Tracer Study Impact Assessment of four CHIETA programmes

Tracer Study: Impact Assessment of four CHIETA programmes (Project in progress)

Purpose / objective of study • To determine the impact of the CHIETA learnership, apprenticeship, and workintegrated learning (WIL) programmes in the lives of beneficiaries who completed their training during the 2017/2018 period • To determine the value of the training voucher project in terms of advancing the knowledge and skills of SMME owners and co-workers

Background • Applying the impact assessment model that was developed in 2017 on work-based learning (WBL) programmes • Defining WBL • Apprenticeships • Learnerships • Work-integrated learning (WIL) • WIL in the CHIETA context • Internships • TVET college qualifications • Higher Education Institution (HEI) qualifications

Research Methodology (1) • Both quantitative and qualitative methods are applied to collect data – Tracer study by means of cross-sectional surveys using structured interviews (beneficiaries of apprenticeships, learnerships, and WIL programmes) – Semi-structured interviews (employers and owners of SMMEs) – Case studies in video format (success stories of beneficiaries)

Research Methodology (2) • Samples for apprenticeship and learnership surveys stratified according to: – Type of learner (18. 1 or 18. 2) (proportional) – Type of trade/learnership (proportional) – Gender (disproportional) – Random sample was drawn from each group • Complete sample framework used for WIL participants – lack of contact details • Purposive samples for – Employers (15) – SMMEs (10) – Case studies (5)

Realisation of Survey Samples Programmes Apprenticeships (Survey completed) Learnerships (Survey completed) WIL (In progress) Total Year 2017/2018 Sample Framework (N) Realisation of Sample (%) Q 1 -Q 3 472 210 44 Q 1 -Q 4 697 297 43 Q 2 124 36 29 1 293 543 42

Demographic profile of apprenticeship respondents (N=210) N % Unemployed (18. 2) 142 68 Employed (18. 1) 68 32 Male 186 89 Female 24 11 African 176 84 Coloured 8 4 Indian 8 4 White 18 9 Automotive Motor Mechanic 2 1 Electrician 80 38 Fitter and Turner 4 2 Instrument Mechanician 6 3 Mechanical Fitter 31 15 Rigger 62 30 Welder 25 12 Average 34

Demographic profile of learnership respondents (N=297) N % Unemployed (18. 2) 221 74 Employed (18. 1) 76 26 Male 198 67 Female 99 33 African 264 89 Coloured 14 5 Indian 11 4 White 8 3 Automated Packaging Operator 37 12 Boiler Maker 12 4 Chemical Manufacturing 78 26 Chemical Operations 49 16 Electrical Engineering 30 10 Electrician 1 0 Instrument Mechanician 1 0 Measurement, Control & Instrumentation 13 4 Mechanical Fitter 42 14 Molten Glass Production 2 1 Pharmaceutical Sales Representation 16 5 Rigger 3 1 Welder 13 4 Average 31

Employment of Unemployed (18. 2) learners after completion of learning programme Learnerships (N=229) Employed after training 64% Still unemployed after training 36% Apprenticeships (N=142) Employed after training 50% Still unemployed after training 50%

Employment of 18. 2 learners who completed learnerships Self-employed 1% Employed by the same company 72% Employed by another company 27%

Employment conditions (learnerships) • Full-time (40 hours or more per week) – 87% • Permanent position – 75%

Income levels (gross p. m. ) of 18. 2 learners who are employed (learnerships) >R 20 000 <R 5 000 9% 10% R 15 000 - R 20 000 23% R 5 000 - R 9 999 22% R 10 000 - R 14 999 36%

Employed 18. 2 learners (learnerships) Different type of work not in the chemical sector 7% Different type of work in the chemical sector 3% Same type of work not in the chemical sector 16% Same type of work in the chemical sector 74%

Employed 18. 2 learners (apprenticeships) Selfemployed 7% (N=5) Employed by the same company 57% Employed by another company 36%

Employment conditions (apprenticeships) • Full-time (40 hours or more per week) – 86% • Permanent position – 62%

Income levels (gross p. m. ) of 18. 2 learners who are employed (artisans) <Less R 5 000 9% >R 20 000 18% R 15 000 - R 20 000 13% R 10 000 - R 14 999 24% R 5 000 - R 9 999 36%

Employed 18. 2 learners (artisans) Different type of work not in the chemical sector 3% Different type of work in the chemical sector 7% Same type of work not the chemical sector 24% Same type of work in the chemical sector 66%

Unemployed artisans (N=82) Welder 15% Electrician 21% Instrument Mechanician 1% Rigger 48% Mechanical Fitter 16%

Unemployed (18. 2) learners who could not get access to employment (artisans) Reason for unemployment Number of times mentioned % No jobs available / economy 68 51 Lack of experience 26 19 Over supply 16 12 Only small contracts available 6 4 Corruption 5 4 Gender discrimination (male dominated) 4 3 Health issues 2 1 Relocation necessary 2 1 Still waiting on contract 2 1 Further studying 2 1 Strikes 1 1 134 100 Total

Unemployed (18. 2) learners who could not get access to employment (learnerships) Reason for unemployment No jobs available / economy Lack of experience Need further training Corruption Over supply Family responsibilities Need to do trade test Waiting for trade test certificate Studying full-time Insufficient contacts / networks Only small contracts available Waiting for learnership certificate Insufficient contacts / networks Foreigners take opportunities away Health issues Total Number of times mentioned 67 44 12 8 6 4 3 4 6 2 1 1 161 % 42 27 7 5 4 2 2 2 4 1 1 1 100

Case studies 1. Bafana Mahlangu – RPL to qualified Boilermaker (Richards Bay) 2. Nompumelelo Mbutho – Chemical Operations learnership (Amanzimtoti)

Preliminary recommendations • Further investigate and address the reasons why some artisans struggle to find employment • Establish a relationship with an intermediary that can assist with the placement of unemployed learners who struggle to find employment after completion of a learning programme • Further support SMMEs in terms of entrepreneurial training • Include entrepreneurial training in all programmes

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