hi

gher

deg

ree

(mas

ter’s

or P

hD).

9.

Othe

r inc

lude

s the

follo

win

g ca

tego

ries:

Do n

ot kn

ow.


Table 3 shows the levels of educational attainment by race from 2010 to 2020. Black African and coloured race groups had the largest proportions of persons who have had some secondary schooling as their HLEA. Meanwhile, the largest proportions of Indian/Asian and white people had secondary education as their HLEA.

In general, there were improvements in the share of persons with diploma and degree qualifications within each of the race groups. In the black African population, the proportion of persons with a diploma as their HLEA increased by 0.7 percentage points from 4.2 percent in 2010 to 4.9 percent in 2020. Similarly, the analogous share of white persons improved slightly by 1.2 percentage points from 14.9 percent in 2010 to 16.1 percent in 2020.

Although the proportion of black African adults who have a degree as their HLEA has almost doubled over the past decade, only 4.1 percent had a degree in 2020, compared to 23.4 percent of white adults who had a degree in 2020 (up from 21.0 percent in 2010).


TABL

E 3:

Num

ber a

nd sh

are

of p

erso

ns in

the

popu

latio

n ag

ed 2

5–64

year

s by

high

est l

evel

of e

duca

tiona

l atta

inm

ent a

nd ra

ce, 2

010

and

2020

HIG

HES

T LE

VEL

OF

EDUC

ATIO

NAL

AT

TAIN

MEN

T

BLAC

K AF

RICA

NCO

LOUR

ED

IND

IAN/

ASIA

NW

HIT

E

Q3

2010

Q3

2020

Q3

2010

Q3

2020

Q3

2010

Q3

2020

Q3

2010

Q3

2020

THOUSANDS

%

THOUSANDS

%

THOUSANDS

%

THOUSANDS

%

THOUSANDS

%

THOUSANDS

%

THOUSANDS

%

THOUSANDS

%

No sc

hool

ing

1 18

9 6.

8%59

8 2.

6%59

2.

6%33

1.

3%4

0.6%

6 0.

8%3

0.1%

2 0.

1%

Less

than

prim

ary

scho

olin

g2

656

15.1

%1

831

7.9%

257

11.4

%18

8 7.

1%30

4.

3%6

0.7%

4 0.

2%7

0.3%

Prim

ary

scho

olin

g1

162

6.6%

972

4.2%

214

9.4%

159

6.0%

22

3.1%

12

1.5%

13

0.5%

13

0.6%

Som

e se

cond

ary

scho

olin

g 6

917

39.4

%9

554

41.4

%95

3 42

.0%

1,11

4 42

.4%

196

28.2

%17

5 21

.2%

457

17.8

%27

5 11

.7%

Seco

ndar

y (G

rade

12

or

equi

vale

nt) s

choo

ling

3 83

0 21

.8%

7 10

3 30

.8%

542

23.9

%79

2 30

.1%

294

42.2

%39

3 47

.6%

1 04

2 40

.5%

994

42.1

%

Cert

ifica

te39

9 2.

3%77

3 3.

3%33

1.

4%75

2.

9%9

1.3%

25

3.1%

105

4.1%

117

5.0%

Dipl

oma

742

4.2%

1 14

1 4.

9%98

4.

3%13

8 5.

2%50

7.

1%79

9.

5%38

4 14

.9%

380

16.1

%

Degr

ee41

6 2.

4%93

9 4.

1%72

3.

2%11

4 4.

3%84

12

%12

7 15

.4%

540

21.0

%55

1 23

.4%

Oth

er23

3 1.

3%18

5 0.

8%40

1.

8%17

0.

7%8

1.1%

2 0.

3%25

1.

0%19

0.

8%

Tota

l17

545

10

0.0%

23 0

95

100.

0%2

267

100.

0%2

630

100.

0%69

7 10

0.0%

826

100.

0%2

574

100.

0%2

357

100.

0%

Sour

ce: S

ource

: Sta

ts SA

QLF

S 201

0–20

20 (2

021)

Note

s:1.

No

scho

olin

g in

clude

s Gra

de R

/0.

2.

Less

than

prim

ary s

choo

ling

inclu

des t

he fo

llow

ing

cate

gorie

s: Gr

ade

1/Su

b A,

Gra

de 2

/Sub

B, G

rade

3/S

tand

ard

1/AE

T 1

(Kha

Ri G

ude,

SANL

I), G

rade

4/S

tand

ard

2, G

rade

5/S

tand

ard

3/AE

T 2,

Gr

ade

6/St

anda

rd 4

.3.

Pr

imar

y as H

LEA

refe

rs to

Gra

de 7

/Sta

ndar

d 5/

AET

3.4.

So

me

seco

ndar

y sch

oolin

g as

HLE

A in

clude

s the

follo

win

g ca

tego

ries:

Grad

e 8/

Stan

dard

6/F

orm

1, G

rade

9/S

tand

ard

7/Fo

rm 2

/AET

4, G

rade

10/

Stan

dard

8/F

orm

3, G

rade

11/

Stan

dard

9/F

orm

4,

NTC

l/N1/

NIC/

(v) L

evel

2, N

TC II/

N2/N

IC/(v

) Lev

el 3

, a ce

rtific

ate

with

less

than

Gra

de 1

2/St

anda

rd 1

0, an

d a d

iplo

ma w

ith le

ss th

an G

rade

12/

Stan

dard

10.

5.

Seco

ndar

y sch

oolin

g (G

rade

12

or e

quiva

lent

) as H

LEA

refe

rs to

the

follo

win

g ca

tego

ries:

Grad

e 12

/Sta

ndar

d 10

/For

m 5

/Mat

ric (n

o ex

empt

ion)

, Gra

de 1

2/St

anda

rd 1

0/Fo

rm 5

/Mat

ric (e

xem

ptio

n or

ba

chel

or’s

pass

), an

d NT

C III/

N3/N

IC/(v

) Lev

el 4

.6.

Ce

rtific

ate

refe

rs to

the

follo

win

g ca

tego

ries:

N4/N

TC 4

, N5/

NTC

5, N

6/NT

C 6,

and

a cer

tifica

te w

ith G

rade

12/

Stan

dard

10.

7.

Dipl

oma r

efer

s to

the

follo

win

g ca

tego

ries:

A di

plom

a with

Gra

de 1

2/St

anda

rd 1

0 an

d a h

ighe

r dip

lom

a. 8.

De

gree

refe

rs to

the

follo

win

g ca

tego

ries:

A po

st-hi

gher

dip

lom

a (m

aste

r’s o

r doc

tora

l dip

lom

a), a

bac

helo

r’s d

egre

e, a p

ostg

radu

ate

dipl

oma,

an h

onou

rs de

gree

, and

a hi

gher

deg

ree

(mas

ter’s

or P

hD).

9.

Othe

r inc

lude

s the

follo

win

g ca

tego

ries:

Do n

ot kn

ow.


Table 4 shows the level of education attained by age group for the years 2010 and 2020. The age groups compared are 15–24 years old, 25–34 years old, 35–44 years old, 45–54 years old, and 55–64 years old. The largest proportions are those who have had some secondary schooling, followed by those who have completed secondary education as their HLEA. In each age group, the proportions of persons with secondary education as their HLEA increased consistently from 2010 to 2020. Among persons with secondary education as their HLEA, those aged 15–24 years saw the largest upsurge (5.9 percentage points), from 24.1 percent in 2010 to 30.0 percent in 2020. Meanwhile, those aged 55–64 years had the least share, which increased by merely 3.4 percentage points from 13.1 percent in 2010 to 16.5 percent in 2020. The distribution in the share of persons with secondary education as their HLEA indicates that younger people are generally more likely to complete secondary education compared to older people. On the other hand, higher proportions of older persons tend to have a degree as their HLEA compared to their younger counterparts, suggesting the participation of many older people in the higher education system.

In order to inform suitable educational and skills policy interventions in response to rising globalisation and technological innovations, the knowledge base and specialised skills of individuals need to continually improve to meet the needs of labour markets worldwide (Asmal et al., 2020). It is therefore essential for each country to monitor the proportion of its population that has tertiary education and ensure that it grows over time. Tertiary education includes both theoretical programmes leading to advanced research or high-skill professions and more vocational programmes leading to the labour market.

The number of doctoral graduates per million people produced annually in a country is an indicator that is commonly used to assess a country’s progress towards the stock of high-level skills needed to stimulate innovation and productivity in an economy. South Africa’s NDP endorsed a target that more than 100 doctoral graduates per million people should be produced annually by 2030 in order to strengthen the country’s relative standing as a regional hub for higher education and training.


TABL

E 4:

Sha

re o

f per

sons

in th

e po

pula

tion

by h

ighe

st le

vel o

f edu

catio

nal a

ttain

men

t and

age

gro

up, 2

010

and

2020

LEVE

L O

F ED

UCAT

ION

AL A

TTAI

NM

ENT

15–2

4 YE

ARS

25–3

4 YE

ARS

35–4

4 YE

ARS

45–5

4 YE

ARS

55–6

4 YE

ARS

Q3

2010

Q3

2020

Q3

2010

Q3

2020

Q3

2010

Q3

2020

Q3

2010

Q3

2020

Q3

2010

Q3

2020

No sc

hool

ing

0.7%

0.3%

1.5%

0.6%

3.3%

1.3%

9.1%

2.8%

16.1

%7.

1%

Less

than

prim

ary

scho

olin

g6.

9%3.

4%6.

3%2.

8%11

.3%

4.8%

19.7

%9.

3%24

.2%

18.6

%

Prim

ary

scho

olin

g6.

7%5.

4%4%

2.1%

6.5%

3.2%

8.1%

5.1%

8.4%

8.6%

Som

e se

cond

ary

scho

olin

g 58

.2%

57.2

%42

.9%

39.4

%36

.9%

40.5

%32

.9%

37.3

%25

.8%

33.5

%

Seco

ndar

y (G

rade

12

or e

quiv

alen

t) sc

hool

ing

24.1

%30

.0%

32.4

%39

.9%

26.3

%33

.6%

15.5

%27

.5%

13.1

%16

.5%

Cert

ifica

te1.

1%1.

7%3.

2%4.

0%2.

6%4.

2%1.

3%2.

7%1.

0%1.

5%

Dipl

oma

1.1%

0.6%

5.4%

5.5%

6.3%

6.1%

5.3%

6.9%

4.6%

5.7%

Degr

ee0.

5%0.

7%3.

4%5.

1%5.

6%5.

6%6.

3%7.

4%4.

8%7.

0%

Oth

er0.

6%0.

7%1.

0%0.

6%1.

2%0.

6%1.

8%0.

9%2.

0%1.

4%

Tota

l10

0.0%

100.

0%10

0.0%

100.

0%10

0.0%

100.

0%10

0.0%

100.

0%10

0.0%

100.

0%

Sour

ce: S

ource

: Sta

ts SA

QLF

S 201

0–20

20 (2

021)

Note

s:1.

No

scho

olin

g in

clude

s Gra

de R

/0.

2.

Less

than

prim

ary s

choo

ling

inclu

des t

he fo

llow

ing

cate

gorie

s: Gr

ade

1/Su

b A,

Gra

de 2

/Sub

B, G

rade

3/S

tand

ard

1/AE

T 1

(Kha

Ri G

ude,

SANL

I), G

rade

4/S

tand

ard

2, G

rade

5/S

tand

ard

3/AE

T 2,

Gra

de 6

/St

anda

rd 4

.3.

Pr

imar

y as H

LEA

refe

rs to

Gra

de 7

/Sta

ndar

d 5/

AET

3.4.

So

me

seco

ndar

y sch

oolin

g as

HLE

A in

clude

s the

follo

win

g ca

tego

ries:

Grad

e 8/

Stan

dard

6/F

orm

1, G

rade

9/S

tand

ard

7/Fo

rm 2

/AET

4, G

rade

10/

Stan

dard

8/F

orm

3, G

rade

11/

Stan

dard

9/F

orm

4, N

TC l/

N1/

NIC/

(v) L

evel

2, N

TC II/

N2/N

IC/(v

) Lev

el 3

, a ce

rtific

ate

with

less

than

Gra

de 1

2/St

anda

rd 1

0, an

d a d

iplo

ma w

ith le

ss th

an G

rade

12/

Stan

dard

10.

5.

Seco

ndar

y sch

oolin

g (G

rade

12

or e

quiva

lent

) as H

LEA

refe

rs to

the

follo

win

g ca

tego

ries:

Grad

e 12

/Sta

ndar

d 10

/For

m 5

/Mat

ric (n

o ex

empt

ion)

, Gra

de 1

2/St

anda

rd 1

0/Fo

rm 5

/Mat

ric (e

xem

ptio

n or

ba

chel

or’s

pass

), an

d NT

C III/

N3/N

IC/(v

) Lev

el 4

.6.

Ce

rtific

ate

refe

rs to

the

follo

win

g ca

tego

ries:

N4/N

TC 4

, N5/

NTC

5, N

6/NT

C 6,

and

a cer

tifica

te w

ith G

rade

12/

Stan

dard

10.

7.

Dipl

oma r

efer

s to

the

follo

win

g ca

tego

ries:

A di

plom

a with

Gra

de 1

2/St

anda

rd 1

0 an

d a h

ighe

r dip

lom

a. 8.

De

gree

refe

rs to

the

follo

win

g ca

tego

ries:

A po

st-hi

gher

dip

lom

a (m

aste

r’s o

r doc

tora

l dip

lom

a), a

bac

helo

r’s d

egre

e, a p

ostg

radu

ate

dipl

oma,

an h

onou

rs de

gree

, and

a hi

gher

deg

ree

(mas

ter’s

or P

hD).

9.

Othe

r inc

lude

s the

follo

win

g ca

tego

ries:

Do n

ot kn

ow.


Figure 4 indicates that the number of doctoral graduates per million people per year increased consistently throughout the period 2010–2019, from 28 graduates per million in 2010 to 59 graduates per million in 2019. In order to achieve the NDP 2030 target for doctoral graduates, these numbers would have to increase by an average of at least four graduates per million annually over the period 2020–2030.

FIGURE 4: Number of doctoral degree graduates per million people per year, 2010–2019

2010 2011 2012 2013 2014 2015 2016 2017 2018 20190

10

20

30

40

50

60

70

per m

illio

n pe

ople

2831

36 3842

4650

5458 59

Sources: Stats SA mid-year population estimates (2020); DHET Higher Education Management Information System (2021b)

Figure 5 makes an international comparison of doctoral degree graduates relative to the population based on the proportions of selected countries’ populations aged 25 years and older that attained doctoral or equivalent (ISCED 8) degrees in 2018. The respective indicator is calculated by dividing the number of persons aged 25 years and above who hold a completed doctoral or equivalent degree by the total population of the same age group and multiplying the result by 100.

The share of South Africa’s population that attained a doctoral or equivalent qualification relative to the 25 years and older category was considerably lower (at 0.3 percent in 2017 and 0.2 percent in 2018) compared to that of other nations. Countries whose performance in this regard would be considered close to South Africa’s include Hungary (with 0.6 percent in 2017 and 0.7 percent in 2018) and Portugal (with 0.8 percent in both 2017 and 2018). Nations that recorded the highest performance on this indicator are Germany (with 2.1 percent in both 2017 and 2018) and the United Kingdom (with 2.0 percent in both 2017 and 2018), while Austria, Belgium, and Slovakia sat at the middle of the list.


FIGURE 5: Share of population that attained doctoral degrees or equivalent (ISCED 8) (%), for the population aged 25 years and older, 2017–2018

1.0%

1.5%

2.0%

2.5%%

of p

opul

atio

n

0.0%

0.5%

South Africa Austria Belgium Germany Hungary Portugal Slovakia United Kingdom

2017 0.3 1.4 1.5 2.1 0.6 0.8 1.5 2.0

2018 0.2 1.3 1.6 2.1 0.7 0.8 1.3 2.0

Sources: Stats SA, General Household Surveys (2017, 2018); Stats SA mid-year population estimates (2020); OECD (2021b)

Note: The proportions for all other countries are obtained from the OECD, while proportions for South Africa are calculated using data from Stats SA.

Figure 6 compares persons who completed a bachelor’s degree relative to the population across a range of selected countries. The graph shows that the percentage of the population aged 25 years and over with at least a completed bachelor’s or equivalent degree (ISCED 64) or higher in South Africa stood at 8.2 percent in 2017. South Africa’s performance in this regard was higher compared to that of other African nations such as Burundi (0.9 percent), Mozambique (1.8 percent), Senegal (2.8 percent), and Zimbabwe (3.3 percent). Internationally, South Africa’s position was also higher than that of countries such as Sri Lanka (4.2 percent), Fiji (5.2 percent), El Salvador (6.7 percent), and Puerto Rico (7.6 percent). However, South Africa’s position relative to European countries especially and similar middle-income countries such as Brazil and Mexico remains very low. Kuwait (10.7 percent), Mexico (15.4 percent), Brazil (15.7 percent), France (18.0 percent), Finland (24.3 percent), Australia (31.4 percent), the United Kingdom (33.9 percent), and Belgium (34.7 percent) have much higher proportions of adults with degrees than South Africa. Even Bangladesh, which has a lower GDP than South Africa, has a higher proportion of adults with degrees.

4 Definition provided in Appendix A.


FIGURE 6: Percentage of the population aged 25 years and over with at least a completed bachelor’s or equivalent degree (ISCED 6 or higher), 2017

Europ

e

United Kingdom

Finland

France

Belgium

Austr

alia/

Ocea

nia Fiji

Australia

Ameri

ca

Puerto Rico

Mexico

El Salvador

Brazil

Asia

Sri Lanka

Kuwait

Bangladesh

Afric

a

Senegal

South Africa

Zimbabwe

Mozambique

Burundi

% of population aged 25+ years

0 5 10 15 20 25 30 35 40

33.9

24.3

18.0

34.7

5.2

31.4

7.6

15.4

6.7

15.7

4.2

10.7

9.0

2.8

8.2

3.3

1.8

0.9

Source: World Bank Education Statistics (2020a)

Notes:1. The latest data available at the time of producing the report were for the year 2017.2. The countries included in this figure were selected based on the availability of the latest data.

Figure 7 indicates the share of the population aged 25–34 years that has tertiary education in South Africa relative to those of the same age category in selected countries around the world, expressed as a percentage. Over the years 2016–2018, South Africa’s share fares poorly compared to other countries in the OECD group, at 5.4 percent and 5.6 percent in 2016 and 2018, respectively. South Africa’s performance was lower than the OECD averages of 42.5 percent in 2016 and 44.1 percent in 2018. It was also lower than Mexico’s performance (21.8 percent in 2016 and 23.4 percent in 2018), as well as Brazil’s (19.7 percent in 2016 and 21.3 percent in 2018).


FIGURE 7: Percentage of the population aged 25–34 years with tertiary education, 2016–2018

% o

f pop

ulat

ion

aged

25–

34 ye

ars

Australia Brazil Canada Mexico USA OECD average South Africa

2016 49.3 19.7 60.6 21.8 47.5 42.5 5.4

2017 52.0 19.6 60.9 22.6 47.8 43.3 6.0

2018 51.4 21.3 61.8 23.4 49.4 44.1 5.6

0

10

20

30

40

50

60

70

51.45249.3

21.319.619.7

61.860.960.6

23.422.621.8

49.447.847.544.143.342.5

5.665.4

Source: OECD Education at a Glance: Educational Attainment and Labour-Force Status (2021a)

3.2 How does educational attainment affect participation in the labour market?

Table 5 presents the numbers and shares of persons in the population aged 25–64 years by their HLEA and their employment status in 2010, 2019, and 2020. From 2010 to 2019, the total number of persons employed increased by 23.1 percent, but the figure dropped by 9.0 percent in 2020 due to the negative impact of economic contractions caused by the COVID-19 pandemic. The table below reveals that over the last decade, higher levels of education have correlated with higher employment rates. Thus, while those who had some secondary education as their HLEA saw their employment levels decline slightly, from 33.1 percent in 2010 to 32.9 percent in 2019, the number of those with post-school certificates, diplomas, and degrees increased along with the employment levels for this group.


