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A predictive framework for sustainable youth skills development

Arnesh Telukdarie (Faculty of Engineering and Built, Environment University of Johannesburg, Johannesburg, South Africa)
Megashnee Munsamy (University of Johannesburg - Doornfontein Campus, Doornfontein, South Africa)
Popopo Jonas Mohlala (Good and Beverage Sector Training Authority, Johannesburg, South Africa)
Lesego Lydia Monnapula (Food and Beverage SETA, Johannesburg, South Africa)
Radhakrishnan Viswanathan (University of Johannesburg - Doornfontein Campus, Doornfontein, South Africa)

Higher Education, Skills and Work-Based Learning

ISSN: 2042-3896

Article publication date: 29 November 2021

Issue publication date: 15 July 2022

263

Abstract

Purpose

The purpose of this research is to investigate sustainable strategies for skills development that is specific to the youth of South Africa. International and South African data are statistically analysed and quantified to provide inputs for the systems dynamics (SD)-based predictive skills model. The skills model simulates the impact of barriers and drivers on youth skills development towards identification of focus areas for improvement.

Design/methodology/approach

The research adopts a mixed-methods approach. The study begins with an explorative literature study on skills development, with the findings applied in developing (1) South African specific research instruments for small, medium and micro enterprises (SMMEs) and skills programme grant recipients and (2) a conceptual framework of the SD predictive skills model. The responses to the South African specific instruments are analysed via confirmatory factor analysis (CFA), which quantifies the input coefficients to the system dynamics model. To quantify the global inputs for the SD model, an in-depth literature review of the global skills development initiatives is conducted. The SD model output on skills, for the South African inputs, is comparatively evaluated against global inputs.

Findings

The paper details the results of the literature analysis, instrument analyses, CFA and SD model. The instrument results rank experience, skills and interactions with experts and work-based learning as most important. South African and global learners identify networking as the primary medium for identifying training and employment opportunities. South African and global learners also identify qualifications and work-based experience as key to finding employment. The quantified results of the SA and global analysis are used as inputs in the SD model to deliver a forecasting tool. The SD model finds that the global data provide for better development of the skills base than the South African inputs. The key focus areas identified for improvement in South Africa include networking, work-based experience and a reduction in administrative requirements.

Originality/value

The research's originality resides in the ability to predict the impact of drivers and barriers on skills development. This research sought to transform qualitative global and South African inputs into a consolidated, predictive systems-based model. The SD model can be adopted as an indicator of drivers and barriers focused towards the optimisation of skills development.

Keywords

Acknowledgements

The project is funded by the FoodBev Manufacturing SETA. The team would also like to thank the University of Johannesburg for supporting the research.

Citation

Telukdarie, A., Munsamy, M., Mohlala, P.J., Monnapula, L.L. and Viswanathan, R. (2022), "A predictive framework for sustainable youth skills development", Higher Education, Skills and Work-Based Learning, Vol. 12 No. 4, pp. 661-673. https://doi.org/10.1108/HESWBL-01-2021-0002

Publisher

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Emerald Publishing Limited

Copyright © 2021, Emerald Publishing Limited

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