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South African Schooling: The Enigma of Inequality pp 25–45Cite as

Educational Outcomes in Post-apartheid South Africa: Signs of Progress Despite Great Inequality

Part of the Policy Implications of Research in Education book series (PIRE,volume 10)

Abstract

This chapter examines grade attainment, assessment and examinations data to detect changes in South Africa’s educational inequality over an extended period. The available data permit long-range trends with respect to attainment, and here inequalities have declined substantially. Data on learning outcomes cover a shorter period, but indicate that since around 2002, inequalities have declined. TIMSS Grade 9 data are clearly the easiest to interpret, but SACMEQ and PIRLS data point to similar trends. Moreover, Grade 12 examinations data point to the number of black African youths attaining results which would allow them enter into mathematically-oriented university programmes increasing by 65% between 2002 and 2016. Yet in 2016 white youths were still seven times more likely to achieve this status than black African youths. Reductions in inequality have occurred while average performance has improved markedly according to TIMSS, though the data suggest improvements have slowed down since around 2011. Standard measures of inequality with respect to learning outcomes indicate that inequality in South Africa is as high as that in other developing countries with similarly weak performance averages. However, South Africa’s inequality is driven to an exceptionally large degree by below-expectation performance in around half of all schools.

Keywords

  • International assessments
  • TIMSS
  • PILRS
  • SACMEQ
  • educational inequality
  • performance trends
  • social gradients

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Notes

  1. 1.

    The slight downward trend in attainment levels for the most recent cohorts towards the end of the period is because some members of the 1990 cohort were still engaged in education at the time of the 2011 census, mainly in universities (university education is included in years of education attained).

  2. 2.

    There is some exaggeration in the proportion responding that they have completed matric. Other surveys of StatsSA show that some people who indicate that the highest grade they have completed is matric admit in further questioning that they reached but did not pass matric.

  3. 3.

    See Carnoy et al. (2015, p. 9). Note one PISA point is around 0.01 of a Brazilian standard deviation.

  4. 4.

    Programme for International Student Assessment (PISA).

  5. 5.

    Scores below 300 are often regarded as less reliable in TIMSS and PIRLS, inter alia because they may be strongly influenced by guesswork where there are multiple choice questions. This of course should cancel out to some extent across individuals. However, even if one accepts that this score is a ‘floor’ that cannot be exactly determined, the rise since then has been so large that there can be no question that there has been considerable improvement, although the magnitude of improvement is less clear.

  6. 6.

    In the absence of technical documentation about the SACMEQ equating of scores across the 2007 and 2013 surveys, the massive gains observed in SACMEQ 2013 cannot be verified.

  7. 7.

    As discussed above, greater clarity is needed around the inconsistencies between the SACMEQ classical and IRT scores, clarity which should become possible when the technical documentation on the calculation of the IRT scores becomes available.

  8. 8.

    Theil T has been the preferred measure for gauging the inequality of test scores in a few analyses – see for instance Crouch and Gustafsson (2018) and Sahn and Younger (2007).

  9. 9.

    The socio-economic status of schools was derived applying Multiple Correspondence Analysis on a set of 31 possessions of school children and their households, and can thus be considered an asset or wealth index. The proportion of the variance statistically “explained” was the coefficient of determination (R-squared) in determined in ordinary least square regressions, with population weights applied.

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Authors and Affiliations

  1. Resep, University of Stellenbosch, Stellenbosch, South Africa

    Servaas van der Berg

  2. Department of Basic Education and Resep, University of Stellenbosch, Stellenbosch, South Africa

    Martin Gustafsson

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  1. Servaas van der Berg
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  2. Martin Gustafsson
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Correspondence to Servaas van der Berg .

Editor information

Editors and Affiliations

  1. Department of Economics, Stellenbosch University, Cape Town, South Africa

    Dr. Nic Spaull

  2. Faculty of Education, Stellenbosch University, Cape Town, South Africa

    Prof. Jonathan D. Jansen

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van der Berg, S., Gustafsson, M. (2019). Educational Outcomes in Post-apartheid South Africa: Signs of Progress Despite Great Inequality. In: Spaull, N., Jansen, J. (eds) South African Schooling: The Enigma of Inequality. Policy Implications of Research in Education, vol 10. Springer, Cham. https://doi.org/10.1007/978-3-030-18811-5_2

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  • DOI: https://doi.org/10.1007/978-3-030-18811-5_2

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