TABL

E 5:

Num

ber a

nd sh

are

of p

erso

ns in

the

popu

latio

n ag

ed 2

5–64

year

s by

high

est l

evel

of e

duca

tiona

l atta

inm

ent a

nd e

mpl

oym

ent s

tatu

s, Q3

201

0, Q

3 20

19, a

nd Q

3 20

20

HIG

HES

T LE

VEL

OF

ED

UCAT

ION

AL A

TTAI

NM

ENT

EMPL

OYED

UNEM

PLOY

ED5

Q3

2010

Q3

2019

Q3

2020

Q3

2010

Q3

2019

Q3

2020

THOUSANDS

%

THOUSANDS

%

THOUSANDS

%

THOUSANDS

%

THOUSANDS

%

THOUSANDS

%

No sc

hool

ing

401

3.2%

286

1.9%

167

1.2%

78

2.4%

68

1.3%

53

1.0%

Less

than

prim

ary

scho

olin

g1

107

8.9%

913

6.0%

703

5.1%

316

9.6%

305

5.9%

267

5.1%

Prim

ary

scho

olin

g62

7 5.

1%58

7 3.

8%43

6 3.

1%18

6 5.

7%19

9 3.

8%21

4 4.

1%

Som

e se

cond

ary

scho

olin

g 4

106

33.1

%5

017

32.9

%4

522

32.5

%1

554

47.2

%2

509

48.3

%2

398

45.5

%

Seco

ndar

y (G

rade

12

or e

quiv

alen

t) sc

hool

ing

3 58

4 28

.9%

4 88

4 32

.0%

4 76

2 34

.3%

929

28.2

%1

586

30.5

%1

779

33.7

%

Cert

ifica

te39

3 3.

2%63

8 4.

2%62

3 4.

5%78

2.

4%19

9 3.

8%18

4 3.

5%

Dipl

oma

1 04

8 8.

4%1

293

8.5%

1 20

9 8.

7%80

2.

4%18

9 3.

6%22

4 4.

3%

Degr

ee96

3 7.

8%1

459

9.6%

1 38

4 10

.0%

39

1.2%

110

2.1%

126

2.4%

Oth

er17

8 1.

4%19

5 1.

3%88

0.

6%31

0.

9%34

0.

7%27

0.

5%

Tota

l12

406

10

0.0%

15 2

73

100.

0%13

895

10

0.0%

3 29

2 10

0.0%

5 19

7 10

0.0%

5 27

2 10

0.0%

Sour

ce: S

tats

SA Q

LFS 2

010–

2020

(202

1)

Note

s:1.

No

scho

olin

g in

clude

s Gra

de R

/0.

2.

Less

than

prim

ary s

choo

ling

inclu

des t

he fo

llow

ing

cate

gorie

s: Gr

ade

1/Su

b A,

Gra

de 2

/Sub

B, G

rade

3/S

tand

ard

1/AE

T 1

(Kha

Ri G

ude,

SANL

I), G

rade

4/S

tand

ard

2, G

rade

5/S

tand

ard

3/AE

T 2,

Gr

ade

6/St

anda

rd 4

.3.

Pr

imar

y as H

LEA

refe

rs to

Gra

de 7

/Sta

ndar

d 5/

AET

3.4.

So

me

seco

ndar

y sch

oolin

g as

HLE

A in

clude

s the

follo

win

g ca

tego

ries:

Grad

e 8/

Stan

dard

6/F

orm

1, G

rade

9/S

tand

ard

7/Fo

rm 2

/AET

4, G

rade

10/

Stan

dard

8/F

orm

3, G

rade

11/

Stan

dard

9/F

orm

4,

NTC

l/N1/

NIC/

(v) L

evel

2, N

TC II/

N2/N

IC/(v

) Lev

el 3

, a ce

rtific

ate

with

less

than

Gra

de 1

2/St

anda

rd 1

0, an

d a d

iplo

ma w

ith le

ss th

an G

rade

12/

Stan

dard

10.

5.

Seco

ndar

y sch

oolin

g (G

rade

12

or e

quiva

lent

) as H

LEA

refe

rs to

the

follo

win

g ca

tego

ries:

Grad

e 12

/Sta

ndar

d 10

/For

m 5

/Mat

ric (n

o ex

empt

ion)

, Gra

de 1

2/St

anda

rd 1

0/Fo

rm 5

/Mat

ric (e

xem

ptio

n or

ba

chel

or’s

pass

), an

d NT

C III/

N3/N

IC/(v

) Lev

el 4

.6.

Ce

rtific

ate

refe

rs to

the

follo

win

g ca

tego

ries:

N4/N

TC 4

, N5/

NTC

5, N

6/NT

C 6,

and

a cer

tifica

te w

ith G

rade

12/

Stan

dard

10.

7.

Dipl

oma r

efer

s to

the

follo

win

g ca

tego

ries:

A di

plom

a with

Gra

de 1

2/St

anda

rd 1

0 an

d a h

ighe

r dip

lom

a. 8.

De

gree

refe

rs to

the

follo

win

g ca

tego

ries:

A po

st-hi

gher

dip

lom

a (m

aste

r’s o

r doc

tora

l dip

lom

a), a

bac

helo

r’s d

egre

e, a p

ostg

radu

ate

dipl

oma,

an h

onou

rs de

gree

, and

a hi

gher

deg

ree

(mas

ter’s

or P

hD).

9.

Othe

r inc

lude

s the

follo

win

g ca

tego

ries:

Othe

r and

Do

not k

now

.

5 Th

e ‘na

rrow

’ or o

fficia

l defi

nitio

n of

une

mpl

oym

ent w

as u

sed.


Table 6 presents the unemployment rates of South African persons aged 25–34 years by their HLEA relative to the OECD average and the national rates of Australia, Brazil, Russia, Indonesia, Italy, and the United States. In 2019, South Africa’s unemployment rates for persons in the specified age category among each of the three groups of educational attainment (below upper secondary, upper secondary or non-tertiary post-secondary, and tertiary) were much higher relative to the analogous unemployment rates of specified countries and the OECD average. The unemployment rates by level of education qualification generally decline as persons attain higher levels of educational attainment.

TABLE 6: Unemployment rates6 of 25–34-year-olds by highest level of educational attainment, as a percentage, 2019

BELOW UPPER SECONDARY

UPPER SECONDARY OR NON-TERTIARY POST-SECONDARY TERTIARY

South Africa 37 35 10

OECD average 13 7 5

Australia 10 5 3

Brazil 14 13 8

Russia 14 7 4

Indonesia 3 5 5

Italy 21 14 12

United States 10 6 2

Source: OECD Education at a Glance (2020)

3.3 How does HLEA affect wages?

PSET qualifications provide good returns to individuals. They improve their chances of attaining employment and access to better wages. Table 7 shows that the median wages of workers with a degree are more than six times as large as those of workers without matric or secondary education at least. The race gap in median wages favours white people above all other race groups at all levels of education. However, disparities in the median wage earnings per month narrowed substantially among persons with a degree across all the four race groups (black African, coloured, Indian/Asian, and white), where the lowest median wage was R18 488 among black African people and the highest median wage was R20 142 among white counterparts.

In addition, the gender gap in median wages favours male persons above female persons at all levels of education. However, similar to the racial disparities, the gap between males and females with a degree is narrowing. In 2019, the median wage of males with a degree was 7.6 percent (R1 409) higher than the female median wage (at R18 591).

6 Unemployment rates as a percentage of 25–34-year-olds in the labour force.


TABLE 7: Median wages per month by race, gender, and highest level of educational attainment, 2019

NO MATRIC MATRIC CERTIFICATE DIPLOMA DEGREE TOTAL

Black African 3 021 4 000 5 164 7 023 18 488 3 563

Coloured 3 491 4 500 4 923 5 681 18 591 3 683

Indian/Asian 4 648 5 900 20 033 14 460 19 624 7 453

White 12 216 9 668 19 337 15 107 20 142 13 132

All males 3 580 4 648 10 833 8 728 20 000 4 131

All females 2 545 3 850 4 886 7 050 18 591 3 466

Total 3 200 4 190 7 500 8 000 19 135 3 822

Source: Stats SA QLFS (2019)

4Access to post-school education and training


4.1 To what extent is there access to PSET?

This chapter provides an analysis of enrolment trends in the PSET system by making use of the following indicators: the Gross Enrolment Ratio (GER) and the Gender Parity Index (GPI). An analysis of enrolment trends relative to the overall population and the number of persons who are not in employment, education, and training (NEET) is first presented to assess whether the PSET system is making a transformational impact on the skill sets of the South African population.

4.1.1 Enrolment at PSET institutions relative to the populationTable 8 below presents the population trends of persons aged 15–64 relative to their enrolment in the PSET system. During the period 2010–2019, enrolment grew significantly compared to the population. Whereas population growth was 14.6 percent from 2010 to 2019, PSET enrolment showed a growth rate of 38.8 percent. This trend suggests that, in general, the PSET enrolment trajectory compares well with population growth trends.

FIGURE 8: Working-age population (15–64 years), growth rate versus PSET enrolment rate, 2010 and 2019

2010 2019

% GROWTHTHOUSANDS

Population 33 462 38 341 14.6%

Enrolment 1 802 2 502 38.8%

Sources: DHET Statistics on PSET (2010, 2019); Stats SA mid-year population estimates (2020).

Notes:1. The data for 2018 do not indicate the total enrolment because CET colleges, GETC: ABET Level 4 registration data for

examinations were used as a proxy for reporting on enrolment for CET colleges.2. The CET data for 2019 are based on a 70.7 percent response rate.3. The private colleges data for 2019 are based on a 53.7 percent response rate.

4.1.2 Enrolment at PSET institutions relative to persons who are NEET

South Africa has made remarkable strides in expanding enrolment and promoting equitable access to PSET institutions. However, the attainment of NDP enrolment targets continues to face headwinds from the growing number of youth who are NEET.

Figure 9 shows that enrolment at PSET institutions is increasing year on year, but the increase is not enough to curb the high numbers of persons who are NEET in the country. In 2019, only 2.5 million students of all age groups were enrolled at PSET institutions, yet 3.3 million youth aged 15–24 years were in the NEET category. This paradox indicates a need to expand access to post-school opportunities and requires PSET institutions to offer a diversity of programmes that not only take into account the needs of the youth who completed schooling but also those who did not complete their schooling (Khuluvhe & Negogogo, 2021).

4 | ACCESS TO POST -SCHOOL EDUCATION AND TRAINING | 41

FIGURE 9: Total number of students attending PSET institutions (all age groups) compared to NEET youth (15–24-year-olds) in thousands, 2013–2019

Thou

sand

s

2013 2014 2015 2016 2017 2019 20190

500

1 000

1 500

2 000

2 500

3 000

3 00

4 000

3 340

2 503

3 261

2 324

3 212

2 384

3 139

2 473

3 219

2 541

3 213

2 625

3 254

2 532

NEET youth Total enrolment

Sources: DHET Statistics on PSET (2015, 2016, 2017b, 2018, 2019b, 2020d, 2021d); Stats SA QLFS (2013–2019)

4.1.3 Access to universitiesIn 2019, there were 26 public universities and 131 private universities7 in South Africa, with the total public and private enrolment being over 1.2 million in that year.

4.1.3.1 GER – Public universities

Table 8 shows that in 2019, the GER (participation rate) for public universities was close to 22.0 percent, reflecting a significant increase since 2010, when the GER was 16.5 percent. Given enrolment growth trends over the past decade, it is very likely that the target of 25.0 percent set by the White Paper for Post-School Education and Training (DHET, 2013a) for university participation rates will be met by 2030.

While the number of black African students enrolled at public universities grew by an average rate of 3.8 percent from 2010 to 2019, resulting in black African students making up over 80 percent of the enrolment rate at public universities, the number of whites and Indian/Asian students declined by 3.7 percent and 2.4 percent, respectively. However, the GER for black African students remains the lowest when compared to that of other race groups. In 2019, the GER for black African students sat at 20.2 percent, while that of white students sat at 48.6 percent.

7 Legally, the term ‘private higher education institutions’ is used to refer to what is commonly known as private ‘universities’.


TABLE 8: Public universities: Total headcounts and GER by race, 2010–2019

YEAR BLACK AFRICAN COLOURED INDIAN/

ASIAN WHITE UNKNOWN TOTAL

2010 595 783 58 176 54 492 178 190 6 295 892 936

2011 640 443 59 312 54 698 177 365 6 383 938 201

2012 662 066 58 671 52 284 172 611 7 741 953 373

2013 689 503 61 034 53 787 171 927 7 447 983 698

2014 679 800 60 716 53 611 166 172 8 855 969 154

2015 696 320 62 186 53 378 161 739 11 589 985 212

2016 701 482 61 963 50 450 152 489 9 453 975 837

2017 763 767 64 772 50 131 148 802 9 512 1 036 984

2018 820 619 65 911 47 865 140 305 10 868 1 085 568

2019 830 797 62 362 43 330 126 755 11 668 1 074 912

AVERAGE ANNUAL ENROLMENT GROWTH RATE

2010–2019 3.8% 0.8% –2.4% –3.7% 8.1% 2.1%

GROSS ENROLMENT RATIO

2010 13.2% 13.3% 46.4% 52.6% – 16.5%

2011 14.2% 13.5% 46.7% 54.1% – 17.4%

2012 14.7% 13.3% 44.7% 54.1% – 17.7%

2013 15.4% 13.8% 46.1% 55.5% – 18.4%

2014 15.3% 13.8% 46.3% 55.1% – 18.3%

2015 15.9% 14.2% 46.6% 55.1% – 18.9%

2016 16.2% 14.2% 44.6% 53.6% – 18.9%

2017 17.9% 15.0% 45.1% 53.8% – 20.4%

2018 19.7% 15.3% 44.1% 52.2% – 21.8%

2019 20.2% 14.6% 41.0% 48.6% – 21.9%

Source: Stats SA mid-year population estimates (2020); DHET Higher Education Management Information System (2021b)

4.1.3.2 GER – Private universities

Table 9 shows that the overall GER of students enrolled at private universities increased by 2.2 percentage points, from 1.7 percent in 2011 to 3.9 percent in 2019. Indian/Asian students enrolled at private universities recorded the highest GER, at 13.8 percent, while black African students recorded the lowest GER, at 3.1 percent.


TABLE 9: Private universities: Total headcounts and GER by race, 2011–2019

YEAR BLACK AFRICAN COLOURED INDIAN/ASIAN WHITE TOTAL

2011 56 988 7 526 5 913 23 311 93 738

2012 56 813 6 876 5 222 18 500 87 411

2013 64 933 8 183 6 649 26 664 106 429

2014 80 983 12 716 10 396 22 191 126 286

2015 83 997 11 127 9 456 25 740 130 320

2016 99 972 11 223 10 494 27 212 148 901

2017 112 124 13 491 11 955 29 780 167 350

2018 122 342 14 057 12 756 31 802 180 957

2019 128 519 16 260 14 594 32 131 191 504


2011–2019 11.0% 11.8% 13.6% 5.7% 10.2%


2011 1.3% 1.7% 5.0% 7.1% 1.7%

2012 1.3% 1.6% 4.5% 5.8% 1.6%

2013 1.4% 1.9% 5.7% 8.6% 2.0%

2014 1.8% 2.9% 9.0% 7.4% 2.4%

2015 1.9% 2.5% 8.3% 8.8% 2.5%

2016 2.3% 2.6% 9.3% 9.6% 2.9%

2017 2.6% 3.1% 10.8% 10.8% 3.3%

2018 2.9% 3.3% 11.8% 11.8% 3.6%

2019 3.1% 3.8% 13.8% 12.3% 3.9%

Sources: DHET Statistics on Post-School Education and Training in South Africa (2013c, 2014, 2015, 2016, 2017b, 2018, 2019b, 2020d, 2021d); DHET annual report submitted by private HEIs (2019); Stats SA mid-year population estimates (2020)

4.1.3.3 GER – Public and private universities

Table 10 presents the headcount enrolments and GERs by race for both public and private universities over the period 2011–2019. Over this period, the number of students enrolled at universities grew by an average annual growth rate of 2.6 percent, resulting in total enrolment at both public and private universities reaching close to 1.3 million in 2019. In 2019, the GER for the South African university sector (public and private combined) was 25.6 percent, reflecting a significant increase compared to 2011, when the GER was 19.0 percent. This increase was the result of black African student enrolment, which grew by 3.8 percent from 2010 to 2019, while the number of white and Indian/Asian students declined by 2.6 percent and 0.5 percent, respectively.


TABLE 10: Public and private universities: Total headcounts and GER by race, 2011–2019


2011 697 431 66 838 60 611 200 676 1 025 556

2012 718 879 65 547 57 506 191 111 1 033 043

2013 754 436 69 217 60 436 198 591 1 082 680

2014 760 783 73 432 64 007 188 363 1 086 585

2015 780 317 73 313 62 834 187 479 1 103 943

2016 801 454 73 186 60 944 179 701 1 115 285

2017 875 891 78 263 62 086 178 582 1 194 822

2018 942 961 79 968 60 621 172 107 1 255 657

2019 959 316 78 622 57 924 158 886 1 254 748


2011–2019 4.1% 2.1% –0.5% –2.8% 2.6%


2011 15.5% 15.2% 51.7% 61.2% 19.0%

2012 16.0% 14.8% 49.2% 59.9% 19.2%

2013 16.8% 15.7% 51.8% 64.1% 20.2%

2014 17.2% 16.7% 55.3% 62.5% 20.5%

2015 17.8% 16.7% 54.8% 63.9% 21.1%

2016 18.5% 16.8% 53.8% 63.2% 21.6%

2017 20.6% 18.1% 55.8% 64.5% 23.5%

2018 22.6% 18.6% 55.9% 64.0% 25.2%

2019 23.4% 18.4% 54.8% 60.9% 25.6%

Sources: DHET Higher Education Management Information System (2021b); DHET Statistics on Post-School Education and Training in South Africa (2013c, 2014, 2015, 2016, 2017b, 2018, 2019b, 2020d, 2021d); DHET annual report submitted by private HEIs (2019); Stats SA mid-year population estimates (2020)

4.1.3.4 Enrolment per 100 000 people

Measuring the enrolment in higher education per 100 000 people in the total population is an alternate way of assessing the extent of student participation in the sector (DBE, 2009), since this approach avoids reference to the age of the population, thereby providing a relatively different perspective on access. The measure assists in comparing year-on-year enrolment in spite of any fluctuations in the 20–24-year age group, which is used in the calculation of the GER referred to in the above sections. Figure 10 shows that student enrolment at universities (both public and private) per 100 000 members of the population increased by 263 over the past decade.


FIGURE 10: Enrolment at tertiary education institutions per 100 000 people, 2010–2019

2010 2011 2012 2013 2014 2015 2016 2017 2018 20191 750

1 950

1 900

1 850

1 800

2 000

2 050

2 100

2 150

2 200

2 250pe

r 100

000

peo

ple

1 921

2 002 1 990

2 0582 041 2 047 2 035

2 142

2 2162 184

Sources: DHET Statistics on Post-School Education and Training in South Africa (2013b, 2013c, 2014, 2015, 2016, 2017b, 2018, 2019b, 2020d, 2021d); Stats SA mid-year population estimates (2020)

Note: Enrolments at tertiary education level include both public and private HEIs.

4.1.3.5 International comparison of GER

Despite significant growth in the participation rate of students at universities over the past decade, Figure 11 shows that South Africa’s GER, at 21.8 percent,8 is significantly below the average for other middle-income countries, which stood at 36.0 percent in 2018. South Africa’s GER is also exceptionally low compared to high-income countries, where the average participation rate is 77.0 percent. However, it fares much better than low-income and Sub-Saharan African countries, where average participation rates are 9.5 percent and 9.4 percent, respectively.

FIGURE 11: GERs for tertiary education by GDP per capita (PPP US$), 2018

Low income

Sub-Saharan Africa

Middle income

Upper middle income

OECD members

High income South Africa

0 0%

30%

20%

10%10 000

40%

20 000

50%30 000

60%40 000

70%50 000

80%

60 000 90%

US$

perc

enta

ge

GDP per capita (2010 constant US$) GER

11 600

36.0

44 913

75.6

3 848

9.416 728

51.8

12 929

21.8

9.5

2 408

50 153

77.0

Source: World Bank (2020b)

8 This figure is for 2018.


4.1.3.6 Gender Parity Index – Universities

Table 11 shows that more females than males participated at both public and private universities for the period 2011 to 2019, resulting in a GPI of 1.59 in 2019. Table 11 also shows that despite significant increases in GPI at private universities since 2011, the index at public universities was higher than at private universities in 2019.

