EducationEducation

Grade progression

Author/s: Katharine Hall
Date: November 2018

Definition

This indicator measures the number and percentage of children who have passed grades 3 and 9 by the appropriate age. Grade 3 progression is based on children aged 10-11 years; Grade 9 progression is based on children aged 16-17 years. The age limit is generous. If a child started school in the year that they turned 7 and progressed one grade every year, they would be expected to complete Grade 3 in the year that they turn 9, and Grade 9 in the year that they turn 15.

Data


Data Source Statistics South Africa (2003 - 2018) General Household Survey 2002 - 2017. Pretoria, Cape Town: Statistics South Africa. Analysis by Katharine Hall & Winnie Sambu, Children's Institute, University of Cape Town.
Notes
  1. Children are defined as persons aged 0 – 17 years. The proportions for this indicator are based on children in the age group appropriate for school level: Completion of Gr 3: 10 – 11 years; Completion of Gr 9: 16 – 17 years.
  2. Population numbers have been rounded off to the nearest thousand.
  3. Sample surveys are always subject to error, and the proportions simply reflect the mid-point of a possible range. The confidence intervals (CIs) indicate the reliability of the estimate at the 95% level. The wider the CI, the more uncertain the proportion. Where CIs overlap for different sub-populations or time periods we cannot be sure that there is a real difference in the proportion, even if the mid-point proportions differ. CIs are represented in the bar graph by vertical lines at the top of each bar.

Systemic evaluations by the Department of Education have recorded very low pass rates in numeracy and literacy among both grade 3 and grade 6 learners.1  Despite measures to address the inherited inequities in the education system through revisions to the legislative and policy frameworks, and the school funding norms, continued disparities in the quality of education offered by schools reinforce existing socio-economic inequalities, limiting the future work opportunities and life chances of children who are born into poor households.2  We have already seen that school attendance rates are very high during the compulsory schooling phase (grade 1 – 9). However, attendance tells us little about the quality of education that children receive, or their progress through the education system. South Africa has poor educational outcomes by international standards,3 and even within Africa, and high rates of grade repetition have been recorded in numerous studies. For example, a study of children’s progress at school found that only about 44% of young adults (aged 21 – 29) had matriculated, and of these less than half had matriculated “on time”.4 This was based on 2008 data from the National Income Dynamics Study. In 2016, only 51% of young people aged 20 – 24 had completed a matric or matric equivalent.5 In South Africa, the labour market returns to education only start kicking in on successful completion of matric, not before. However it is important to monitor progress and grade repetition in the earlier grades as slow progress at school is a strong determinant of school drop-out.6  Assuming that children are enrolled in primary school at the prescribed age (by the year in which they turn seven) and assuming that they do not repeat a grade or drop out of school, they would be expected to have completed the foundation phase (grade 3) by the year that they turn nine, and the general education phase (grade 9) by the year they turn 15. This indicator allows a little more leeway: it measures the number and proportion of children aged 10 and 11 years who have completed a minimum of grade 3, and the proportion of those aged 16 and 17 years who have completed a minimum of grade 9. In other words, it allows for the older cohort in each group to have repeated one grade, or more if they started school in the year before they turned seven.

In 2017, 89% of all children aged 10 and 11 were reported to have completed grade 3. This was up from 78% in 2002. This improvement in progress through the foundation phase was evident across most of the provinces, with significant advances in the Eastern Cape (from 64% to 86%), Limpopo (80% to 95%), Mpumalanga (from 75% to 89%), and KwaZulu-Natal (from 75% to 88%). These improvements have narrowed the gap between provinces: most provinces record a progression rate of more than 89% and the lowest performing provinces are the Eastern Cape and Western Cape – at 86% and 85% respectively. As would be expected, the rate of progression through the entire general education and training band (grades 1 – 9) is lower, as there is more time for children to have repeated or dropped out by grade 9. Just under seventy percent of children aged 16 – 17 years had completed grade 9 in 2017. This represents an overall improvement of 20 percentage points over the 16-year period, from 50% in 2002. Provincial variation is slightly more pronounced than for progress through the foundation phase: Gauteng had the highest rate of grade 9 progression (80%), followed by the Western Cape (74%). Progress was poorest in the Northern and Eastern Cape, where just over half (54% and 56% respectively) of children had completed grade 9 by the expected age. 

