Research Articles

Educational outcomes: Pathways and performance in South African high schools

Vijay Reddy, Servaas van der Berg, Dean Janse van Rensburg, Stephen Taylor
South African Journal of Science | Vol 108, No 3/4 | a620 | DOI: https://doi.org/10.4102/sajs.v108i3/4.620 | © 2012 Vijay Reddy, Servaas van der Berg, Dean Janse van Rensburg, Stephen Taylor | This work is licensed under CC Attribution 4.0
Submitted: 07 February 2011 | Published: 14 March 2012

About the author(s)

Vijay Reddy, Human Sciences Research Council, South Africa
Servaas van der Berg, University of Stellenbosch, South Africa
Dean Janse van Rensburg, Human Sciences Research Council, South Africa
Stephen Taylor, University of Stellenbosch, South Africa


Share this article

Bookmark and Share

Abstract

We analysed the pathways and performances in mathematics of high (secondary) school students in South Africa using a panel-like data set of Grade 8 students who participated in the 2002 Trends in International Mathematics and Science Study (TIMSS) and who were tracked to Grade 12 examination data sets. We examined the relationship between TIMSS mathematics performance and reaching Grade 12, the selection of and performance in Grade 12 mathematics, and success rates in the matriculation examination. The progression of students from schools serving middle-class (Subsystem M) and poorer students (Subsystem P, the majority) was compared. Firstly, mathematics achievement scores in South Africa are low and different performance patterns were shown between the two subsystems. Secondly, students who started with similar Grade 8 mathematics scores had different educational outcomes 4 years later. In Subsystem M schools, Grade 8 mathematics scores were a good indicator of who would pass matric, whilst this relationship was not as strong in Subsystem P schools. Thirdly, there was a stronger association between TIMSS Grade 8 scores and subject choice of matric mathematics in Subsystem M schools than in Subsystem P schools. Fourthly, there was a strong correlation between Grade 8 mathematics performance and matric mathematics achievement. Mathematics performance in the earlier years predicted later mathematics performance. To raise exit level outcomes, mathematics scores need to be raised by Grade 8 or earlier. To improve educational and labour market outcomes, the policy priority should be to build foundational knowledge and skills in numeracy.

Keywords

education pathways; foundation phase; early development; TIMSS; secondary education; mathematics

Metrics

Total abstract views: 1055
Total article views: 1921

References


Mbeki T. Address of the President of South Africa, Thabo Mbeki, at the second joint sitting of the third democratic parliament, Cape Town. Speech delivered in Cape Town. 2005 February 11.

Organisation for Economic Co-operation and Development (OECD). Review of national policies for education: South Africa. Paris: OECD; 2008.

Reddy V. State of mathematics and science education: Schools are not equal. Perspect Educ. 2005;23(3):125–138.

Reddy V. Mathematics and science achievement at South African schools in TIMSS 2003. Pretoria: HSRC Press; 2006.

Van der Berg S. Apartheid’s enduring legacy: Inequalities in education. J Afr Econ. 2007;16(5):849–880. http://dx.doi.org/10.1093/jae/ejm017

Fleisch B. Primary education in crisis: Why South African schoolchildren underachieve in reading and mathematics. Cape Town: Juta & Co; 2008.

Simmons J, Alexander L. The determinants of school achievement in developing countries: A review of the research. Econ Dev Cult Change. 1978;26(2):341–357. http://dx.doi.org/10.1086/451019

Fuller B. What school factors raise achievements in the third world? Rev Educ Res. 1987;57(3):255–292. http://dx.doi.org/10.3102/00346543057003255

Van der Berg S, Louw M. South African student performance in regional context. In: Bloch G, Chisholm L, Fleisch B, Mabizela M, editors. Investment choices for South African education. Johannesburg: Wits University Press, 2008; p.49-69.

Bhorat H, Oosthuizen M. Determinants of Grade 12 pass rates in the post-apartheid South African schooling system. J Afr Econ. 2008;18(4):634–666. http://dx.doi.org/10.1093/jae/ejn027

Heyneman SP, Loxley WA. The effect of primary school quality on academic achievement across twenty-nine high and low-income countries. Am J Sociol. 1983;88(6):1162–1194. http://dx.doi.org/10.1086/227799

Glewwe P, Grosh M, Jacoby H, Lockheed M. An eclectic approach to estimating the determinants of achievements in Jamaican primary education. World Bank Econ Rev. 1995;9(2):231–258. http://dx.doi.org/10.1093/wber/9.2.231

Thrupp M. Recent school effectiveness counter-critiques: Problems and possibilities. Brit Educ Res J. 2001;27(4):443–457. http://dx.doi.org/10.1080/01411920120071452

Lee VE, Zuze TL, Ross KN. School effectiveness in 14 sub-Saharan African countries: Links with 6th graders’ reading achievement. Stud Educ Eval. 2005;31:207–246. http://dx.doi.org/10.1016/j.stueduc.2005.05.011

United Nations Educational, Scientific and Cultural Organization (UNESCO). Education for all, the quality imperative, EFA global monitoring report 2005. Paris: UNESCO; 2004.