TABLE 11: Trends in GPI, 2011–2019

YEAR PUBLIC UNIVERSITIES PRIVATE UNIVERSITIES TOTAL

2011 1.4 1.1 1.4

2012 1.4 1.2 1.4

2013 1.4 1.2 1.4

2014 1.4 1.1 1.4

2015 1.4 1.2 1.4

2016 1.4 1.3 1.4

2017 1.4 1.4 1.4

2018 1.5 1.4 1.5

2019 1.5 1.4 1.5

Sources: DHET Statistics on Post-School Education and Training in South Africa (2013c, 2014, 2015, 2016, 2017b, 2018, 2019b, 2020d, 2021d); DHET annual report submitted by private HEIs (2019); DHET Higher Education Management Information System (2021b); Stats SA mid-year population estimates (2020)

Note: A GPI of 1 indicates equitable gender participation. A GPI above 1 is indicative of higher female participation, while a GPI below 1 is indicative of higher male participation.

Table 12 shows higher female participation than male participation across all race groups for all the years under review. South Africa has done fairly well in terms of gender transformation within the student composition.

TABLE 12: Public and private universities: GPI by race, 2011–2019


2011 1.4 1.1 1.4 1.4 1.1

2012 1.4 1.2 1.4 1.4 1.2

2013 1.4 1.2 1.4 1.4 1.2

2014 1.4 1.1 1.4 1.4 1.1

2015 1.4 1.2 1.4 1.4 1.2

2016 1.4 1.3 1.4 1.4 1.3

2017 1.4 1.4 1.4 1.4 1.4

2018 1.5 1.4 1.5 1.5 1.4

2019 1.5 1.7 1.6 1.3 1.5

Sources: DHET Statistics on Post-School Education and Training in South Africa (2013c, 2014, 2015, 2016, 2017b, 2018, 2019b, 2020d, 2021d); DHET annual report submitted by private HEIs (2019); DHET Higher Education Management Information System (2021b); Stats SA mid-year population estimates (2020)


9 This indicates that female enrolment is 50% higher than male enrolment.


Table 13 shows the GPI by race group in public universities. In 2019, the GPI was highest among coloured students, at 1.8, and lowest among white students, at 1.3.

TABLE 13: Public universities: GPI by race, 2010–2019


2010 1.4 1.5 1.5 1.2 1.42011 1.4 1.6 1.6 1.2 1.42012 1.4 1.6 1.6 1.2 1.42013 1.4 1.6 1.6 1.2 1.42014 1.4 1.6 1.7 1.3 1.42015 1.4 1.7 1.7 1.3 1.42016 1.4 1.7 1.7 1.3 1.42017 1.4 1.7 1.7 1.3 1.42018 1.5 1.8 1.7 1.3 1.52019 1.5 1.8 1.7 1.3 1.5

Sources: Stats SA mid-year population estimates (2020); DHET Higher Education Management Information System (2021)


4.1.3.7 International comparison of GPI

Figure 12 shows that South Africa’s GPI for tertiary education is among the highest in the world. In 2018, the GPI for South Africa stood at 1.32 compared to the averages for high-income countries (1.20), upper-middle income countries (1.16), OECD members (1.15), and the Sub-Saharan African region (0.77).

FIGURE 12: GPI for gross tertiary enrolment, 2018

GPI

Incom

e grou

p/reg

ion

High income

Upper-middle income

OECD members

Middle income

Low and middle income

Lower-middle income

Sub-Saharan Africa

Low income

Natio

n

Republic of Korea

Germany

India

Russian Federation

Malaysia

China

United Kingdom

South Africa

0,0 0.2 0.4 0.6 0.8 1.0 1.2 1.4

1.20

1.16

1.15

1.12

1.10

1.04

0.77

0.64

0.77

1.03

1.07

1.15

1.18

1.18

1.27

1.32

Source: World Bank (2020c)

Note: The countries included in this figure were selected based on the availability of the latest data.


4.1.4 Access to TVET collegesThe NDP (National Planning Commission, 2012) anticipates that TVET colleges will become “the institutions of choice for the training of artisans and producing other mid-level skills”. TVET colleges are therefore intended to provide the technical and vocational knowledge, skills, and attributes that are vital for national social and economic development. To achieve this aim, the White Paper for Post-School Education and Training (DHET, 2013a) indicates that public TVET colleges must expand access, improve the quality of provisioning, become more efficient, and ensure that their programmes are more responsive to the needs of the economy and the labour market. Currently, there are 50 public TVET colleges in South Africa, with 253 campuses located all over the country.

4.1.4.1 GER – TVET colleges

This section provides an analysis of the extent to which young people, particularly in terms of their race and gender, participate at TVET colleges. The GER for TVET colleges, which provides a measure of participation, is calculated as the total headcount for enrolment (regardless of age) expressed as a percentage of the total population aged 16–20 years. The age group was revised from that used in the previous PSET monitor (DHET, 2019a),10 in order to align the current report to the policy objective of targeting 16–18-year-olds for National Certificate (Vocational) programmes (equivalent to a matric qualification) and 19–20-year-olds for N4–N6 programmes, particularly because entry into N-level programmes requires the completion of matric.

Table 14 shows that the GER for TVET colleges more than doubled over the past decade, from 6.9 percent in 2010 to 14.6 percent in 2019. Despite the significant increase in TVET participation rates in the last ten years, it is unlikely that the NDP target of 25.0 percent GER will be met by 2030, given the current slow growth trajectory. Similarly, although enrolment at TVET colleges rose by 7.3 percent from 2010 to 2019, it is not probable that the White Paper for Post-School Education and Training enrolment target of 2.5 million TVET college students will be met by 2030, as this would require sustained enrolment growth of almost 13.0 percent per year over the period 2019–2030.

Table 14 also shows that in 2019, the TVET college participation rate of black African students (16.0 percent) was higher than that of other race groups in South Africa, with the participation rates of Indians/Asians and whites visibly lower.

10 The age group used in the 2018 PSET monitor was 16–24 years.


TABLE 14: TVET colleges: Total enrolment and GER by race, 2010–2019

YEAR BLACK AFRICAN COLOURED INDIAN/ASIAN WHITE TOTAL11

2010 266 620 31 545 4 004 15 702 358 393

2011 310 990 33 197 3 993 14 630 400 273

2012 429 593 40 066 4 816 14 503 657 690

2013 553 248 41 557 3 985 13 370 612 621

2014 588 664 44 341 3 226 11 692 702 383

2015 650 419 39 621 2 617 9 996 737 880

2016 649 677 46 031 1 932 7 547 705 397

2017 635 717 43 640 1 699 6 826 688 028

2018 603 112 46 597 1 452 5 850 657 133

2019 621 187 45 374 1 535 5 243 673 490

AVERAGE ENROLMENT ANNUAL GROWTH RATE

2010–2019 9.9% 4.1% –10.1% –11.5% 7.3%

GROSS ENROLMENT RATIO FOR TVET COLLEGES

2010 6.2% 7.1% 3.7% 4.9% 6.9%

2011 7.3% 7.5% 3.7% 4.7% 7.8%

2012 10.2% 9.2% 4.5% 4.8% 13.0%

2013 13.3% 9.6% 3.8% 4.6% 12.3%

2014 14.5% 10.3% 3.2% 4.1% 14.4%

2015 16.3% 9.3% 2.7% 3.6% 15.4%

2016 16.5% 10.8% 2.0% 2.8% 14.9%

2017 16.4% 10.4% 1.8% 2.6% 14.8%

2018 15.6% 11.2% 1.6% 2.3% 14.2%

2019 16.0% 11.1% 1.7% 2.1% 14.6%

Sources: DHET Statistics on Post-School Education and Training (2015, 2016, 2017b, 2018, 2019b, 2020d, 2021d); Stats SA mid-year population estimates (2020); TVET Management Information System (2021e)

Table 15 shows that in 2019, the participation rate of female students at TVET colleges (17.0 percent) was significantly higher than that of male students (12.0 percent). However, this was not the case a decade ago, when the GER for male students was higher than that of female students from 2010 until 2012. In 2019, the GER of black African and coloured female students was higher than that of their male counterparts, whereas the GER of Indian/Asian and white male students was higher than that of their respective female students.

11 Enrolment by race does not add up to the total due to the unspecified racial classification of some students.


TABLE 15: TVET colleges: GER by race and gender, 2010–2019 (%)

BLACK AFRICAN COLOURED INDIAN/ASIAN WHITE GRAND TOTAL

FEM

ALE

MAL

E

TOTA

L

FEM

ALE

MAL

E

TOTA

L

FEM

ALE

MAL

E

TOTA

L

FEM

ALE

MAL

E

TOTA

L

FEM

ALE

MAL

E

TOTA

L

2010 6.0% 6.3% 6.2% 6.8% 7.4% 7.1% 1.6% 5.8% 3.7% 2.7% 7.3% 4.9% 6.5% 7.3% 7.6%

2011 7.4% 7.2% 7.3% 7.1% 8.0% 7.5% 1.3% 6.2% 3.7% 2.2% 7.3% 4.7% 7.5% 8.1% 8.5%

2012 10.6% 9.8% 10.2% 8.4% 10.0% 9.2% 1.7% 7.5% 4.5% 2.1% 7.6% 4.8% 10.2% 10.4% 10.9%

2013 14.1% 12.6% 13.3% 8.9% 10.2% 9.6% 1.7% 6.1% 3.8% 1.7% 7.4% 4.6% 13.1% 12.6% 12.3%

2014 16.0% 13.0% 14.5% 9.7% 10.6% 10.2% 1.4% 5.1% 3.2% 1.9% 6.3% 4.1% 15.0% 13.3% 14.4%

2015 18.2% 14.4% 16.3% 8.6% 9.9% 9.3% 1.0% 4.4% 2.7% 1.4% 5.8% 3.6% 16.7% 14% 15.4%

2016 19.1% 14.0% 16.5% 10.6% 11.1% 10.8% 0.8% 3.3% 2.0% 1.2% 4.5% 2.8% 16.9% 13% 14.9%

2017 18.9% 13.8% 16.4% 10.6% 10.2% 10.4% 0.7% 3.0% 1.8% 0.9% 4.3% 2.6% 16.8% 12.7% 14.8%

2018 18.2% 13% 15.6% 11.9% 10.6% 11.2% 0.7% 2.5% 1.6% 0.8% 3.8% 2.3% 16.3% 12.1% 14.2%

2019 19.1% 12.9% 16.0% 11.5% 10.6% 11.1% 0.8% 2.7% 1.7% 0.8% 3.4% 2.1% 17.1% 12.0% 14.6%


4.1.4.2 GPI – TVET colleges

Table 16 shows that overall enrolment of female students grew more rapidly than that of male students over the 10-year period under review. Gender parity was attained in 2012 and 2013, then continued to rise in the period between 2014 and 2019, marking a significant shift towards higher female than male student participation at TVET colleges. The substantial change in GPI over the 2010–2019 period was primarily driven by changes in GPI among black African students, which increased from 1.0 in 2010 to 1.5 in 2019. For coloured students, GPI was attained in 2017 and thereafter female student enrolment surpassed that of male students. Indian/Asian and white students recorded low GPIs, showing a disparity in favour of male students.

TABLE 16: TVET college: GPI by race, 2010–2019


2010 1.0 0.9 0.3 0.4 0.9

2011 1.0 0.9 0.2 0.3 0.9

2012 1.1 0.8 0.2 0.3 1.0

2013 1.1 0.9 0.3 0.2 1.0

2014 1.2 0.9 0.3 0.3 1.1

2015 1.3 0.9 0.2 0.2 1.2

2016 1.4 0.9 0.2 0.3 1.3

2017 1.4 1.0 0.2 0.2 1.3

2018 1.4 1.1 0.3 0.2 1.3

2019 1.5 1.1 0.3 0.2 1.4




4.1.5 Access to private collegesPrivate colleges are a relatively small but important component of the PSET system. Currently, 287 private colleges are registered with the DHET (more than the current 253 TVET campuses). However, the total student enrolment at private colleges is not known for certain since only 154 of the 287 (53.0 percent) private colleges reported enrolment and other data to the DHET in 2019. It is therefore of little value to provide information about the overall participation rates of private colleges in this report. However, race and gender patterns of participation can be helpful in understanding some aspects of the private college component of the PSET system.

Figure 13 shows that more female than male students enrolled at private colleges for much of the past decade. In recent years, the gender distribution of students enrolled at these colleges shows a better balance, even when compared to that of public TVET colleges.

FIGURE 13: Percentage of students enrolled at private colleges by gender, 2010–2019

2010 2011 2012 2013 2014 2015 2016 2017 2018 20190

40%

30%

20%

10%

50%

60%

70%

80%

90%

100%42%

58%

43%

57%

44%

56%

42%

58%

52%

48%

49%

51%

49%

51%

50%

50%

48%

52%

51%

49%

Female Male

Source: DHET Statistics on Post-School Education and Training in South Africa (2013b, 2013c, 2014, 2015, 2016, 2017b, 2018, 2019b, 2020d, 2021d)

Figure 14 below shows the percentage of students enrolled at private colleges by race for the period 2010 to 2019. Most of the students enrolled at these colleges were black African in the 10-year period under review. The composition by race has generally remained stable in this period.


FIGURE 14: Percentage of students enrolled at private colleges by race, 2010–2019

2010 2011 2012 2013 2014 2015 2016 2017 2018 2019Coloured 6% 6.3% 7.4% 6.2% 6.8% 5.4% 4.4% 5.6% 5.2% 5.1%

Indian 4% 3.4% 3.4% 3.6% 9.3% 3.0% 3.7% 3.1% 3.5% 3.2%

White 10% 11.0% 7.0% 8.6% 7.7% 6.0% 7.8% 8.5% 9.1% 9.9%

Black African 80% 79.4% 82.2% 81.6% 76.2% 85.6% 84.1% 82.8% 82.2% 81.8%

0

40%

30%

20%

10%

50%

60%

70%

80%

90%

100%

Source: DHET Statistics on Post-School Education and Training in South Africa (2013b, 2013c, 2014, 2015, 2016, 2017b, 2018, 2019b, 2020d, 2021d)

4.1.6 Access to CET collegesCET colleges constitute an effort to support those with lower levels of education, both in terms of their labour market prospects and their broader functioning in society. These are so-called ‘second-chance’ institutions, offering education and training opportunities to youth and adults who did not, for whatever reason, have access to sufficient education and training earlier in their lives. There are currently nine CET colleges in South Africa, with one in each province. The White Paper for Post-School Education and Training (DHET, 2013a) envisages one million students enrolled at CET colleges by 2030.

4.1.6.1 GER – CET colleges

Table 17 shows the participation rate of youth and young adults by GER at CET colleges during the period 2010–2019. The GER in this instance is calculated as the total headcount enrolment (regardless of age) relative to the size of the national population aged 15–35 years. Although CET colleges target both youth and adults for enrolment to its programmes, the 15–35 years age group was selected for the calculation of this GER because it is currently the dominant age group among CET college-going students. As Table 17 indicates, the GER at CET colleges declined from 1.5 percent in 2010 to 0.8 percent in 2019. This change is concerning, especially since the number of persons who are NEET has been increasing year on year.

The participation of students at CET colleges is skewed towards females, as demonstrated by the higher female GER for the period under review. The female GER was 1.1 percent in 2019, whereas the male GER was only 0.5 percent.


TABLE 17: CET colleges: GER by gender, 2010–2019 (%)

YEAR FEMALE MALE TOTAL

2010 2.1 0.8 1.5

2011 2.1 0.8 1.4

2012 2.1 0.8 1.5

2013 1.7 0.7 1.2

2014 1.8 0.7 1.3

2015 1.9 0.7 1.3

2016 1.8 0.7 1.3

2017 1.7 0.7 1.2

2018 0.7 0.2 0.512

2019 1.1 0.5 0.8


4.1.6.2 GPI – CET colleges

The extremely high GPI at CET colleges is a matter of concern, because it indicates that the level of male participation at CET colleges is significantly lower than that of female students. Table 18 shows that the CET college GPI stood at 2.2 in 2019. Disparity in favour of female students is likely to continue given the consistent trend over time. The reasons for this high level of difference are not quite understood as yet and therefore require deeper research.

TABLE 18: CET colleges: Trend in GPI, 2010–2019

YEAR 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019

GPI 2.6 2.6 2.6 2.4 2.6 2.7 2.6 2.4 3.5 2.2

Sources: DHET Statistics on Post-School Education and Training (2013b, 2013c, 2014, 2015, 2016, 2017b, 2018, 2019b, 2020d, 2021d); Stats SA mid-year population estimates (2020); TVET Management Information System (2021e)


4.1.7 Students living with disabilities participating at PSET institutionsIn the South African context, disability represents an important dimension for evaluating equity in and the transformation of the PSET system. The White Paper for Post-School Education and Training (DHET, 2013a) acknowledges that “levels of commitment toward people with a disability vary considerably between institutions, as do the resources allocated to addressing disability issues. TVET colleges in particular lack the capacity, or even the policies, to cater for disabled students and staff”.

The participation of students living with disabilities in the PSET sector is, therefore, unsurprisingly low. Although little formal evidence is available about the reasons for the low levels of participation, it is generally known that the absence of proactive interventions and the lack of capacity and resources contribute to this phenomenon.

12 The GETC: ABET Level 4 registration data for examinations were used as a proxy for reporting on enrolment at CET colleges.


Tabl

e 19

show

s tha

t in

2019

, abo

ut 1

6 00

013 st

uden

ts li

ving

with

disa

bilit

ies w

ere

enro

lled

at P

SET

inst

itutio

ns, a

ccou

ntin

g fo

r 0.8

per

cent

of t

otal

stud

ent e

nrol

men

t for

the

year

. Fro

m 2

016

to 2

019,

the

prop

ortio

n of

stud

ents

livi

ng w

ith d

isabi

litie

s who

par

ticip

ated

in P

SET

rem

aine

d co

nsist

ently

low

, ran

ging

bet

wee

n 0.

6 pe

rcen

t and

0.8

per

cent

. G

iven

that

the

prop

ortio

n of

per

sons

livi

ng w

ith a

disa

bilit

y re

lativ

e to

the

popu

latio

n ag

ed 1

5–35

yea

rs is

6.4

per

cent

,14 it

is o

f con

cern

that

con

com

itant

pro

port

ions

are

not

pa

rtic

ipat

ing

in th

e PS

ET s

yste

m. T

able

20

high

light

s th

e sh

are

of th

e po

pula

tion

that

live

s w

ith d

isabi

litie

s re

lativ

e to

stu

dent

s en

rolle

d at

eac

h in

stitu

tion

type

. The

tabl

e re

veal

s th

at th

e pa

rtic

ipat

ion

rate

s of

per

sons

livi

ng w

ith d

isabi

litie

s at

pub

lic u

nive

rsiti

es (3

.8 p

erce

nt),

TVET

col

lege

s (1

.3 p

erce

nt),

and

priv

ate

colle

ges

(0.6

per

cent

) are

ab

ysm

ally

low

com

pare

d to

the

over

all p

artic

ipat

ion

rate

s at t

hese

inst

itutio

ns re

ferr

ed to

in th

e ab

ove

sect

ions

.

TABL

E 19

: Enr

olm

ent o

f stu

dent

s liv

ing

with

disa

bilit

ies a

t PSE

T in

stitu

tions

, 201

6–20

19

YEAR

PUBL

IC U

NIV

ERSI

TIES

TVET

CO

LLEG

ESCE

T CO

LLEG

ESPR

IVAT

E CO

LLEG

ESTO

TAL

PSET

TOTA

L EN

ROLM

ENT

STUD

ENTS

LI

VING

WIT

H A

DISA

BILI

TY

% O

F ST

UDEN

TS

LIVI

NG W

ITH

A DI

SABI

LITY

TOTA

L EN

ROLM

ENT

STUD

ENTS

LI

VING

WIT

H A

DISA

BILI

TY

% O

F ST

UDEN

TS

LIVI

NG W

ITH

A DI

SABI

LITY

TOTA

L EN

ROLM

ENT

STUD

ENTS

LI

VING

WIT

H A

DISA

BILI

TY

% O

F ST

UDEN

TS

LIVI

NG W

ITH

A DI

SABI

LITY

TOTA

L EN

ROLM

ENT

STUD

ENTS

LI

VING

WIT

H DI

SABI

LITI

ES

% O

F ST

UDEN

TS

LIVI

NG W

ITH

A DI

SABI

LITY

TOTA

L EN

ROLM

ENT

STUD

ENTS

LI

VING

WIT

H DI

SABI

LITI

ES

% O

F ST

UDEN

TS

LIVI

NG W

ITH

A DI

SABI

LITY

2016

975

837

7 52

50.