As found in other analyses of transitions through school,7  educational attainment (measured by progress through school) varies along economic and racial lines. These differences become more pronounced as children advance through the grades. Gender differences in school progression, on the other hand, have remained consistent and even widened over the years: girls are more likely than boys to progress through school at the expected rate and the difference becomes more pronounced in the higher grades. In 2017, 91% of girls aged 10 – 11 had completed grade 3, compared with 87% of boys; in the same year, 77% of 16 – 17-year-old girls had completed grade 9, compared only 61% of boys in the same age cohort. This finding is consistent with analyses elsewhere.8 There are significant differences in grade completion across income quintiles, especially amongst children who have completed grade 9: in 2017, 64% of 16 – 17-year-olds in the poorest 20% of households completed grade 9, compared to 88% in the richest 20% of households.

Of course, grade progression and grade repetition are not easy to interpret. Prior to grade 12, the promotion of a child to the next grade is based mainly on the assessment of teachers, so the measure may be confounded by the extent of the teacher’s competence to assess the performance of the child. Analyses of the determinants of school progress and drop-out point to a range of factors, many of which are interrelated: there is huge variation in the quality of education offered by schools. These differences largely reflect the historic organisation of schools into racially defined and inequitably resourced education departments. Household-level characteristics and family background also account for some of the variation in grade progression. For example, the level of education achieved by a child’s mother explains some of the difference in whether children are enrolled at an appropriate age and whether they go on to complete matric successfully.9  This in turn suggests that improved educational outcomes for children will have a cumulative positive effect for each subsequent generation.



1 Department of Basic Education (2014) Report on the Annual National Assessments of 2014. Pretoria: DBE.

2 Zoch A (2013) Life Chances and Class: Estimating Inequality of Opportunity in South Africa for Various Life Stages. Stellenbosch Economic Working papers 08/13. Stellenbosch University.
See also:
South African Human Rights Commission & UNICEF (2014) Poverty Traps and Social Exclusion among Children in South Africa 2014. Pretoria: SAHRC & UNICEF.
Spaull N (2015) Schooling in South Africa: How low quality education becomes a poverty trap. In: De Lannoy A, Swartz S, Lake L & Smith C (eds) South African Child Gauge 2015. Children’s Institute, UCT.


3 Van der Berg S, Burger C, Burger R, de Vos M, Gustafsson M, Moses E, Shepherd D, Spaull N, Taylor S, van Broekhuizen H & von Fintel D (2011) Low Quality Education as a Poverty Trap. Stellenbosch: Stellenbosch University.

4 Timæus I, Simelane S & Letsoalo T (2013) Poverty, race and children’s progress at school in South Africa. The Journal of Development Studies, 49(2): 270-284.

5 Southern Africa Labour and Development Research Unit (2018) Youth Explorer. Viewed 20 September 2018: https://youthexplorer.org.za/profiles/country-ZA-south-africa/#education.

6 Statistics South Africa (2016) General Household Survey 2015. Pretoria: StatsSA. Analysis by Katharine Hall, Children’s Institute, UCT.
For more information on school drop-out, see also:
Branson N, Hofmeyer C & Lam D (2014) Progress through school and the determinants of school dropout in South Africa. Development Southern Africa, 31(1): 106-126.
Gustafsson M (2011) The When and How of Leaving School: The Policy Implications of New Evidence on Secondary School in South Africa. Stellenbosch Economic Working Papers 09/11. Stellenbosch: Stellenbosch University.

7 Branson N & Lam D (2010) Educational inequality in South Africa: Evidence from the National Income Dynamics Study. Studies in Economics and Econometrics, 34(3): 85-105;
See also:
Lam D & Seekings J (2005) Transitions to Adulthood in Urban South Africa: Evidence from a Panel Survey. Prepared for the International Union for the Scientific Study of Population (IUSSP) general conference, 18 – 23 July 2005, Tours, France;
Van der Berg et al, 2011 (above)


8 See, for example: Fleisch B & Shindler J (2009) Gender repetition: School access, transitions and equity in the ‘Birth-to-Twenty’ cohort panel study in urban South Africa. Comparative Education, 45(2): 265-279;
Branson et al, 2014 (above).