8%70

5 39

72

639

0.4%

273

431

2 38

00.

9%

No d

ata

1 95

4 66

512

544

0.6%

2017

1 03

6 98

48

004

0.8%

688

028

2 15

90.

3%25

8 19

92

592

1.0%

1 98

3 21

112

755

0.6%

2018

1 08

5 56

89

040

0.8%

657

133

2 08

40.

3%No

dat

a1

742

701

11 1

240.

6%

2019

1 07

4 91

210

753

1.0%

673

490

3 59

00.

5%15

1 13

61

763

1.17

%1

899

538

16 1

060.

8%

Sour

ces:

DHET

CLC

ann

ual s

urve

ys (2

016–

2017

); DHE

T Sta

tistic

s on

Post-

Scho

ol Ed

ucat

ion

and

Train

ing

in So

uth

Afric

a (2

018,

2019

b, 20

20d,

2021

d)); D

HET H

ighe

r Edu

catio

n M

anag

emen

t Inf

orm

atio

n Sy

stem

(202

1b); D

HET T

VET

Man

agem

ent I

nfor

mat

ion

Syste

m (2

021e

)

TABL

E 20

: Num

ber a

nd sh

are

of th

e po

pula

tion

for p

erso

ns a

nd st

uden

ts li

ving

with

disa

bilit

ies,

2019

INST

ITUT

ION

TYPE

STUD

ENTS

LIV

ING

WIT

H D

ISAB

ILIT

IES

PERS

ON

S LI

VIN

G W

ITH

DIS

ABIL

ITIE

S IN

TH

E PO

PULA

TIO

NTO

TAL

POPU

LATI

ON

PER

AGE

GRO

UP%

OF

STUD

ENTS

LIV

ING

WIT

H D

ISAB

ILIT

IES

AS A

PRO

PORT

ION

OF

PERS

ON

S LI

VIN

G W

ITH

DIS

ABIL

ITIE

S IN

TH

E PO

PULA

TIO

N

% O

F PE

RSO

NS

LIVI

NG

WIT

H D

ISAB

ILIT

IES

IN

THE

POPU

LATI

ON

Publ

ic un

iver

sitie

s10

753

283

051

4 87

0 41

23.

8%5.

8%

TVET

colle

ges

3 59

027

8 20

44

560

703

1.3%

6.1%

Priv

ate

colle

ges

1 76

327

8 20

44

560

703

0.6%

6.1%

Sour

ces:

DHET

Stat

istics

on

Post-

Scho

ol Ed

ucat

ion

and

Train

ing

in So

uth

Afric

a ( 2

018,

2019

b, 20

20d,

2021

d); D

HET H

ighe

r Edu

catio

n M

anag

emen

t Inf

orm

atio

n Sy

stem

(202

1b);

DHET

TVET

Man

agem

ent I

nfor

mat

ion

Syste

m (2

021e

)

Note

: The

sam

e po

pulat

ion

age

grou

ps as

thos

e us

ed to

calcu

late

the

GERs

for e

ach

inst

itutio

n ty

pe w

ere

used

for t

otal

popu

latio

ns: 1

5–35

year

for C

ET co

llege

s; 16

–20

year

s for

TVET

and

priva

te co

llege

s; an

d 20

–24

year

s for

uni

versi

ties.

13

This

figur

e ex

clude

s dat

a for

CET

colle

ges,

since

ther

e w

ere

no d

ata f

or 2

018

and

2019

.14

Th

e to

tal n

umbe

r of p

erso

ns liv

ing

with

disa

bilit

ies i

n th

e po

pulat

ion

(age

d 15

–35)

in 2

019

was

1 3

77 9

42, a

nd th

e to

tal p

opul

atio

n (a

ged

15–3

5) w

as 2

1 50

5 96

7 in

201

9. 1

377

942

/21

505

967*

100

= 6.

4 pe

rcen

t (St

ats S

A Ge

nera

l Hou

seho

ld S

urve

y, 20

19).


4.1.8 Foreign nationals participating at PSET institutionsThe presence of foreign students in the South African PSET system is part of a broader globalisation process and represents an attempt to transform the system. This process seeks to configure a new PSET system that opens up education and training institutions to a globalised world of knowledge, employment, and investments relating to the production of knowledge. A fundamental aspect of this globalisation process is student travel mobility for South African students going abroad as much as for foreign students coming to South Africa who seek to begin or finish their post-school studies.

Table 21 shows that, in 2019, approximately 80 000 foreign students enrolled at South African PSET institutions,15 constituting about 4.1 percent of all students enrolled at these institutions. Table 21 also shows that private universities enrolled a higher proportion of foreign students in relation to their total student population compared to public universities and TVET colleges.

TABLE 21: Number of foreign students enrolled at South African PSET institutions by type of institution, 2019

INSTITUTION TOTAL ENROLMENT AT PSET INSTITUTIONS

NUMBER OF FOREIGN STUDENTS ENROLLED AT

SOUTH AFRICAN PSET INSTITUTIONS

FOREIGN STUDENTS AS A % OF TOTAL STUDENTS

ENROLLED AT PSET INSTITUTIONS

Public universities 1 074 912 58 852 5.5%

Private universities 208 978 16 554 7.9%

TVET colleges 673 490 4 361 0.6%

Total 1 957 380 79 767 4.1%

Sources: DHET Statistics on Post-School Education and Training in South Africa (2021d); DHET TVET Management Information System (2021e)

Table 22 shows that approximately 59 000 foreign students were enrolled at South African public universities, constituting 5.5 percent of their total student population. The majority of these students (67.1 percent) were nationals from the Southern African Development Community (SADC) region, mainly from Zimbabwe and Namibia. Enrolment of foreign students at public universities began to decline from 2016 onwards (decreasing from 69 000 students in 2016 to 59 000 students in 2019).

15 ‘PSET institutions’ in this context includes only universities (both public and private) and TVET colleges. It thus excludes CET colleges since the applicable data were not available for them.


TABLE 22: Number and share of foreign students enrolled at public universities by country, 2016–2019

COUNTRY2016 2017 2018 2019

NUMBER % NUMBER % NUMBER % NUMBER %

Zimbabwe 25 642 37.0% 25 859 38.3% 23 983 37.5% 21 693 36.9%

Namibia 5 812 8.4% 5 481 8.1% 4 657 7.3% 4 350 7.4%

Nigeria 4 062 5.9% 4 031 6.0% 3 961 6.2% 3 768 6.4%

Democratic Republic of Congo 3 530 5.1% 3 679 5.5% 3 723 5.8% 3 662 6.2%

Lesotho 3 437 5.0% 3 499 5.2% 3 494 5.5% 3 341 5.7%

Kingdom of Eswatini 3 651 5.3% 3 462 5.1% 3 151 4.9% 2 933 5%

Zambia 1 773 2.6% 1 633 2.4% 1 483 2.3% 1 351 2.3%

Botswana 1 873 2.7% 1 624 2.4% 1 448 2.3% 1 315 2.2%

Kenya 1 365 2.0% 1 321 2.0% 1 220 1.9% 1 155 2%

Congo 967 1.4%

Ghana 1 054 1.6% 1 066 1.8%

Malawi 873 1.5%

United States of America 1 465 2.1%

Other foreign countries 16 750 24.1% 15 878 23.5% 15 844 24.7% 13 345 22.7%

Total 69 360 100.0% 67 434 100.0% 64 018 100.0% 58 852 100.0%

Source: DHET Statistics on Post-School Education and Training in South Africa (2018, 2019b, 2020d, 2021d)

Table 23 shows that during the 2016–2019 period, the majority of foreign students at public universities were enrolled through the contact mode of attendance, with the exception of Zimbabwean students, the majority of whom had enrolled for distance learning. The proportion of foreign students enrolled for the contact mode of study increased from 60.2 percent in 2016 to 65.9 percent in 2019.


TABL

E 23

: Num

ber a

nd sh

are

of fo

reig

n st

uden

ts e

nrol

led

at p

ublic

HEI

s by

atte

ndan

ce m

ode

and

coun

try,

2016

–201

9

COUN

TRY

2016

2017

2018

2019

CON

TACT

DIS

TAN

CECO

NTA

CTD

ISTA

NCE

CON

TACT

DIS

TAN

CECO

NTA

CTD

ISTA

NCE

NUM

BER

%N

UMBE

R%

NUM

BER

%N

UMBE

R%

NUM

BER

%N

UMBE

R%

NUM

BER

%N

UMBE

R%

Zim

babw

e10

959

42.7

%14

683

57.3

%11

144

43.1

%14

715

56.9

%10

897

45.4

%13

086

54.6

%10

617

48.9

%11

076

51.1

%

Nam

ibia

2 64

745

.5%

3 16

554

.5%

2 66

848

.7%

2 81

351

.3%

2 53

154

.3%

2 12

645

.7%

2 38

554

.8%

1 96

545

.2%

Nige

ria3

077

75.8

%98

524

.2%

3 14

277

.9%

889

22.1

%3

130

79.0

%83

121

.0%

3 13

783

.3%

631

16.7

%

Dem

ocra

tic

Repu

blic

of C

ongo

2 89

782

.1%

633

17.9

%2

961

80.5

%71

819

.5%

3 00

680

.7%

717

19.3

%2

990

81.6

%67

218

.4%

Leso

tho

2 63

976

.8%

798

23.2

%2

712

77.5

%78

722

.5%

2 73

178

.2%

763

21.8

%2

634

78.8

%70

721

.2%

King

dom

of

Esw

atin

i2

052

56.2

%1

599

43.8

%1

893

54.7

%1

569

45.3

%1

814

57.6

%1

337

42.4

%1

835

62.6

%1

098

37.4

%

Zam

bia

1 11

162

.7%

662

37.3

%1

056

64.7

%57

735

.3%

1 01

868

.6%

465

31.4

%99

773

.8%

354

26.2

%

Bots

wan

a1

052

56.2

%82

143

.8%

955

58.8

%66

941

.2%

878

60.6

%57

039

.4%

853

64.9

%46

235

.1%

Keny

a1

091

79.9

%27

420

.1%

1 08

081

.8%

241

18.2

%1

016

83.3

%20

416

.7%

996

86.2

%15

913

.8%

Cong

o70

673

.0%

261

27 %

Ghan

a71

467

.7%

340

32.3

%76

571

.8%

301

28.2

%

Mal

awi

695

79.6

%17

820

.4%

Unite

d St

ates

of

Amer

ica1

367

93.3

%98

6.7%

Oth

er fo

reig

n co

untri

es12

863

76.8

%3

887

23.2

%12

410

78.2

%3

468

21.8

%12

781

80.7

%3

063

19.3

%10

879

81.5

%2

466

18.5

%

Tota

l41

755

60.2

%27

605

39.8

%40

727

60.4

%26

707

39.6

%40

516

63.3

%23

502

36.7

%38

783

65.9

%20

069

34.1

%

Sour

ce: D

HET S

tatis

tics o

n Po

st-Sc

hool

Educ

atio

n an

d Tra

inin

g in

Sout

h Af

rica

(201

8, 20

19b,

2020

d, 20

21d)


Table 24 shows that from 2016 to 2019, the majority of foreign students who had enrolled at South African private universities were from Namibia (28.5 percent) and Zimbabwe (20.2 percent).

TABLE 24: Number and share of foreign students enrolled at private universities by country, 2016–2019

COUNTRY2016 2017 2018 2019

NUMBER % NUMBER % NUMBER % NUMBER %

Zimbabwe 2 159 13.2% 3 884 23.7% 3 352 20.3% 3 338 20.2%

Namibia 4 582 28.0% 5 101 31.1% 4 850 29.4% 4 723 28.5%

Nigeria 293 1.8% 271 1.7% 318 1.9% 347 2.1%

Kingdom of Eswatini 1 387 8.5% 1 503 9.2% 1 497 9.1% 1 409 8.5%

Democratic Republic of Congo

639 3.9% 416 2.5% 622 3.8% 653 3.9%

Lesotho 345 2.1% 586 3.6% 321 1.9% 240 1.4%

Botswana 841 5.1% 720 4.4% 664 4% 485 2.9%

Zambia 595 3.6% 569 3.5% 466 2.8% 360 2.2%

Kenya 108 0.7% 221 1.3% 209 1.3% 149 0.9%

United States of America 72 0.4% 94 0.6% 102 0.6% 130 0.8%

Other foreign countries 5 372 32.8% 3 022 18.4% 4 095 24.8% 4 720 28.5%

Total 16 393 100.0% 16 387 100.0% 16 496 100.0% 16 554 100.0%

Source: DHET Statistics on Post-School Education and Training in South Africa (2018, 2019b, 2020d, 2021d)

Table 25 indicates that throughout the 2016–2019 period, students from Lesotho, Namibia, and Zimbabwe were the most dominant among foreign students enrolled at South African TVET colleges. In 2019, Zimbabwean students accounted for 26.5 percent of all foreign students at these colleges, followed by Basotho students at 19 percent, and Namibian students at 17.5 percent.


TABL

E 25

: Num

ber a

nd sh

are

of fo

reig

n st

uden

ts e

nrol

led

at T

VET

colle

ges b

y co

untr

y, 20

16–2

019

COUN

TRY

2016

2017

2018

2019

NUM

BER

%N

UMBE

R%

NUM

BER

%N

UMBE

R%

Leso

tho

756

23.6

%1

010

9.5%

972

13.2

%82

9 19

%

Nam

ibia

591

18.4

%94

6 8.

9%1

037

14.1

%76

5 17

.5%

Zim

babw

e54

8 17

.1%

889

8.4%

1 06

1 14

.4%

1 15

4 26

.5%

Rest

of A

frica

1654

2 16

.9%

6 67

4 62

.9%

3 00

4 40

.8%

471

10.8

%

King

dom

of E

swat

ini

228

7.1%

206

1.9%

255

3.5%

214

4.9%

Ango

lan

130

4.1%

266

2.5%

202

2.7%

138

3.2%

Oth

er a

nd th

e re

st o

f Oce

ania

127

4.0%

264

2.5%

432

5.9%

410

9.4%

Moz

ambi

que

96

3.0%

86

0.8%

71

1.0%

64

1.5%

Mal

awi

46

1.4%

56

0.5%

43

0.6%

39

0.9%

Zam

bia

44

1.4%

31

0.3%

42

0.6%

42

1.0%

Bots

wan

a35

1.

1%44

0.

4%40

0.

5%48

1.

1%

Asia

n co

untri

es23

0.

7%66

0.

6%51

0.

7%35

0.

8%

SADC

(exc

ept S

outh

Afri

ca)

19

0.6%

34

0.3%

36

0.5%

54

1.2%

Dem

ocra

tic R

epub

lic o

f Con

go10

0.

3%7

0.1%

9 0.

1%14

0.

3%

Tanz

ania

5 0.

2%3

0.0%

2 0.

0%4

0.1%

Mau

ritiu

s4

0.1%

3 0.

0%2

0.0%

0.0%

Aust

ralia

and

oth

er O

cean

ia co

untri

es1

0.0%

1 0.

0%n/

a0.

0%0.

0%

Euro

pean

coun

tries

1 0.

0%12

0.

1%11

0.

1%17

0.

4%

Nort

h Am

erica

n co

untri

es0.

0%2

0.0%

5 0.

1%5

0.1%

Unsp

ecifi

ed66

0.

9%57

1.

3%

Sout

h/Ce

ntra

l Am

erica

n co

untri

es0.

0%7

0.1%

16

0.2%

1 0.

0%

Gran

d to

tal

3 20

6 10

0.0%

10 6

07

100.

0%7

357

100.

0%4

361

100.

0%

Sour

ce: D

HET T

VET M

anag

emen

t Inf

orm

atio

n Sy

stem

(202

1e)

16

Afric

an co

untri

es n

ot al

read

y inc

lude

d se

para

tely.


4.1.9 Access to SETA-supported workplace-based learning programmes

Table 26 shows that the number of workers and unemployed persons registered for SETA-supported learning programmes (learnerships, internships, and skills programmes) increased from 135 229 in 2011/12 to 222 210 in 2019/20. This represents a 6.5 percent average annual growth rate since 2011/12. The number of certificated individuals grew at an average annual growth rate of 5.4 percent over the same period. However, the numbers of both registered and certificated individuals declined from 2018/19 to 2019/20, except for those who were certificated through internship programmes.

4.1.10 Persons in the population who have access to the internetThe COVID-19 pandemic has presented education and training systems in South Africa with huge and unprecedented challenges, while simultaneously creating opportunities for the re-envisioning of these systems. The pandemic exacerbated pre-existing education disparities by reducing the opportunities for the most vulnerable in the country to access education. While the pandemic stimulated innovation in the PSET sector, with many PSET institutions (especially universities) shifting teaching and learning to online platforms as a replacement for contact learning, online learning solutions failed to reach millions of students due to their lack of access to the internet as well as devices such as computers, laptops, and smartphones, which are needed for online education.

Table 27 shows that about 72.0 percent of persons in the 15–24 age group had access to the internet in 2019, with a higher proportion of those with access being female. Although access to the internet for this age group has increased substantially over the past six years, the shift is inadequate in light of the importance of the internet for not only teaching and learning but also for seeking employment, developing life skills, and being informed about important matters.


TABL

E 26

: Num

ber o

f wor

kers

and

une

mpl

oyed

per

sons

regi

ster

ed a

nd ce

rtifi

cate

d at

SET

A-su

ppor

ted

lear

ning

pro

gram

mes

by

prog

ram

me

type

, 201

1/12

–201

9/20

YEAR

REGI

STER

EDCE

RTIF

ICAT

ED

LEAR

NER

SHIP

SIN

TERN

SHIP

SSK

ILLS

PR

OGR

AMM

ESTO

TAL

REGI

STER

EDLE

ARN

ERSH

IPS

INTE

RNSH

IPS

SKIL

LS

PRO

GRAM

MES

TOTA

L CE

RTIF

ICAT

ED

2011

/12

43 8

71

3 45

2 87

906

13

5 22

9 29

197

87

8 87

527

11

7 60

2

2012

/13

50 8

85

6 12

7 74

587

13

1 59

9 37

158

2

195

86 4

91

125

844

2013

/14

75 7

82

8 01

7 92

508

17

6 30

7 38

796

2

510

109

547

150

853

2014

/15

77 9

31

12 0

06

137

880

227

817

40 8

91

3 66

3 10

6 45

9 15

1 01

3

2015

/16

94 3

69

13 1

35

123

593

231

097

43 3

22

3 35

2 12

7 14

4 17

3 81

8

2016

/17

101

447

17 2

16

131

017

249

680

58 0

80

6 77

7 11

6 14

1 18

0 99

8

2017

/18

111

681

12 9

35

144

531

269

147

48 0

02

6 49

6 12

2 97

9 17

7 47

7

2018

/19

105

548

15 4

82

150

674

271

704

61 8

41

6 12

3 14

4 46

0 21

2 42

4

2019

/20

81 9

88

11 7

84

128

438

222

210

57 8

88

7 71

1 11

4 03

2 17

9 63

1

Aver

age

annu

al g

row

th

from

201

1/12

to 2

019/

208.

1%16

.6%

4.9%

6.4%

8.9%

31.2

%3.

4%5.

4%

Sour

ce: D

HET S

tatis

tics o

n Po

st-Sc

hool

Educ

atio

n an

d Tra

inin

g in

Sout

h Af

rica

(201

3c, 2

014,

2015

, 201

6, 20

17b,

2018

, 201

9b, 2

020d

, 202

1d)

TABL

E 27

: Per

cent

age

of th

e po

pula

tion

who

hav

e ac

cess

to th

e in

tern

et b

y ag

e an

d ge

nder

, 201

4–20

19

YEAR

15–2

425

–34

35–4

445

–54

55–6

4

MAL

E FE

MAL

ETO

TAL

MAL

EFE

MAL

ETO

TAL

MAL

EFE

MAL

ETO

TAL

MAL

EFE

MAL

ETO

TAL

MAL

EFE

MAL

ETO

TAL

%%

2014

55.1

56

.9

56

56.0

57

.7

56.9

53

.2

55.4

54

.3

52.8

57

.4

55.3

51

.5

50.7

51

.1

2015

61.3

64

.4

62.9

60

.5

62.8

61

.6

57.9

61

.2

59.5

57

.2

62.5

60

.0

55.8

56

.5

56.2

2016

66.5

69

.6

68.1

66

.5

68.8

67

.7

63.6

69

.0

66.2

61

.2

66.3

63

.9

58.7

62

.8

61.0

2017

68.7

71

.0

69.8

67

.9

72.1

70

.0

65.0

69

.7

67.3

63

.0

68.1

65

.7

61.5

64

.6

63.2

2018

71.5

74

.4

73.0

72

.6

75.0

73

.8

68.6

72

.3

70.4

66

.2

71.9

69

.1

63.6

66

.2

65.0

2019

70.3

73

.5

71.9

69

.7

73.5

71

.6

67.3

71

.7

69.5

66

.0

71.7

69

.0

63.9

65

.5

64.8

Sour

ce: S

tats

SA G

ener

al H

ouse

hold

Surv

ey (2

014,

2015

, 201

6, 20

17, 2

018,

2019

)


Table 28 shows that close to 77 percent of the 15–24-year-old population had access to mobile phones in 2019, with more females than males in possession of these devices. Table 28 reveals a disturbing trend in relation to mobile phone access for the 15–24-year-old age group, with lower access in 2019 compared to preceding years.

TABLE 28: Percentage of the population who have access to mobile phones, by gender and age, 2014–2019YE

AR

15–24 25–34 35–44 45–54 55–64 M

ALE

FEM

ALE

TOTA

L

MAL

E

FEM

ALE

TOTA

L

MAL

E

FEM

ALE

TOTA

L

MAL

E

FEM

ALE

TOTA

L

MAL

E

FEM

ALE

TOTA

L

%

2014 77.2 81.9 79.5 89.9 93.9 91.9 90.8 94.1 92.4 87.6 90.8 89.3 84.6 83.3 83.9

2015 79.0 82.2 80.6 90.4 94.2 92.3 91.8 94.5 93.1 89.2 91.7 90.6 86.6 86.6 86.6

2016 79.0 83.3 81.2 91.2 94.6 92.9 91.9 94.4 93.1 90.0 91.6 90.9 86.6 87.6 87.2

2017 78.0 82.1 80.1 91.0 95.3 93.2 91.7 94.9 93.3 91.0 93.3 92.2 89.4 88.2 88.7

2018 79.1 84.0 81.6 91.7 96.0 93.8 92.5 95.9 94.2 91.1 93.5 92.3 89.5 89.5 89.5

2019 73.4 79.6 76.5 86.0 91.3 88.7 89.5 91.6 90.6 88.4 90.6 89.5 86.4 87.0 86.7

Source: Stats SA General Household Survey (2014, 2015, 2016, 2017, 2018, 2019)

5Quality of PSET provisioning


5.1 Quality of the PSET system as measured by student:staff ratio and the qualifications of its lecturing staff

Providing an exact definition of quality (and, therefore, the identification of the indicators of quality) is more difficult than is the case for access. The nature of some inputs to the PSET system can, however, provide some signals regarding the quality of teaching and learning. For example, a measure of adequate and well-qualified staff members who have good pedagogic competencies and the appropriate content knowledge can provide some insights into the quality of education. In this report, the share of academic staff members with a PhD degree who teach at universities is used as an important indicator of staff competence. The ratio between full-time equivalent18 (FTE) student enrolment and the number of academic staff provides an indication of the ability of staff to provide quality learning inputs as well as high-quality research outputs.

The NDP acknowledges that academic professions require renewal if South African universities are to expand, compete in, and drive the knowledge society and economy (National Planning Commission, 2012). The NDP also notes that there is a shortage of academics, especially in the human, natural, engineering, and actuarial sciences.

Table 29 shows that the FTE student:staff ratio remained relatively stable during the period 2010–2019. It fluctuated between a low of 25.5 in 2016 and a high of 29.1 in 2019. In relative terms, the number of FTE students increased by 2.7 percent per annum, while the number of FTE staff increased by 2.0 percent per annum over the same period, indicating that the increase in FTE student enrolment growth outpaced the expansion of public universities’ academic staff complement. This trend signals a possible decline in the quality of teaching and learning in universities. However, deeper research needs to be undertaken to explore the effects of growing student:staff ratios on the quality of education.

A new factor to consider is the widespread adoption of blended approaches to teaching and learning as a result of the COVID-19 pandemic, which includes the use of online approaches. Blended approaches to teaching and learning (a mix of online plus contact) will undoubtedly affect how student:staff ratios are to be understood and interpreted, particularly when comparing trend data. Nonetheless, the rising student:staff ratios over the past three years remain a point of concern, since they negatively affect not only the quality of teaching and learning but also the quantity or quality of research output. In order to ensure quality in the university education system, the academic staff complement actually needs to grow further, particularly in the context of student enrolment targets projected in the NDP.

18 The number of FTE students adjusts for the number of credits each student is enrolled for in a given year. Thus, a student enrolled for only half the required credits of a full academic year will be counted as half an FTE student.

5 | QUALIT Y OF PSE T PROVISIONING | 65

TABLE 29: Public universities: FTE students to FTE staff ratio, 2010–2019

YEAR FTE STUDENTS FTE STAFF STUDENT:STAFF RATIO

2010 600 002 21 968 27.3

2011 628 410 23 274 27.0

2012 634 549 24 089 26.3

2013 665 857 24 282 27.4

2014 666 946 24 806 26.9

2015 678 842 25 814 26.3

2016 685 297 26 894 25.5

2017 731 602 27 938 26.2

2018 775 808 28 054 27.7

2019 760 362 26 070 29.1

AVERAGE ANNUAL GROWTH

2010–2019 2.7% 2.0%

Source: DHET Higher Education Management Information System (2021b)

The level of academic staff qualifications is often regarded as a useful measure of the quality of education. The achievement of a PhD degree, in particular, is seen as a gold standard for good-quality teaching and learning as well as for the production of good-quality research. The NDP therefore set a target that 75 percent of all academic staff at public universities should have a doctoral degree by 2030. Figure 15 indicates that the proportion of university academic staff with a PhD qualification during the period 2010–2019 increased by 12.0 percentage points, from 35.7 percent in 2010 to 47.7 percent in 2019. Despite this positive trend, it remains a matter of concern that less than half of the university academic staff in South Africa have a PhD degree.

FIGURE 15: Share of academic staff with a PhD in universities, 2010–2019

2010 2011 2012 2013 2014 2015 2016 2017 2018 20190%

10%

20%

30%

40%

50%

60%

% o

f aca

dem

ic st

aff

35.7 37.5 38.641.1 42.9 43.8 44.9 46.0

48.0 47.7


The success of the PSET

system

6

6 | THE SUCCESS OF THE PSE T SYSTEM | 67

6.1 Graduate outputs in the PSET system

The better the quality of PSET in all forms and at all levels, the greater the likelihood of systemic and institutional efficiency and success in terms of regular and sustained student progress and accomplishment as well as enhanced career prospects. However, it is difficult to define success for the PSET system as a whole. Success speaks to an adequate number of graduates across all levels of the PSET system, in all relevant qualifications and programmes (DHET, 2021). It addresses the notion of completion, especially in appropriate qualifications and programmes, and thereby focuses on the number of graduates who complete PSET qualifications and programmes. Issues pertaining to efficiency and quality are covered in separate chapters in this report.

This section considers graduation rates (for universities) and certification rates (for TVET colleges) as two indicators related to success. Graduation rates are defined as the number of students who have graduated in a particular year, irrespective of the first year of study, divided by the total number of students enrolled at public universities in that particular year. Certification rates are defined as the number of students who successfully completed a qualification in an academic year, as a percentage of the number of candidates who were eligible to complete a qualification and who wrote the examinations in that year.

6.1.1 University graduation ratesFigure 16 shows university graduation rates by gender during the 2010–2019 period. The average university graduation rate in 2019 was 20.6 percent, reflecting an improvement from the 2010 graduation rate of 17.2 percent. University graduation rates for female students remained consistently higher than those for male students over the past decade. However, both female and male graduation rates generally improved.

FIGURE 16: Graduation rate at public universities by gender, 2010–2019

17%

16%

15%

18%

19%

20%

21%

22%

23%

perc

enta

ge

2010 2011 2012 2013 2014 2015 2016 2017 2018 2019

Male 15.9 16.1 16.0 17.3 18.0 18.3 19.3 18.8 19.2 19.1 Female 18.2 17.9 17.5 19.2 19.9 20.3 21.9 21.4 22.1 21.7 Average 17.2 17.1 16.8 18.4 19.1 19.4 20.8 20.3 20.9 20.6



Differentials in graduation rates by race in tertiary education provide important insights into racial gaps in student academic success and can therefore inform suitable policy measures and support interventions. Figure 17 shows graduation rates by race for the period 2010–2019. Despite the upsurge in the graduation rate of black African students, from 15.8 percent in 2010 to 19.9 percent in 2018, the figures for this group constantly remained below the average graduation rate. In 2019, the graduation rate of black African students declined marginally by 0.5 percentage points, to 19.4 percent. The graduation rate of their white counterparts grew from 21.7 percent in 2010 to 27.0 percent in 2019. In that year, the graduation rates of coloured, Indian/Asian, and white students were above the 20.7 percent overall graduation rate. The comparative statistics suggest that black Africans students are less likely to graduate relative to students in other race groups, while white students are more likely to graduate than students in the other race groups.

FIGURE 17: Graduation rates at public universities by race, 2010–2019

16%

14%

12%

18%

20%

22%

24%

26%

28%

perc

enta

ge

2010 2011 2012 2013 2014 2015 2016 2017 2018 2019

Black African 15.8 15.7 15.8 16.9 18.0 18.3 19.8 19.3 19.9 19.4 Coloured 18.2 17.8 18.1 18.2 19.2 19.1 20.5 19.7 20.8 21.8 Indian/Asian 15.8 16.8 17.9 19.0 19.1 19.5 21.2 22.0 23.2 24.2 White 21.7 21.8 22.5 23.6 23.8 24.3 25.4 25.4 26.4 27.0 Average 17.2 17.1 17.4 18.4 19.1 19.4 20.8 20.3 20.9 20.7


6.1.2 TVET college certification rates TVET colleges offer two main qualification types: namely, the National Certificate (Vocational), referred to as the NC(V), and the National Technical Education Diploma, referred to as the NATED. The NATED comprises six components or part-qualifications – the N1 to N6 qualifications, with each component assessed separately via a national examination. This report provides certification rates for the N3 and N6 part-qualifications and the NC(V).

Table 30 shows the N3 certification rate for the period 2013–2019. In 2019, only 68.0 percent (approximately 38 000) of students who wrote the N3 national examinations passed. Although this figure represents a significant improvement from the 2013 certification rate of 44.6 percent, it is disconcerting to note that it also reflects a significant drop from the 2017 and 2018 certification rates. The rate increased from 44.6 percent in 2013 to 83.2 percent in 2018, then decreased by over 15.0 percentage points to 68.0 percent in 2019.


TABLE 30: Examination candidates, passes, and certification rates for N3 at TVET colleges, 2013–2019

CANDIDATES WHO WROTE CANDIDATES WHO PASSED CERTIFICATION RATE

NUMBER %

2013 41 201 18 383 44.6%

2014 42 244 23 411 55.4%

2015 47 811 31 023 64.9%

2016 59 409 39 102 65.8%

2017 60 711 46 641 76.8%

2018 41 804 34 793 83.2%

2019 55 707 37 863 68.0%

Sources: DHET Statistics on Post-School Education and Training in South Africa (2015, 2016, 2017b, 2018, 2019b, 2020d, 2021d); DHET statistics on TVET, CET, and private colleges examinations (2015); DHET examination data for South African TVET, CET, and private colleges (2017)

Note: The certification rate (also known as the completion rate) is the proportion of students who successfully completed a qualification in an academic cycle, expressed as a percentage of the number of students who were eligible to complete the level and were assessed in that academic cycle.

Table 31 shows the N6 certification rate for the period 2013–2019. The number of students who wrote exit exams increased from 42 841 in 2013 to 117 641 in 2019. The certification rate for the N6 increased from 35.6 percent in 2013 to 96.4 percent in 2019, pointing to significant improvements over the period. Although N6 certification rates rose relatively consistently between 2013 and 2019, the 2018 certification rate deviates quite dramatically from this trend. At this stage, there is no explanation for the poor performance in 2018, and further research needs to be undertaken in this regard.

TABLE 31: Examination candidates, passes, and certification rates for N6 at TVET colleges, 2013–2019


NUMBER %

2013 42 841 15 268 35.6%

2014 57 014 24 396 42.8%

2015 76 378 46 569 61.0%

2016 91 772 60 642 66.1%

2017 117 086 112 508 96.1%

2018 84 212 73 377 87.1%

2019 117 641 113 393 96.4%




As indicated in Table 32, although the certification rates for NC(V) Level 4 have increased significantly, from 37.0 percent in 2013 to 49.4 percent in 2019, they remain considerably lower than the N3 and N6 certification rates shown in Tables 30 and 31 above. The certification rates for NC(V) Level 4 nonetheless increased significantly from 37.0 percent in 2013 to 53.9 percent in 2018, then decreased to 49.4 percent in 2019. This translates to an increase of 16.9 percentage points over the period under review.

TABLE 32: Examination candidates, passes, and certification rates for NC(V) Level 4 at TVET colleges, 2013–2019


NUMBER %

2013 21 930 8 114 37.0%

2014 22 176 7 624 34.4%

2015 25 645 10 308 40.2%

2016 28 104 11 716 41.7%

2017 26 519 11 377 42.9%

2018 21 978 11 837 53.9%

2019 22 126 10 920 49.4%



6.1.3 Private college certification rates Table 33 shows the certification rate for the N3 qualification at private colleges for the period 2013–2019. The rate increased by 32.7 percentage points, from 31.7 percent in 2010 to 64.4 percent in 2019. Completion rates showed an upward trend between 2013 and 2017 but decreased by about 6.0 percentage points from 64.6 percent in 2017 to 59.1 in 2018, then increased again to 64.4 percent in 2019.

TABLE 33: Examination candidates, passes, and certification rates for Report 191 N3 at private colleges, 2013–2019

YEARCANDIDATES WHO WROTE CANDIDATES WHO PASSED CERTIFICATION RATE

NUMBER %

2013 24 587 7 803 31.7%

2014 32 466 12 371 38.1%

2015 25 839 12 236 47.4%

2016 31 988 15 212 47.6%

2017 30 779 19 883 64.6%

2018 20 810 12 297 59.1%

2019 32 708 21 063 64.4%




Table 34 presents the certification rates for the N6 qualification for the period 2013–2019. The N6 qualification reflects a similar trend to the N3 qualification – its certification rates increased moderately from 2013 until 2016, then sharply from 57.0 percent in 2016 to 91.6 percent in 2017. This represents an overall increase of almost 35.0 percentage points. N6 certification rates decreased by almost 9.0 percentage points between 2017 and 2018 but increased again to 93.0 percent in 2019.

TABLE 34: Examination candidates, passes, and certification rates for N6 at private colleges, 2013–2019


NUMBER %

2013 9 211 3 316 36.0%

2014 11 664 4 675 40.1%

2015 13 076 6 556 50.1%

2016 15 155 8 638 57.0%

2017 28 267 25 906 91.6%

2018 23 359 19 354 82.9%

2019 36 144 33 597 93.0%



Contrary to the picture presented by the N3 and N6 programmes, Table 35 shows that certification rates for NC(V) Level 4 programmes declined from 43.0 percent in 2013 to 30.4 percent in 2019. As with the certification rates at TVET colleges, the certification rates for NC(V) Level 4 programmes have remained very low compared to the N3 and N6 qualifications.

TABLE 35: Examination candidates, passes, and certification rates for NC(V) Level 4 at private colleges, 2013–2019


NUMBER %

2013 540 232 43.0%

2014 529 214 40.5%

2015 499 157 31.5%

2016 579 182 31.4%

2017 446 144 32.3%

2018 424 193 45.5%

2019 171 52 30.4%


Note: Certification rate also known as completion rate is the proportion of students who successfully completed a qualification in an academic cycle, expressed as a percentage of the number of students who were eligible to complete the level and are assessed in that academic cycle.

The efficiency of the PSET

system

7

7 | THE EFFICIENCY OF THE PSE T SYSTEM | 73

Efficiency speaks to a PSET system that makes optimal use of resources, systems, and time to serve the needs of the nation (DHET, 2021c). There are several aspects to the idea of efficiency. For the purpose of this section, the two most relevant aspects include:

| Analysis of throughput, dropout, and repetition rates, as well as the average time that it takes for a graduate to complete a qualification;

| The optimal use of financial resources in order to produce the outputs and immediate outcomes of the PSET system.

7.1 How efficient is the PSET system as measured by throughput and dropout rates?

An efficient system is one that is characterised by high rates of retention (low dropout rates) among the students it admits and enables as many students as possible to complete their studies within the required minimum time frame, or as close to it as possible, without compromising quality. This section provides an analysis of the throughput rates of both public universities and TVET colleges19 as one good indicator of efficiency. Throughput rates for universities are defined as “the number of first-time entry undergraduate students of a specific cohort of a specific year who have graduated either within the minimum time, or up to two years beyond the minimum time, to the number of students in the baseline enrolments of that cohort” (CHE, 2019). The throughput rate of TVET colleges, which is currently based only on NC(V) students, is calculated by dividing the total number of students who completed NC(V) Level 4 in Year 3 of their studies by the total number of students who enrolled for NC(V) Level 2 in Year 1 (Khuluvhe & Mathibe, 2021).

7.1.1 Throughput rates for public universitiesTable 36 shows that there has been substantial and sustained improvement in the throughput rate of university undergraduate students, from 18.8 percent for the 2009 cohort to 22.9 percent for the 2012 cohort, to 29.9 percent for the 2016 cohort. These students graduated within the expected three-year time frame. Despite the noticeable improvement in throughput rates, it should be noted that there are still far too many students who take too long to complete their university degrees, thereby burdening the system in terms of funding.

19 In the case of TVET colleges, throughput rates are only provided for the NC(V) qualification. In the future, throughput rates will be provided for the N6 part-qualification.


TABLE 36: Throughput rates for first-time-entering student cohort in three-year degree programmes through contact and distance learning modes, 2009–2016 intake years

NATIONAL TOTAL: CONTACT AND DISTANCE

INTAKE YEAR Graduates (%)

YEAR 1 Year 3 Year 4 Year 5 Year 6 Year 7 Year 8 Year 9 Year 10

2009 18.8 35.1 46.0 52.0 55.7 58.1 59.7 60.9

2010 21.5 39.0 50.3 55.8 59.2 61.3 62.7

2011 20.9 38.0 48.9 54.4 57.5 59.7

2012 22.9 40.5 51.7 57.2 60.5

2013 26.6 46.2 57.6 63.4

2014 28.1 47.8 59.6 Data not available

2015 28.6 49.1

2016 29.9

Source: DHET 2000–2016 First Time Entering Undergraduate Cohort Studies for Public Higher Education Institutions (2020b)

Note: The section ‘Data not available’ requires data from the 2019 academic year and onwards. The data for this period became available in October 2020.

Table 37 shows throughput rates by the intake year of first-time-entering students in three-year undergraduate degree programmes (via contact mode only), for the 2009–2016 intake years. Throughput rates are improving overall, although very slowly. While 25.0 percent of the 2009 contact learning cohort completed their studies within the expected three-year time frame, 32.2 percent of the 2016 contact learning cohort achieved this aim. Shockingly, it took 10 years until 73.0 percent of the 2009 cohort of students enrolled for contact learning had completed their studies.