9 Timaeus et al 2013 (above).
The General Household Survey asks: "What is the highest level of education that ... has sucessfully completed?"
The response categories are broken down into individual grades. This indicator reflects those who have successfully completed Grade 3 or higher (for the younger age group), and Grade 9 or higher (for the older age group).

The numbers are derived from the General Household Survey, a multi-purpose annual survey conducted by the national statistical agency, Statistics South Africa, to collect information on a range of topics from households in the country’s nine provinces. The survey uses a sample of 30,000 households. These are drawn from Census enumeration areas using multi-stage stratified sampling and probability proportional to size principles. The resulting estimates should be representative of all households in South Africa.

The GHS sample consists of households and does not cover other collective institutionalised living-quarters such as boarding schools, orphanages, students’ hostels, old-age homes, hospitals, prisons, military barracks and workers’ hostels. These exclusions should not have a noticeable impact on the findings in respect of children.

Changes in sample frame and stratification
The sample design for the 2015 GHS was based on a master sample that was designed in 2013 as a general purpose sampling frame to be used for all Stats SA household-based surveys. The same master sample is shared by the GHS, the Quarterly Labour Force Survey, the Living Conditions Survey and the Income and Expenditure Survey. The 2013 master sample is based on information collected during the 2011 population census. The previous master sample for the GHS was used for the first time in 2008, and the one before that in 2004. These again differed from the master sample used in the first two years of the GHS: 2002 and 2003. Thus there have been four different sampling frames during the 14-year history of the annual GHS, with the changes occurring in 2004, 2008 and 2013. In addition, there have been changes in the method of stratification over the years. These changes could compromise comparability across iterations of the survey to some extent, although it is common practice to use the GHS for longitudinal monitoring and many of the official trend analyses are drawn from this survey.

Weights
Person and household weights are provided by Stats SA and are applied in Children Count analyses to give estimates at the provincial and national levels. The GHS weights are derived from Stats SA’s mid-year population estimates. The population estimates are based on a model that is revised from time to time when it is possible to calibrate the population model to larger population surveys (such as the Community Survey) or to census data.

In 2013, Stats SA revised the demographic model to produce a new series of mid-year population estimates. The 2013 model drew on the 2011 census (along with vital registration, antenatal and other administrative data) but was a “smoothed” model that did not mimic the unusual shape of the age distribution found in the census. The results of the 2011 census were initially questioned because it seemed to over-count children in the 0 – 4 age group and under-count children in the 4 – 14-year group.

The 2013 model was used to adjust the benchmarking for all previous GHS data sets, which were re-released with the revised population weights by Stats SA, and was still used to calculate weights for the GHS up to and including 2015, even though it is now known that the mid-year population estimates on which the weights are based are incorrect. All the Children Count indicators were re-analysed retrospectively, using the revised weights provided by Stats SA, based on the 2013 model. The estimates are therefore comparable over the period 2002 to 2015. The revised weights particularly affected estimates for the years 2002 – 2007.

It is now thought that the fertility rates recorded in the 2011 population census may have been an accurate reflection of recent trends, with an unexplained upswing in fertility around 2009 after which fertility rates declined gradually. Similar patterns were found in the vital registration data as more births were reported retrospectively to the Department of Home Affairs, and in administrative data from schools, compiled by the Department of Basic Education. In effect, this means that there may be more children in South Africa than appear from the analyses presented in these analyses, where we have applied weights based on a model that it is now known to be inaccurate.

Disaggregation
Statistics South Africa suggests caution when attempting to interpret data generated at low level disaggregation. The population estimates are benchmarked at the national level in terms of age, sex and population group while at provincial level, benchmarking is by population group only. This could mean that estimates derived from any further disaggregation of the provincial data below the population group may not be robust enough.

Reporting error
Error may be present due to the methodology used, i.e. the questionnaire is administered to only one respondent in the household who is expected to provide information about all other members of the household. Not all respondents will have accurate information about all children in the household. In instances where the respondent did not or could not provide an answer, this was recorded as “unspecified” (no response) or “don’t know” (the respondent stated that they didn’t know the answer).

For more information on the methods of the General Household Survey, see the metadata for the respective survey years, available on Nesstar  or DataFirst