TABLE 37: Throughput rates by intake year of first-time-entering students in three-year undergraduate degree programmes (contact mode only), 2009–2016 intake years

NATIONAL TOTAL: CONTACT



2009 25.0 45.6 58.4 64.7 68.1 70.2 71.5 72.6

2010 27.9 49.4 62.4 68.4 71.5 73.3 74.6

2011 28.6 50.2 63.2 68.7 71.6 73.5

2012 29.1 50.2 62.7 68.4 71.5

2013 30.2 51.3 63.2 69.0


2015 31.9 53.6

2016 32.2




Table 38 shows that education via distance learning seems to be less efficient than contact learning. Throughput rates are lower for distance students than for contact students. For the 2009 cohort, 2.8 percent graduated within the expected three-year time frame, whereas for the 2016 cohort, 6.0 percent graduated after Year 3 of their studies. After 10 years, only 30.5 percent of the 2009 cohort of students enrolled for distance learning had completed their studies.

TABLE 38: Throughput rates by intake year of first-time-entering students in three-year undergraduate degree programmes (distance mode only), 2009–2016 intake years

NATIONAL TOTAL: DISTANCE



2009 2.8 7.8 13.6 19.0 23.1 26.6 28.7 30.5

2010 2.0 7.5 13.6 18.3 22.6 25.5 27.4

2011 1.7 7.9 13.9 19.5 23.1 25.7

2012 1.9 7.7 14.6 19.4 23.4

2013 3.4 12.8 21.0 27.3


2015 4.5 16.3

2016 6.0



An alternative way of evaluating the efficiency of the university sector is through the analysis of dropout rates. Table 39 shows the cumulative percentage of students who dropped out after successive years of study for first-time-entering student cohorts that entered three-year university programmes from 2009 to 2017. The table shows that dropout rates at universities are declining, with 10.3 percent of the 2017 cohort dropping out after one year of study compared to 16.5 percent of the 2009 student cohort. After five years, 20.8 percent of the 2009 student cohort that entered in 2009 had dropped out, relative to a 17.1 percent dropout of the student cohort that entered the system in 2014. In general, the decrease in dropout rates reflects some improvement in student retention in the system.


TABLE 39: Dropout rates by intake year of first-time-entering students in three-year undergraduate degree programmes (contact mode only), 2009–2017 intake years

NATIONAL TOTAL: CONTACT

INTAKE YEAR Dropouts (%)YEAR 1 Year 2 Year 3 Year 4 Year 5 Year 6 Year 7 Year 8 Year 9 Year 102009 16.5 19.2 20.5 20.8 22.1 22.5 22.6 22.1 21.72010 14.1 17.5 18.2 19.6 20.2 20.4 20.2 19.72011 13.8 16.3 18.3 19.7 20.2 19.9 19.52012 13.1 17.6 19.3 19.9 20.0 19.62013 15.3 19.1 18.6 18.3 18.52014 15.9 17.5 16.9 17.12015 11.8 14.7 14.8 Data not available2016 11.3 14.42017 10.3



Dropout rates are substantially higher for distance students (Table 40) than for contact students (Table 39). Table 40 shows that in 2010 (Year 2 of the study programme), 29.3 percent of the 2009 first-time-entering cohort had dropped out after their first year of study. By 2018 (after 10 years of study), 56.9 percent of this cohort had dropped out. For the 2017 first-time-entering cohort, the dropout rate after the first year of study had improved slightly, with 28.1 percent of the cohort having dropped out from their studies after the first year.

TABLE 40: Dropout rates by intake year of first-time-entering students in three-year undergraduate degree programmes (distance mode only), 2009–2017 intake years

NATIONAL TOTAL: DISTANCE

INTAKE YEAR Dropouts (%)YEAR 1 Year 2 Year 3 Year 4 Year 5 Year 6 Year 7 Year 8 Year 9 Year 102009 29.3 41.8 47.8 48.6 53.5 55.1 57.5 57.1 56.92010 31.8 44.1 47.1 53.3 55.5 58.6 58.4 58.62011 34.3 40.8 49.1 53.2 56.9 57.4 58.22012 28.8 42.6 48.1 52.9 54.5 55.82013 31.6 44.0 52.1 52.7 52.42014 26.4 38.3 45.4 45.42015 28.7 39.0 42.4 Data not available2016 29.3 36.52017 28.1




7.1.2 TVET collegesThe NC(V) qualification was introduced by the then Department of Education at public TVET colleges in 2007 in an effort to respond to the South African economy’s demand for priority skills. The NC(V) continues to be offered by TVET colleges; however, a number of stakeholders have expressed concern about the inordinate amount of time that students spend at college to complete the full NC(V) qualification.

Table 41 shows that in the 2016 academic year, 88 771 students had enrolled for the NC(V) Level 2 programme. However, only 8 135 students of this cohort completed the NC(V) Level 4 qualification after three years (in 2018). These figures mean that only 9.2 percent of all students enrolled in the NC(V) Level 2 programme in 2016 completed this qualification within the expected time frame. It is assumed that the low throughput rates are the result of a combination of repetition and dropout. This phenomenon needs to be further interrogated so that appropriate solutions could be found to this highly concerning problem.

TABLE 41: Overall throughput rate of NC(V) Level 2 students enrolled at TVET colleges in 2016

NUMBER OF STUDENTS ENROLLED FOR NC(V) LEVEL 2 IN 2016

NUMBER OF STUDENTS WHO COMPLETED NC(V) LEVEL 4 IN 2018

THROUGHPUT RATE (%)

88 771 8 135 9.2

Source: DHET Throughput Rate of TVET College Students: National Certificate Vocational (2021)

Table 42 shows that the NC(V) Level 2 throughput rate for female students was 4.6 percentage points higher than that for male students and 1.8 percentage points higher than the overall throughput rate of 9.2 percent.

TABLE 42: Throughput rate by gender, 2016–2018

GENDER NUMBER OF STUDENTS ENROLLED FOR NC(V) LEVEL 2 IN 2016

NUMBER OF STUDENTS WHO COMPLETED NC(V) LEVEL 4 IN 2018

THROUGHPUT RATE (%)

Male 35 046 2 226 6.4

Female 53 725 5 909 11.0

Overall 88 771 8 135 9.2

Source: DHET Throughput Rate of TVET College Students: National Certificate Vocational (2021)


7.2 What is the total spending on education?

The global economic impact of COVID-19 has been severe. In South Africa, the pandemic has led to a steep economic decline and accelerated the deterioration of public finances. The 2021 National Treasury Budget Review (National Treasury, 2021d) indicates that the pandemic shock is estimated to have led to a 7.2 percent contraction in GDP growth in 2020, and that the economy is projected to grow in real terms by 3.3 percent in 2021 and 2.2 percent in 2022. GDP is only expected to recover to pre-pandemic levels in late 2023. The impact of low growth on revenue collection has been considerable. Tax revenue estimates, while higher than projected in October 2020, are R213.2 billion lower than projected in the 2020 national budget. Given that the economy has not performed as expected, this report examines how these developments have affected expenditure on PSET.

7.2.1 Consolidated government spending on a select number of functions

Figure 18 shows that over the period 2017/18 to the end of 2023/24, although the proportion of consolidated government expenditure on PSET was low compared to the other social functions of government, it has risen over the past three years and is projected to increase by about 1.2 percentage points from 5.9 percent in 2017/18 to 7.1 percent in 2023/24. Figure 18 also shows a concerning drop in government expenditure on PSET from 2019/20 to 2020/21.

FIGURE 18: Percentage of consolidated government expenditure across a select number of functions, 2017/18–2023/24

0%

6%

4%

2%

8%

10%

12%

% o

f con

solid

ated

gov

ernm

ent e

xpen

ditu

re

2017/18 2018/19 2019/20 2020/21 2021/22 2022/23 2023/24

Basic Education 16.7 16.7 15.9 14.6 15.,6 15.9 15.9

Health 13.8 14.3 13.6 13.6 14.2 14.1 13.9

PSET 5.9 6.3 6.8 6.1 6.8 7.1 7.1

Social Protection 12.8 12.9 13.5 14.1 13.1 13.8 13.7

14%

16%

18%

Source: National Treasury Medium Term Budget Policy Review Expenditure Priorities (2018, 2019, 2020); National Treasury Consolidated Budget Spending Plans (2021a)

Notes:1. Expenditure on education for the years 2016/17 to 2019/20 is the audited outcome.2. Expenditure on education for the year 2020/21 is the revised estimate.3. Expenditure on education for the years 2021/22 to 2022/23 is the mid-term estimate.4. All values are based on nominal values from the source.


7.2.2 Overall government spending on the schooling system versus the post-schooling system

The UNESCO Education 2030: Incheon Declaration and Framework for Action (2015) endorses the following two key benchmarks for public spending on education:

| Allocating at least 4.0–6.0 percent of GDP to education. | Allocating at least 15.0–20.0 percent of public spending to education.

Figure 19 below provides the consolidated government expenditure on total education (adding together expenditure on the schooling system and the post-schooling system) as a percentage of total government expenditure as well as GDP. By UNESCO standards, South Africa continues to spend a large share of its wealth on education. Spending on education as a proportion of both overall government expenditure (22.7 percent in 2019/20) and GDP (7.2 percent in 2019/20) far exceeds the benchmarks set by UNESCO for all countries in the world. It is concerning that while government expenditure on PSET will increase, spending in relation to GDP is expected to decline quite substantially in the 2021/22–2021/24 medium-term expenditure framework.

FIGURE 19: Consolidated government spending on education as percentage of total government expenditure and GDP, 2017/18-2023/24

2017/18 2018/19 2019/20 2020/21 2021/22 2022/23 2023/24Audited outcome Revised estimate Medium-term expenditure estimate0

5%

10%

15%

20%

25%

30%

perc

enta

ge

Education as a % of total government expenditure Education as a % of GDP

6.7

22.6

6.9

23.0

7.2

22.7

7.7

20.8

7.3

22.5

7.1

23.0

6.7

23.1

Sources: National Treasury Medium Term Budget Policy Review Expenditure Priorities (2018, 2019, 2020); National Treasury Consolidated Budget Spending Plans (2021a); National Treasury GDP time series data, budget (2021b)

Notes:1. All values are expressed as nominal values as reported by the source. 2. Consolidated government expenditure includes spending by national departments and sub-national spending

(inclusive of national transfers and sub-national own resources).

A comparison of education expenditure in South Africa against that of other countries points to some interesting observations. Figure 20 below shows expenditure on education as a percentage of government expenditure and GDP for a select number of countries. The figure was relatively high in South Africa compared to other BRICS countries and even exceeded the OECD member average in 2017. However, it was not too far off from the Sub-Saharan African average. South Africa’s expenditure on education as a percentage of GDP also exceeded that of all the countries shown in the graph below, except for Brazil.


FIGURE 20: Expenditure on education (both schooling and post-schooling) as a percentage of total government expenditure and GDP by country, 2017

perc

enta

ge

Brazil Chile Mauritius Malawi Malaysia OECD members

Russian Federation

Sub-Saharan Africa South Africa Zambia Zimbabwe

0

5%

10%

15%

20%

25%

% of total government expenditure % of GDP

6.3

16.5

5.4

21.3

5.0

19.9

4.0

14.3

4.7

21.7

5.0

12.1

4.7

13.5

4.0

17.1

6.1

18.7

3.7

14.8

5.8

20.8

Source: World Bank Education Statistics (2020a)

Notes:1. The values for South Africa reported by the World Bank are slightly different to the values calculated using the National

Treasury data as reported in Figure 18. The differences might be due to the revisions of the mid-term budget review. The calculations in this report for South Africa are based on the latest available data from the National Treasury.

2. The countries included in this figure were selected based on the availability of the latest data.

Figure 21 below shows that South Africa spent 0.9 percent of its GDP on tertiary education in 2017 – a figure that was, at the time, far below many other similar-income countries, such as Brazil, Chile, and Malaysia. This figure (for 2017) also falls slightly short of that recommended by the Heher Commission in 2017 (Commission of Inquiry into Higher Education and Training, 2017). However, as indicated above, South Africa’s spending on tertiary education as a percentage of its GDP increased significantly to 1.3 percent in 2019/20 as a result of a massive injection into student funding. Unfortunately, the unavailability of international comparative data for 2019/20 does not make it possible to conclude whether South Africa currently compares better with other countries than it did two years ago.

FIGURE 21: Expenditure on tertiary education as a percentage of GDP by country, 2017

Brazil Chile Germany Malaysia Mauritius Russian Federation South Africa

United Kingdom of Great Britain and Northern Ireland

Zambia

0

0.4

0.6

0.8

1.0

1.2

1.4

Perc

enta

ge o

f GDP

1.6

1.51.4

1.3

1.0

0.3

0.80.9

1.4

0.3

0.2

Source: UNESCO Institute for Statistics [UIS] (2021)

Notes:1. The value for South Africa reported by UIS is slightly different to the value calculated using the National Treasury data

as reported in Figure 6. The differences might be due to the revisions of the Estimates of National Expenditure data. The calculations in this report are based on the latest available data from the National Treasury.

2. The countries included in this figure were selected based on the availability of the latest data.


PSET and schooling expenditure as a share of consolidated government expenditure on education is presented in Figure 22. The government spent more on the schooling system than the post-schooling system over the seven-year period under review. This is not surprising, given that student enrolment in schools is over 12 million, while that in universities, TVET colleges, and CET colleges is about 2.3 million, almost six times smaller. However, it is interesting to note that the PSET share of overall expenditure has been increasing over the past few years and is expected to continue increasing in the next three years.

FIGURE 22: PSET and schooling expenditure as a share of consolidated government expenditure on education, 2017/18–2023/24

2017/18 2018/19 2019/20 2020/21 2021/22 2022/23 2023/24Audited outcome Revised estimate Medium-term expenditure estimate

69.1

30.9

0

40%30%20%10%

50%60%70%80%90%

100%

PSET share of total education Schooling share of total education

73.9

26.1

72.7

27.3

70.0

30.0

70.5

29.5

69.5

30.5

69.3

30.7

perc

enta

ge

Sources: National Treasury Medium Term Budget Policy Review Expenditure Priorities (2018, 2019, 2020); National Treasury GDP time series data, budget (2020)

Notes:1. All values are expressed as nominal values as reported in the medium-term budget review. 2. Consolidated government expenditure includes spending by national departments and sub-national spending

(inclusive of national transfers and sub-national own resources).

7.2.3 Overall public spending on PSETTable 43 provides information on government spending on PSET, which increased from about R69 billion spent in 2017/18 to R107 billion in 2019/20. Most spending was towards university education (at R68.2 billion expenditure in 2019/20), followed by SETAs and the NSF (R18.2 billion), then TVET colleges (at R17.6 billion).


TABLE 43: Government spending, including skills levy, on PSET (R million), 2017/18–2019/20

AUDITED OUTCOME

2017/18 2018/19 2019/20

University (including National Student Financial Aid Scheme [NSFAS]) 39 838 56 397 68 241

TVET (including NSFAS) 9 737 13 689 17 626

CET 1 933 1 979 2 058

SETAs and the NSF 16 294 17 480 18 284

Other 748 802 859

Total 68 550 90 346 107 067

Sources: DHET Statistics on Post-School Education and Training in South Africa (2019b); National Treasury Estimates of National Expenditure (2021c)

Notes:1. All values are expressed as nominal values as reported by the source.2. The values for university include transfers to departmental agencies NSFAS and the Council on Higher Education.3. Other includes funds allocated to the following programmes: administration, planning, policy and strategy, and

skills development.4. University (including NSFAS) was calculated by subtracting the amount of TVET NSFAS from the amount allocated for

university education in the Estimates of National Expenditure.5. TVET (including NSFAS) was calculated by adding the amount of TVET NSFAS to the amount allocated for TVET in the

Estimates of National Expenditure.6. Even though SETAs and the NSF receive funding from the skills levy, which is from the private sector, they are included

as part of government expenditure since the funds flow through the National Treasury.

Figure 23 shows government spending on PSET as a percentage of total consolidated government expenditure and GDP. The graph shows that as a percentage of GDP, PSET is expected to grow by 0.5 percentage points, from 1.5 percent in 2017/18 to 2.0 percent in 2023/24. Spending on PSET as a proportion of overall government expenditure is projected to increase by 2.1 percentage points, from 4.9 percent in 2017/18 to 7 percent in 2023/24.

FIGURE 23: Government spending on PSET as a percentage of total consolidated government expenditure and GDP, 2017/18–2023/24

2017/18 2018/19 2019/20 2020/21 2021/22 2022/23 2023/24Audited outcome

Adjusted appropriation

Medium-term expenditure estimate

0%

2%

4%

6%

8%

10%

perc

enta

ge

% of GDP % of total government expenditure

4.9%

6.1%6.5%

5.7%

6.6% 6.9% 7.0%

1.5% 1.8% 2.1% 2.1% 2.2% 2.1% 2.0%

Sources: National Treasury Medium Term Budget Policy Statements (2018, 2019, 2020); National Treasury Estimates of National Expenditure (2021c); National Treasury GDP time series data, budget (2021b); National Treasury Consolidated Budget Spending Plans (2021a)

Note: All calculations are based on nominal values as reported by the sources.


7.2.4 Real per capita spending on PSETFigure 24 below provides information about inflation-adjusted per capita spending on students at both public universities and TVET colleges for the period 2010/11–2019/20. In 2010/11, the cost for training a full-time university student for one year was R80 000; this figure has been rising over the past decade, albeit slowly, even after considering the effect of inflation. By 2018/19, the inflation-adjusted cost of training a full-time university student for one year was R88 600. This amount reflects a real cost per capita increase of R8 600 over the past 10 years. However, as Figure 24 shows, the inflation-adjusted cost per capita per student rose in 2016/17 (probably due to changes in the threshold income of students who qualified for NSFAS) and declined significantly between 2016/17 and 2018/19, then increased significantly in 2019/20. In contrast, the cost per FTE TVET student was only R42 800 in 2010/11. It declined significantly for seven years then jumped to R44 000 in 2019/20. The increase can be explained by the substantial increase in the subsidies allocated to TVET colleges from 2017/18 to 2018/19 (from about R1.5 billion in 2017/18 to about R4.3 billion in 2018/19) and the huge increase for NSFAS (from R2.7 billion in 2018/19 to R5.1 billion in 2019/20).

FIGURE 24: Per FTE student expenditure at public universities and TVET colleges, 2010/11–2019/20

2010/11 2011/12 2012/13 2013/14 2014/15 2015/16 2016/17 2017/18 2018/19 2019/200

20

10

40

30

50

80

90

70

60

100

Rand

thou

sand

s

Public universities TVET colleges

80.0

42.8

79.6

37.0

83.6

29.5

82.1

26.9

85.3

26.1

87.6

25.7

90.7

24.4

87.0

25.1

83.5

35.8

88.6

44.0

Sources: DHET Financial Health Reports (2021a); DHET Statistics on Post-School Education and Training in South Africa (2014, 2015, 2016, 2017b, 2018, 2019b, 2020d, 2021d).

Notes:1. All values are expressed in real terms (2015/16 R million).2. Per student FTE expenditure is calculated by dividing the total expenditure from public universities (government, student

fees, and third-stream income) by public university FTE students.3. Per student FTE expenditure for TVET colleges is calculated by adding together subsidies to TVET colleges plus

conditional grants or operational costs, plus TVET NSFAS then dividing the figure by TVET colleges’ FTE students.

Table 44 shows the distribution of the skills development levy from 2011/12 to 2019/20. The total amount disbursed by the Skills Levy Fund has increased at an average annual growth rate of 7.7 percent from 2011/12 to 2019/20. The total amount disbursed in 2019/20 was about R18.3 billion, of which 80.0 percent was transferred to SETAs and the balance to the NSF and the Quality Council for Trades and Occupations (QCTO).


TABLE 44: Distribution of the skills development levy, 2011/12–2019/20

YEAR

TOTA

L AM

OUN

T D

ISBU

RSED

BY

TH

E SK

ILLS

LEV

Y FU

ND

(R T

HO

USAN

DS)

DISTRIBUTION OF LEVY FUNDS

PORT

ION

OF

SETA

AD

MIN

FEE

TR

ANSF

ERRE

D TO

QCT

O

(R T

HO

USAN

DS)

NSF

(R

TH

OUS

AND

S)

AMO

UNT

DIS

BURS

ED

TO S

ETAS

(R

TH

OUS

AND

S)

SETAS

ADM

INI S

TRAT

ION

COST

S (R

TH

OUS

AND

S)

MAN

DATO

RY

GRAN

T

(R T

HO

USAN

DS)

DIS

CRET

ION

ARY

GRAN

T

(R T

HO

USAN

DS)

2011/12 10 106 213 2 020 029 8 086 184 1 010 773 5 053 865 2 021 546 n/a

2012/13 11 419 341 2 283 872 9 135 469 1 141 934 5 709 668 2 283 867 n/a

2013/14 12 566 289 2 511 390 10 054 899 1 319 705 2 513 725 6 221 469 15 428

2014/15 14 036 309 2 818 082 11 218 227 1 472 392 2 804 557 6 941 278 28 500

2015/16 15 225 043 3 044 212 12 180 831 1 598 734 3 045 208 7 536 889 40 000

2016/17 15 298 454 3 046 235 12 252 219 1 608 103 3 063 055 7 581 061 60 670

2017/18 16 234 599 3 246 920 12 987 679 1 704 633 3 246 920 8 036 126 68 431

2018/19 17 479 895 3 495 979 13 983 916 1 835 389 3 495 979 8 652 548 86 691

2019/20 18 283 843 3 656 768 14 627 075 1 919 803 3 656 769 9 050 503 90 347

Average annual growth 2011/12–2019/20

7.7% 7.7% 7.7% 8.3% –4.0% 20.6% n/a

Source: DHET Statistics on Post-School Education and Training in South Africa (2019b)

7.2.5 The National Student Financial Aid SchemeSouth Africa has developed one of the most effective student bursary and loan schemes for PSET called the National Student Financial Aid Scheme (NSFAS). NSFAS is an income-contingent scheme designed for students from poor- and working-class families who have a combined household income of up to R350 000 a year. NSFAS is funded by the government, to the tune of R22.9 billion in 2019/20, up from R7.4 billion in 2011/12. Under this scheme, the number of students assisted for both universities and TVET colleges increased from 332 187 in 2011/12 to 740 037 in 2019/20, as reflected in Table 45 below. In 2019/20, over one-third of students enrolled at universities were NSFAS beneficiaries, while over half of students enrolled at TVET colleges were NSFAS beneficiaries. The real per student university NSFAS allocation increased on average by 7.0 percent from 27 694 in 2011/12 to 47 415 in 2019/20. Real TVET allocations increased by 14.9 percent on average from 2011/12 to 2019/20, and the number of students increased on average by 14.8 percent in the same period. The real per student TVET NSFAS allocation, however, showed an insignificant increase of about 0.1 percent on average in the nine-year period under review. While the TVET college share of NSFAS-supported students has increased from 34.6 percent in 2011/12 to 46.8 percent in 2019/20, the TVET share of NSFAS expenditure fluctuated from 2011/12 to 2019/20 but remained at 18.4 percent in 2019/20.


TABL

E 45

: Tot

al a

nd p

er st

uden

t NSF

AS a

lloca

tion

to p

ublic

uni

vers

ities

and

TVE

T co

llege

s 201

1/12

–201

9/20

YEAR

UNIV

ERSI

TYTV

ET C

OLL

EGES

UNIV

ERSI

TY A

ND

TVET

CO

LLEG

ES

TVET

SH

ARE

OF

NSF

AS

EXPE

ND

ITUR

E

TVET

SH

ARE

OF

NSF

AS

SUPP

ORT

ED

STUD

ENTS

EXPENDITURE(R THOUSANDS)

STUDENTS ASSISTED

PER STUDENT EXPENDITURE


STUDENTS ASSISTED



STUDENTS ASSISTED


(R THOUSANDS)

2011

/12

6 01

5 60

721

7 21

927

694

1

385

239

114

968

12 0

49

7 40

0 84

633

2 18

722

279

18

.7%

34.6

%

2012

/13

6 92

1 50

819

4 93

235

507

2

142

260

188

182

11 3

84

9 06

3 76

938

3 11

423

658

23

.6%

49.1

%

2013

/14

7 49

6 09

019

5 38

738

365

2

169

744

220

978

9 81

9 9

665

834

416

365

23 2

15

22.4

%53

.1%

2014

/15

7 33

1 16

718

6 16

039

381

2

094

386

228

642

9 16

0 9

425

554

414

802

22 7

23

22.2

%55

.1%

2015

/16

7 19

4 61

917

8 96

140

202

2

095

130

235

988

8 87

8 9

289

748

414

949

22 3

88

22.6

%56

.9%

2016

/17

9 69

4 47

622

5 95

042

905

1

981

527

225

557

8 78

5 11

676

003

451

507

25 8

60

17.0

%50

.0%

2017

/18

10 8

76 5

7126

0 00

241

833

1

807

722

200

339

9 02

3 12

684

293

460

341

27 5

54

14.3

%43

.5%

2018

/19

15 7

74 0

0834

6 96

645

463

2

354

615

239

797

9 81

9 18

128

623

586

763

30 8

96

13.0

%40

.9%

2019

/20

18 6

70 3

8739

3 76

747

415

4

203

721

346

270

12 1

40

22 8

74 1

0874

0 03

730

909

18

.4%

46.8

%

AVER

AGE

ANN

UAL

GRO

WTH

2011

/12–

2013

/14

11.6

%–5

.2%

17.7

%25

.2%

38.6

%–9

.7%

14.3

%12

.0%

2.1%

9.5%

23.8

%

2013

/14–

2015

/16

–2.0

%–4

.3%

2.4%

–1.7

%3.

3%–4

.9%

–2.0

%–0

.2%

–1.8

%0.

2%3.

5%

2015

/16–

2017

/18

23.0

%20

.5%

2.0%

–7.1

%–7

.9%

0.8%

16.9

%5.

3%10

.9%

–20.

5%–1

2.5%

2017

/18–

2019

/20

31.0

%23

.1%

6.5%

52.5

%31

.5%

16.0

%34

.3%

26.8

%5.

9%13

.6%

3.7%

2011

/12–

2019

/20

15.2

%7.

7%7.

0%14

.9%

14.8

%0.

1%15

.1%

10.5

%4.

2%–0

.2%

3.8%

Sour

ce: D

HET S

tatis

tics o

n Po

st-Sc

hool

Educ

atio

n an

d Tra

inin

g in

Sout

h Af

rica

(201

9b)

Note

: All v

alues

are

expr

esse

d in

real

term

s (20

15/1

6 R

milli

on).

A responsive PSET system

8

8 | A RESPONSIVE PSE T SYSTEM | 87

8.1 How responsive is the PSET system to the labour market?

In general, the notion of responsiveness speaks to PSET qualifications, programmes, curricula, teaching and learning materials, and practices that are responsive to the needs of individuals and employers, as well as broader economic, societal, and developmental objectives (DHET, 2021). This report, however, focuses on the responsiveness of the PSET system to the needs of the economy and labour market and to individuals in terms of their employability. An understanding of the skills needed by the labour market is therefore critical in ensuring that appropriate interventions are adopted to provide the requisite human resources (Reddy et al., 2016). Without a clear sense of the required mix of skills, it is difficult to formulate appropriate policies that will improve the alignment between the demand and supply of skills in the country. Although there are many indicators that could provide insights into the responsiveness of the PSET system (including graduate and employer perceptions), this report adopts three key indicators to provide information about the level of responsiveness of the PSET system to the needs of the labour market.

The first indicator of responsiveness relates to labour market absorption. Such an indicator signals whether there is a demand for particular kinds of qualifications in the labour market. Information for this indicator is usually obtained from tracer studies. This report draws on a tracer study recently conducted by Rogan and Papier (2020). It provides a measure of labour market absorption by TVET college students who completed their qualifications in 2017. Their labour market status 12–18 months after graduation is used as a measure of labour market absorption. Unfortunately, no recent national tracer studies for higher education graduates are available.

The second indicator, which is used by many countries, relates to the measurement of skills mismatches, which examines the extent to which the levels and types of skills required for a job and the person doing the job do not match. This measure focuses on two elements: namely, the extent of under- or over-qualification for a job and the relative ‘match’ between field of study and occupation. High levels of such mismatches suggest that the PSET system may not be responsive to the needs of the labour market.

The third indicator of responsiveness measures the extent to which universities and TVET colleges are preparing students for occupations that are in high demand (OIHD) in the labour market. The DHET produces this list every two years (to date, four lists have been developed). A measure of enrolment trends against key occupations in the list of OIHD could provide some indication of the responsiveness of the PSET system to the needs of the labour market.

8.1.1 Graduate employment using findings of the TVET tracer study

This section presents key findings from the tracer study titled ‘A Baseline Study on the Destination of TVET College Graduates to Strengthen Employment Promotion in South Africa’ (Rogan & Papier, 2020). The study was commissioned by the Capacity Building Programme for Employment Promotion, a European Union–funded programme implemented by the Government Technical Advisory Centre. This tracer study provides progress towards DHET’s objective of engaging with evidence-based research to evaluate labour market outcomes for the TVET sector. The study sampled nearly 4 000 TVET college graduates with a response rate of 35.2 percent and has revealed important insights into the transition of TVET graduates into the labour market.


Figure 25 provides information about the labour market status of TVET students after completing their qualifications in 2017. It reveals that about 55.0 percent of graduates were either involved in some kind of work or studying, while about 45.0 percent were neither working nor studying. The labour market absorption rate, which is a measure of the graduates who became self-employed, were employed by another person, or were participating in work-based learning (WBL) programmes, was 40.5 percent. Only 14.0 percent of graduates continued with their studies.

FIGURE 25: Labour market status of TVET students after completing their qualifications in 2017

Employed WBL Not working Self-employed Studying0%

25%

20%

15%

10%

5%

30%

35%

40%

45%

50%

perc

enta

ge

16.6

21.9

45.3

14.2

2.0

Source: Rogan & Papier (2020)

Figure 26 shows the labour market status of TVET college students who graduated in 2017 by gender. It reveals that a significantly large number of female graduates were not working compared to male graduates (48.0 percent versus 42.0 percent), while more male graduates were employed or studying further compared to female graduates.

FIGURE 26: Labour market status of TVET college students after completing their qualifications in 2017 by gender

Employed WBL Not working Self-employed Studying0%

10%

20%

30%

40%

50%

60%

perc

enta

ge

31.4

18.915

20.622.8

41.947.6

15.713.1

Female Male

Source: Rogan & Papier (2020)


8.1.2 Skills supply and demand mismatches in South AfricaWhile the South African government and other stakeholders have made many improvements in the skills system in recent years, mismatches between the supply of skills and the demand in the labour market remain a challenge. The COVID-19 crisis is having a profound impact on the South African labour market, with certain sectors and occupations being worse hit by the pandemic than others, and some likely to face long-lasting impacts. Mismatches are therefore likely to become an even bigger problem. Tackling the issue of mismatch is key for the recovery of the South African economy.

The levels of education–job mismatches in South Africa are very high. Table 47 shows that, in 2019, 51.1 percent of South African workers were employed in an occupation for which they did not have the correct education level. About 21.6 percent of South African workers are over-qualified for their jobs (that is, their highest educational attainment level is higher than the one usually required in the occupation they are employed in), and a further 29.5 percent are under-qualified (their highest educational attainment level is lower than the one usually required in the occupation they are employed in). Furthermore, 33.2 percent of South African workers are employed in an occupation that does not match the field of study of their highest educational attainment. These figures refer to workers aged 16–64 years.

Table 46 shows that there was little variation in qualification and field of study during 2019 and 2020. In 2020, 21.5 percent of South African workers were over-qualified (a decrease of 0.1 percentage point from 2019) and 30 percent were under-qualified (an increase of 0.5 percentage point from 2019), while 32.5 percent were mismatched by their field of study (a decrease of 0.7 percentage point from 2019). These mismatches are likely to be a source of productivity losses at the national and industry levels, as well as of wage penalties for individuals.

TABLE 46: Share of employed persons aged 16–64 years by qualification and field-of-study mismatch, 2019 and 2020

YEAR UNDER-QUALIFICATION OVER-QUALIFICATION FIELD-OF-STUDY MISMATCH

2019 29.5% 21.6% 33.2%

2020 30.0% 21.5% 32.5%

Source: OECD Skills for Jobs Database (2021c)

South Africa has very high levels of education–job mismatches in comparison to many other countries. The incidence of qualification mismatch in South Africa (51.5 percent) is higher than all of the countries shown in Figure 27, especially where under-qualification is concerned. The overall incidence of qualification mismatch for OECD countries was only 35.7 percent, compared to South Africa’s 51.5 percent. It is interesting to note, though, that South Africa’s mismatch in terms of field of study (33.08 percent) is similar to that of the OECD average (32.16 percent), suggesting that this problem is not confined to South Africa.


FIGURE 27: Qualification and field-of-study mismatch by country (2020 for South Africa, 2018 for most other countries)

perc

enta

ge

CER

SVK

POL

SVN FIN LUX

HUN

KOR

BEL

USA

DNK

FRA

LTU NOR

OECD AU

TLV

ACH

ESW

ECA

NNL

DAU

SES

T ITA DEU ISL ESP

PRT

GBR IRL TUR

GRC

CHL

MEX

PER

BRA

THA

ARG

ZAF

10%

0%

20%

30%

40%

50%

60%

Under-qualification Over-qualification Field-of-study mismatch

Source: OECD Skills for Jobs Database (2021c)

8.1.3 Occupations in high demandInformation about occupations in high demand (OIHD) provides useful insights into the skills needs of the economy and society, especially in a context where the South African labour market is characterised by high levels of unemployment on the one hand, and skills shortages on the other. The DHET has gazetted four national lists of OIHD to date, with the 2020 list being the latest iteration produced. The gazette provides a list of occupations that have been identified as being in high demand at the national level. The list consists of occupations that are likely to grow over the next two years, thereby providing information that could guide the education and training sector, as well as the public at large (DHET, 2020a). Among other things, the OIHD list signals the need for the development of new qualifications, especially to respond to new and emerging occupations and skills needs, and informs career guidance for learners and students to ensure that they enrol for programmes and select fields of study that respond to the occupations in high demand.

The 2020 list of OIHD comprises a total of 394 occupations. This report selected 102 key occupations from the OIHD list based on their cross-cutting nature and their linkages to the sectors that have been identified as a priority towards the recovery of the South African economy for analysis. These sectors point to a significant demand for science- and technology-based occupations at both the professional and technician levels.

TABLE 47: Occupations in high demand

ENGINEERING ICT ARTISANS

Industrial engineer Chief information officer Chef

Industrial engineering technologist ICT project manager Bricklayer

Production engineering technologist Data management manager Carpenter and joiner

Civil engineer Application development manager Carpenter

Civil engineering technologist Information technology manager Joiner

Environmental engineer Information systems director Wall and floor tiler


ENGINEERING ICT ARTISANS

Environmental impact and restoration analyst Call or contact centre manager Plasterer

Mechanical engineer Multimedia designer Plumber

Mechanical engineering technologist Web designer Pipe fitter

Aeronautical engineer Communication strategist Painter

Aeronautical engineering technologist Corporate communication manager Moulder

Naval architect ICT account manager Rigger

Chemical engineer ICT business development manager Toolmaker

Chemical engineering technologist ICT systems analyst Metal machinist

Mining engineer Data scientist Fitter and turner

Quantity surveyor Software developerTextile, clothing, footwear, and leather processing machine mechanic

Agricultural engineer Programmer analyst Automotive motor mechanic

Agricultural engineering technologist Developer programmer Industrial machinery mechanic

Electrical engineer Multimedia specialist Diesel fitter

Electrical engineering technologist Web developer Small engine mechanic

Energy engineer Applications programmer Diesel mechanic

Energy engineering technologist Computers quality assurance analyst Heavy equipment mechanic

Electronic engineering technician Database designer and administrator Tractor mechanic

Mechanical engineering technician Systems administrator Forklift mechanic

Electrical engineering technician Computer network and systems engineer

Precision instrument maker and repairer

Civil engineering technician Network analyst Goldsmith

Aeronautical engineering technician ICT security specialist Diamond and gemstone setter

Chemical engineering technician Information services manager Glass maker

Industrial engineering technician Computer operator Optical mechanic

Engineering supervisor ICT communications assistant Mechatronics technician

Computer network technician Lift mechanic

Geographic information systems technician Weapon systems mechanic

Marine GIS technician Electrical equipment mechanic

Data entry operator Armature winder

Inbound contact centre consultant Transportation electrician

Outbound contact centre consultant Electrical line mechanic

Contact centre real-time advisor Electronic equipment mechanician

Contact centre resource planner Confectionary baker

Contact centre forecast analyst Pastry cook

Call or contact centre agent Confectionery maker

Source: DHET List of Occupations in High Demand (2020a)


8.1.4 Are universities and TVET colleges preparing students for occupations that are in high demand in the labour market?

Student enrolment and graduation in major fields of study are used as proxies to measure the responsiveness of the PSET system in terms of the production of graduates with the necessary skills required in the labour market, as signalled by the list of OIHD. Table 48 shows that from 2013 through to 2019, the science, engineering, and technology (SET) field of study had the largest number of enrolments, which increased by 14 percent (39 654 students) from 283 621 students in 2013 to 323 275 students in 2019. This trend demonstrates that university enrolment plans are, in a broad sense, responding positively to occupations that are in high demand.

Notably, female students are in the majority in all major fields of study throughout the period, except for SET. However, it appears that the gender gap in SET enrolments is narrowing, as female students made up 47.8 percent of total SET enrolments as compared to 52.2 percent for male students in 2019.

SET fields contributed the highest number of graduates over the period 2010–2019, as shown in Table 49. In 2019, the highest number of graduates were in SET fields (30.0 percent), followed by the humanities (25.5 percent), business and management (24.7 percent), and education (19.7 percent). This trend demonstrates that South Africa has the potential to produce graduates with the necessary skills required in the labour market.


TABL

E 48

: Pub

lic H

EIs:

Enro

lmen

t in

maj

or fi

eld

of st

udy

by g

ende

r, 20

10–2

019

YEAR

SC

IEN

CE, E

NGI

NEE

RIN

G, A

ND

TECH

NO

LOGY

BUSI

NES

S AN

D M

ANAG

EMEN

TED

UCAT

ION

HUM

ANIT

IES

TOTA

L

FEM

ALE

MAL

ETO

TAL

FEM

ALE

MAL

ETO

TAL

FEM

ALE

MAL

ETO

TAL

FEM

ALE

MAL

ETO

TAL

FEM

ALE

MAL

E

2010

112

746

138

591

251

337

156

573

122

267

278

840

107

319

38 0

9214

5 41

113

5 93

481

397

217

331

512

572

380

348

2011

118

421

146

022

264

443

162

688

125

796

288

484

122

296

42 5

8016

4 87

613

9 59

280

718

220

310

542

997

395

116

2012

123

513

149

766

273

279

159

607

122

689

282

296

125

950

42 5

1116

8 46

114

5 77

083

401

229

171

554

840

398

367

2013

129

009

154

612

283

621

156

954

122

998

279

952

129

736

43 2

5517

2 99

115

8 80

089

124

247

924

573

698

409

988

2014

131

664

155

555

287

219

152

484

119

923

272

407

124

636

41 4

6216

6 09

815

6 00

187

425

243

426

564

784

404

365

2015

136

267

158

665

294

932

152

805

121

023

273

828

128

130

42 4

1717

0 54

715

7 47

688

419

245

895

574

677

410

523

2016

136

520

158

854

295

374

147

931

117

001

264

932

131

550

45 4

3417

6 98

415

1 11

987

407

238

526

567

119

408

697

2017

144

677

165

436

310

113

157

174

121

755

278

929

145

103

50 0

0719

5 11

015

9 94

592

867

252

812

606

898

430

065

2018

151

248

169

416

320

664

160

844

122

344

283

188

159

713

54 4

3321

4 14

616

9 68

797

848

267

535

641

492

440

040

2019

154

631

168

644

323

275

152

538

113

423

265

961

157

558

53 7

1221

1 27

017

5 60

598

734

274

339

640

332

434

514

Aver

age

grow

th3.

6%2.

2%2.

9%–0

.2%

–0.8

%–0

.5%

4.5%

4.0%

4.4%

3.0%

2.2%

2.7%

2.5%

1.5%

Sour

ce: D

HET H

ighe

r Edu

catio

n M

anag

emen

t Inf

orm

atio

n Sy

stem

(202

1b)

TABL

E 49

: Pub

lic H

EIs:

Grad

uate

s by

maj

or fi

eld

of st

udy

by g

ende

r, 20

10–2

019

SC

IEN

CE, E

NGI

NEE

RIN

G AN

D TE

CHN

OLO

GYBU

SIN

ESS

AND

MAN

AGEM

ENT

EDUC

ATIO

NH

UMAN

ITIE

STO

TAL

MAL

EFE

MAL

ETO

TAL

MAL

EFE

MAL

ETO

TAL

MAL

EFE

MAL

ETO

TAL

MAL

EFE

MAL

ETO

TAL

MAL

EFE

MAL

E

2010

21 7

5621

003

42 7

5918

380

23 2

7541

655

9 28

128

611

37 8

9210

844

20 1

7332

483

60 2

6093

062

2011

23 3

3522

765

46 1

0019

323

24 8

3544

158

9 59

428

284

37 8

7811

415

21 0

6835

617

63 6

6796

952

2012

24 7

0524

144

48 8

4919

851

26 1

9346

044

9 36

926

102

35 4

7112

113

23 5

0440

382

66 0

3799

943

2013

26 6

0626

571

53 1

7721

097

27 9

5349

050

9 56

528

648

38 2

1313

576

26 8

0642

343

70 8

4410

9 97

8

2014

27 6

6927

906

55 5

7521

656

28 7

2450

380

9 29

127

784

37 0

7514

130

28 2

1342

915

72 7

4611

2 62

7

2015

28 6

7629

414

58 0

9023

222

30 6

4153

863

8 90

327

751

36 6

5414

315

28 6

0045

476

75 1

1711

6 40

5

2016

29 1

5029

971

59 1

2124

144

32 2

1856

362

10 0

5132

056

42 1

0715

419

30 0

5747

139

78 7

6412

4 30

2

2017

29 8

9731

684

61 5

8124

592

33 1

7857

770

10 6

4633

787

44 4

3316

106

31 0

3350

859

81 2

4112

9 68

1

2018

31 2

7733

931

65 2

0825

340

35 1

1860

458

11 7

4238

905

50 6

4716

937

33 9

2251

084

85 2

9614

1 87

6

2019

30 8

2233

855

64 6

7724

240

34 4

2658

666

11 3

1136

177

47 4

8816

730

34 3

5432

483

83 1

0313

8 81

2

Aver

age

grow

th4.

0%5.

5%4.

7%3.

2%4.

5%3.

9%2.

4%3.

0%2.

8%5.

0%6.

2%5.

8%3.

7%4.

6%

Sour

ce: D

HET H

ighe

r Edu

catio

n M

anag

emen

t Inf

orm

atio

n Sy

stem

(202

1b)


8.1.4.1 TVETcolleges–Distributionofstudents’completionbyqualificationand programmes

Table 50 shows the distribution of students who completed an NC(V) Level 4 qualification by programme and gender in 2019. Almost 30.0 percent of NC(V) students who graduated in 2019 did so in office administration, followed by tourism (8.3 percent), and engineering and related design (7.6 percent). Given the dramatically negative impact of COVID-19 on the tourism sector in 2020, it would perhaps be prudent for TVET colleges to revisit their enrolment plans for the tourism programme at the present moment. Furthermore, given that many of the OIHD pertain to SET fields of study, it may be necessary to shift the focus of TVET college enrolments to related programmes.

Table 50 also shows traditional gender bias in enrolment patterns, wherein more female students enrol in ‘soft’ occupations compared to male students. It is concerning that programmes such as office administration, tourism, and hospitality reflected higher proportions of female graduates, while the engineering and related design and electrical infrastructure construction programmes’ graduates were dominated by male students.

TABLE 50: Percentage distribution of students who completed NC(V) Level 4 qualification by programme and gender, 2019

NC(V) LEVEL PROGRAMMEFEMALE MALE TOTAL

NUMBER COMPLETED

% SHARE

NUMBER COMPLETED

% SHARE

NUMBER COMPLETED

% SHARE

1. L4: Civil Engineering and Building Construction 270 3.3% 204 7.4% 474 4.3%

2. L4: Drawing Office Practice 1 0.0% 5 0.2% 6 0.1%

3. L4: Education and Development 429 5.3% 15 0.5% 444 4.1%

4. L4: Electrical Infrastructure Construction 417 5.1% 310 11.2% 727 6.7%

5. L4: Engineering and Related Design 347 4.3% 479 17.3% 826 7.6%

6. L4: Finance Economics and Accounting 614 7.5% 148 5.3% 762 7.0%

7. L4: Hospitality 648 8.0% 114 4.1% 762 7.0%

8. L4: Information Technology and Computer Science 153 1.9% 148 5.3% 301 2.8%

9. L4: Management 494 6.1% 129 4.7% 623 5.7%

10. L4: Marketing 342 4.2% 112 4.0% 454 4.2%

11. L4: Mechatronics 22 0.3% 39 1.4% 61 0.6%

12. L4: Office Administration 2 750 33.7% 420 15.2% 3 170 29.0%

13. L4: Primary Agriculture 267 3.3% 142 5.1% 409 3.7%

14. L4: Primary Health 126 1.5% 11 0.4% 137 1.3%

15. L4: Process Plant Operations 19 0.2% 6 0.2% 25 0.2%

16. L4: Safety in Society 294 3.6% 158 5.7% 452 4.1%

17. L4: Tourism 693 8.5% 216 7.8% 909 8.3%

18. L4: Transport and Logistics 263 3.2% 115 4.2% 378 3.5%

Total 8 149 100.0% 2 771 100.0% 10 920 100.0%



Table 51 shows the percentage distribution of students who completed the N6 qualification by programme and gender in 2019. Of these students, 24.1 percent did so in engineering studies, followed by management assistant studies (19.7 percent), and human resource management studies (11.3 percent). The higher proportion of students enrolled in engineering studies is a positive sign as it suggests greater responsiveness to the kinds of occupations that are in high demand.

However, the pattern of enrolment also reflects a gender bias. More female students who completed N6 did so in management assistant studies (23.6 percent) than male students (11.5 percent), while there were fewer female students completing engineering studies (16.8 percent) than male students (39.7 percent).

TABLE 51: Percentage distribution of students who completed N6 qualification by programme and gender, 2019

N6 PROGRAMMESFEMALE MALE TOTAL

NUMBER COMPLETED

% SHARE

NUMBER COMPLETED

% SHARE

NUMBER COMPLETED

% SHARE

1. N6: Art and Design 119 0.2% 217 0.6% 336 0.3%

2. N6: Business Management 8 078 10.4% 3 457 9.6% 11 535 10.2%

3. N6: Clothing Production 267 0.3% 67 0.2% 334 0.3%

4. N6: Educare 3 949 5.1% 165 0.5% 4 114 3.6%

5. N6: Engineering Studies 13 025 16.8% 14 318 39.7% 27 343 24.1%

6. N6: Farming Management 852 1.1% 715 2.0% 1 567 1.4%

7. N6: Financial Management 6 858 8.9% 2 715 7.5% 9 573 8.4%

8. N6: Hospitality and Catering Services 1 709 2.2% 584 1.6% 2 293 2.0%

9. N6: Human Resources Management 9 536 12.3% 3 241 9.0% 12 777 11.3%

10. N6: Interior Decorating 2 0.0% 1 0.0% 3 0.0%

11. N6: Legal Secretary 736 1.0% 168 0.5% 904 0.8%

12. N6: Management Assistant 18 222 23.6% 4 146 11.5% 22 368 19.7%

13. N6: Marketing Management 3 319 4.3% 1 933 5.4% 5 252 4.6%

14. N6: Medical Secretary 45 0.1% 18 0.0% 63 0.1%

15. N6: Popular Music: Composition – 0.0% 3 0.0% 3 0.0%

16. N6: Popular Music: Performance 48 0.1% 69 0.2% 117 0.1%

17. N6: Popular Music: Studio Work 16 0.0% 127 0.4% 143 0.1%

18. N6: Public Management 7 741 10.0% 3 004 8.3% 10 745 9.5%

19. N6: Public Relations 841 1.1% 206 0.6% 1 047 0.9%

20. N6: Tourism 1 969 2.5% 907 2.5% 2 876 2.5%

Total 77 332 100.0% 36 061 100.0% 113 393 100.0%



8.1.5 Learners completing artisanal learning programmesThe percentage of learners completing artisanal learning programmes by trade and gender for the period 2017/18 to 2019/20 is shown in Table 52 below. 35.9 percent of learners qualified as electricians in 2019/20, followed by mechanical fitters (10.7 percent), and diesel mechanics (10.2 percent). However, no learners qualified as joiners, carpenters, or pipe fitters in the period under review. This lack of graduates is a matter of concern given the government’s economic focus on infrastructure development as well as its strategy to grow the furniture industry. These three occupations are also reflected in the OIHD list, suggesting the need for the improved responsiveness of artisanal programmes to the needs of the labour market.

Given that trade-related occupations have historically been the domain of males, it is inspiring to note that in 2019/20, a higher proportion of female students qualified as electricians and plumbers than male students.

TABLE 52: Percentage of learners completing artisanal learning programmes by trade and gender, 2017/18–2019/20

TRADE2017/18 2018/19 2019/20

FEMALE MALE TOTAL FEMALE MALE TOTAL FEMALE MALE TOTAL

Electrician 47.1% 33.7% 36.0% 43.9% 29.1% 31.7% 51.9% 32.1% 35.9%

Mechanical fitter 7.4% 11.0% 10.4% 10.2% 11.4% 11.2% 8.1% 11.3% 10.7%

Welder 10.1% 8.5% 8.8% 9.5% 7.2% 7.6% 6.9% 7.4% 7.3%

Diesel mechanic 5.5% 9.4% 8.7% 5% 9.4% 8.6% 5.0% 11.4% 10.2%

Plumber 7.0% 8.1% 7.9% 10.3% 11.8% 11.5% 9.2% 8.9% 8.9%

Boilermaker 3.6% 7.6% 6.9% 5.2% 7.5% 7.1% 4.1% 7.5% 6.9%

Automotive motor mechanic 3.3% 6.9% 6.3% 1.4% 5.9% 5.1% 1.9% 5.1% 4.5%

Millwright 4.9% 4.5% 4.6% 5.5% 5.9% 5.8% 4.7% 5.4% 5.3%

Rigger 2.1% 4.8% 4.4% 2% 5.3% 4.7% 1.8% 4.5% 4.0%

Fitter and turner 1.6% 2.5% 2.4% 1.6% 2.9% 2.7% 2.5% 3.8% 3.6%

Carpenter 4.3% 1.5% 2.0% 1.7% 1.5% 1.6% 1.1% 1.1% 1.1%

Bricklayer 3.1% 1.5% 1.7% 3.6% 1.9% 2.2% 2.8% 1.4% 1.7%

Joiner 0.0% 0.0% 0.0% 0.0% 0.3% 0.2% 0.0% 0.1% 0.0%

Carpenter and joiner 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%

Pipe fitter 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%

Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%


9Conclusion


This report monitors the progress made by the PSET system in relation to the goals articulated in the White Paper for Post-School Education and Training, for the period 2010–2019. As indicated in the subtitle, the report adopts high-level quantitative indicators to track the progress made on key dimensions of the PSET system. Many of the indicators selected for the report are used by international organisations such as UNESCO and the OECD to undertake cross-country comparisons of education inputs, outputs, and outcomes. Therefore, the report also provides data on how the South African PSET system has progressed in relation to that of other countries.

The report shows that there has been substantial growth in terms of access to universities and TVET colleges. It is possible for universities to meet the NDP enrolment target of 1.62 million students by 2030, but only if student enrolment increases annually at the same average rate as that obtained over the past decade, for the next nine years (until 2030). Despite significant enrolment growth at universities, it remains disconcerting that local university participation rates are well below those of many other countries, thereby reducing South Africa’s global economic competitiveness. Similarly, although enrolments at TVET colleges almost doubled from 2010 to 2019, the average annual growth rate recorded over the period needs to be doubled per annum from 2019 to 2030 for the NDP enrolment target to be realised. CET colleges’ enrolment numbers are still far below the NDP 2030 target and will have to more than triple in the remaining nine years for the target to be met.

This report demonstrates that access to PSET favours female students more than male students. The GPI for PSET is among the highest in the world, suggesting the prevalence of deeper issues in the South African fabric of society that account for other forms of gender inequality in the country.

The report reveals that the quality of education provision at universities is at risk. It shows that despite significant gains over the past decade, currently, less than 50.0 percent of university academic staff hold a PhD degree. The NDP target of 75.0 percent is therefore unlikely to be reached by 2030. The average student:staff ratio at universities, which is also a key indicator of quality, has been increasing over the past few years, thereby compromising not only the quality of education but also the capacity of universities to produce research outputs.

On a positive note, graduation rates for public universities have continued to grow in the period under review for all race groups and among both female and male students. At TVET colleges, certification rates have also increased significantly for all the programmes offered.

9 | CONCLUSION | 99

The report demonstrates that the university sector is becoming more efficient in terms of its improved throughput rates and declining dropout rates. Since data for throughput rates in TVET colleges were only available for one year, a trend in this regard cannot be observed. However, the very low throughput rate of NC(V) students at TVET colleges is cause for great concern.

Funding for education (schooling and PSET) as a percentage of GDP and the total consolidated government expenditure in South Africa is higher than the targets endorsed by UNESCO, but there are persistent concerns that additional investment in education is undermined by inefficiencies, poor management, and quality deficits. Although spending on PSET is projected to increase in the period under review, it remains inadequate to meet the White Paper for Post-School Education and Training and NDP targets for enrolment, especially for the TVET and CET sub-sectors.

The findings of the TVET tracer study by Rogan and Papier (2020) shows that, of the sampled TVET graduates, more than half were involved in some kind of employment or studying, while a substantial proportion were not working. The co-existence of high levels of unemployment in the country with significant skills shortages suggests that more needs to be done to ensure that the programmes offered in the PSET system are responsive to the needs of the economy and of the labour market.

The report indicates that the extent of mismatches between education and the labour market is fairly high in South Africa. This problem can be partly attributed to the PSET system not providing programmes that are responsive to the needs of the labour market. There is, however, a need for more data and further studies to monitor the responsiveness of the PSET system to the labour market.

Monitoring the performance of some of the PSET sub-sectors has been restricted by inadequate data or the lack of data in some cases. The DHET is currently putting in place measures that would ensure the availability of such data in due course, and it is expected that the next PSET Monitor will provide a more holistic view of the PSET sector.

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1010

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11Appendices


APPENDIX A: DEFINITIONS FOR INTERNATIONAL COMPARABILITY

The International Standard Classification of Education (ISCED) is a standard framework used to categorise and report cross-nationally comparable education statistics (UNESCO, 2012). This approach allows for the international comparability of country comparison data in this report.

ISCED 3: Upper secondary education Upper secondary education is designed to complete secondary education in preparation for tertiary education or provide skills relevant to employment, or both. Programmes at this level offer students more varied, specialised, and in-depth instruction than programmes at ISCED Level 2. They are more differentiated, with an increased range of options and streams available. Source definition: ISCED 2011

ISCED 4: Post-secondary, non-tertiary education Post-secondary, non-tertiary education provides learning and educational activities that build on secondary education to prepare for entry into both the labour market and tertiary education. This kind of education is typically targeted at students who have completed upper secondary (ISCED Level 3) schooling but want to increase their opportunities either to enter the labour market or to progress to tertiary education. Programmes are often not significantly more advanced than those at the upper secondary level, as they typically serve to broaden rather than deepen knowledge, skills, and competencies. Post-secondary, non-tertiary education therefore aims at learning below the high level of complexity that is characteristic of tertiary education. Source definition: ISCED 2011

ISCED 5: Short-cycle tertiary education Programmes at ISCED Level 5, or short-cycle tertiary education, are often designed to provide participants with professional knowledge, skills, and competencies. Typically, they are practically based and occupationally specific, and prepare students to enter the labour market. However, these programmes may also provide a pathway to other tertiary education programmes. Academic tertiary education programmes below the level of a bachelor’s programme or equivalent are also classified at ISCED Level 5. Source definition: ISCED 2011

11 | APPENDICES | 107

ISCED 6: Bachelor’s or equivalent level Programmes at ISCED Level 6 are designed to provide participants with intermediate academic and/or professional knowledge, skills, and competencies, leading to a first degree or equivalent qualification. Programmes at this level are typically theoretically based but may include practical components and are informed by state-of-the-art research and/or best professional practice. They are traditionally offered by universities and equivalent tertiary educational institutions.Source definition: ISCED 2011

ISCED 7: Master’s or equivalent level Master’s or equivalent level programmes are designed to provide participants with advanced academic and/or professional knowledge, skills, and competencies, leading to a second degree or equivalent qualification. Programmes at this level may have a substantial research component but do not yet lead to the award of a doctoral qualification. The programmes are theoretically based but may include practical components and are informed by state-of-the-art research and/or best professional practice. They are traditionally offered by universities and other tertiary educational institutions. Source definition: ISCED 2011

ISCED 8: Doctoral or equivalent level Programmes at ISCED Level 8, or doctoral or equivalent level, are designed primarily to lead to an advanced research qualification. Programmes at this ISCED level are devoted to advanced study and original research and are typically offered only by research-oriented tertiary educational institutions such as universities. Doctoral programmes exist in both academic and professional fields.Source definition: ISCED 2011

Tertiary education (ISCED Levels 5 to 8) Tertiary education builds on secondary education, providing learning activities in specialised fields of education. It aims at learning at a high level of complexity and specialisation. Tertiary education includes what is commonly understood as academic education but also includes advanced vocational or professional education. Source definition: ISCED 2011


APPENDIX B: ADDITIONAL TABLES

FIGURE 28: Enrolment in tertiary education per 100 000 people, by race, 2010–2019

0

50

100

150

per 1

00 0

00 p

eopl

e

2010 2011 2012 2013 2014 2015 2016 2017 2018 2019

Black African 183 193 199 218 224 230 247 258 282 274 Coloured 21 20 20 21 21 21 23 22 24 23 Indian/Asian 17 18 18 19 19 19 19 19 19 18 White 75 74 74 76 73 71 69 66 64 58

200

250

300


Note: Enrolments in tertiary education include both public and private HEIs.

TABLE 53: Number of students enrolled at PSET institutions compared to youth aged 15–24 years who are not in education, employment, or training, 2013–2019

YEAR

ENROLMENT NEET20

UNIVERSITIESTVET

COLLEGESCET

COLLEGESPRIVATE

COLLEGESSETA-SUPPORTED

WBL TOTAL(PUBLIC AND PRIVATE)

2013 1 103 639 639 618 249 507 154 632 176 307 2 323 703 3 261 000

2014 1 111 712 702 383 262 680 79 085 227 817 2 383 677 3 212 000

2015 1 132 422 737 880 283 602 88 203 231 097 2 473 204 3 139 000

2016 1 143 245 705 397 273 431 168 911 249 680 2 540 664 3 219 000

2017 1 222 030 688 028 258 199 187 354 269 147 2 624 758 3 213 000

2018 1 283 466 657 133 100 286 219 837 271 704 2 532 426 3 254 000

2019 1 283 890 673 490 172 142 151 136 222 210 2 502 868 3 340 000

Sources: DHET Statistics on PSET in South Africa (2015, 2016, 2017b, 2018, 2019b, 2020d, 2021d); Stats SA QLFS (2013, 2014, 2015, 2016, 2017, 2018, 2019)

20 NEET figures are rounded-off.

11 | APPENDICES | 109

TABLE 54: Private universities: GPI by race, 2015–2019


2015 1.3 1.2 1.2 1.2 1.4

2016 1.3 1.3 1.2 1.1 1.4

2017 1.5 1.4 1.3 1.1 1.4

2018 1.6 1.4 1.3 1.2 1.5

2019 1.6 1.4 1.3 1.2 1.4

Source: Annual report submitted by private HEIs to DHET (2019); Stats SA mid-year population estimates

Notes:1. A GPI of 1 indicates equitable gender participation. A GPI above 1 is indicative of higher female participation.

A GPI below 1 is indicative of higher male participation.2. The data disaggregated by both gender and race were available from 2015.

FIGURE 29: Public expenditure on tertiary education per student as a percentage of GDP per capita by country, 2015

Brazil Chile Germany United Kingdom High income Republic

of Korea Mauritius OECD members

Russian Federation South Africa

0

5

15

10

20

35

40

30

25

45

Perc

enta

ge o

f GDP

per

capi

ta

33.0

18.4

34.0 35.4

26.9

14.811.1

27.4

18.8

40.0

Source: World Bank (extracted 22 January 2021)

Documents

Post-School Education and Training Monitor