Luyten H, Visscher A, Witziers B. School effectiveness research: From a review of criticisms to recommendations for further development. Sch Eff Sch Improv. 2005;16(3):249–279. http://dx.doi.org/10.1080/09243450500114884

Goldstein H, Woodhouse G. School effectiveness research and educational policy. Oxford Rev Educ. 2000;26(3):353–363. http://dx.doi.org/10.1080/713688547

Wrigley T. ’School effectiveness’: The problem of reductionism. Brit Educ Res J. 2004;30(2):227–244.

Yu G. Research evidence of school effectiveness in sub-Saharan Africa: EdQual Working Paper No. 7. Bristol: EdQual RPC; 2007.

Robinson R. Pathways to completion: Progression through a university degree. High Educ. 2004;47:1–20. http://dx.doi.org/10.1023/B:HIGH.0000009803.70418.9c

Dalton B, Glennie E, Ingels SJ, Wirt J. Late high school dropouts: Characteristics, experiences, and changes across cohorts, descriptive analysis report, 2009. Washington DC: NCES; 2009.

Ginsburg C, Richter LM, Fleisch B, Norris SA. An analysis of associations between residential and school mobility and educational outcomes in South African urban children: The Birth to Twenty Cohort. Int J Educ Dev. 2011;31(3):213–222. http://dx.doi.org/10.1016/j.ijedudev.2010.03.006

Braddock JH II, Dawkins MP. Ability grouping, aspirations, and attainments: Evidence from the National Educational Longitudinal Study of 1988. J Negro Educ. 1993;62(3):324–336. http://dx.doi.org/10.2307/2295468

Khoo ST, Ainley J. Attitudes, intentions and participation, LSAY research report No. 41. Melbourne: ACER; 2005.

Beutel AM, Anderson KG. Race and the educational expectations of parents and children: The case of South Africa. Sociol Quart. 2008;49(2):335–361. http://dx.doi.org/10.1111/j.1533-8525.2008.00118.x

Cosser M. Studying ambitions: Pathways from Grade 12 and the factors that shape them. Pretoria: HSRC Press; 2009.

Reddy V, Bantwini B, Visser M. Youth into science strategy tracking studies’ report. Report commissioned by the Department of Science & Technology. Pretoria: DST; 2009.

Thomson S. Pathways from school to further education or work: Examining the consequences of Year 12 course choices. LSAY Research Report No 42. Melbourne: ACER; 2005.

Cosser M, Sehlola S. Ambitions revised: Grade 12 learner destinations one year on. Pretoria: HSRC Press; 2009.

Letseka M, Cosser M, Breier M, Visser M. Student retention and graduate destination: Higher education and labour market access and success. Pretoria: HSRC Press; 2009.

Marks GN. The occupations and earnings of young Australians: The role of education and training. LSAY Research Report No. 55. Melbourne: ACER; 2009.

Visser M, Kruss G. Learnerships and skills development in South Africa: A shift to prioritise the young unemployed. J Voc Educ Train. 2009;61(3):357–374. http://dx.doi.org/10.1080/13636820903180384, PMid:2169505

Feinstein L. Inequality in the early cognitive development of British children in the 1970 cohort. Economica. 2003;70:73–97. http://dx.doi.org/10.1111/1468-0335.t01-1-00272

Cunha F, Heckman JJ. Formulating, identifying and estimating the technology of cognitive and noncognitive skill formation. Working paper for the University of Chicago. Chicago, IL: University of Chicago; 2006.

Blanden J, Machin S. Recent changes in intergenerational mobility in Britain. Report for the Sutton Trust. London: Sutton Trust; 2007.

Cunha F, Heckman JJ. The technology of skill formation. Am Econ Rev. 2007;97(2):31–47. http://dx.doi.org/10.1257/aer.97.2.31

Lam D, Ardington C, Leibbrandt M. Schooling as a lottery: Racial differences in school advancement in urban South Africa. J Dev Econ. 2011;95(2):121–136. http://dx.doi.org/10.1016/j.jdeveco.2010.05.005, PMid:21499515

Heckman JJ. Skill formation and the economics of investing in disadvantaged children. Science. 2006;312(5782):1900–1902. http://dx.doi.org/10.1126/science.1128898, PMid:16809525

Brooks-Gunn J, Phelps E, Elder GH Jr. Studying lives through time: Secondary data analyses in developmental psychology. Dev Psychol. 1991;27(6):899–910. http://dx.doi.org/10.1037/0012-1649.27.6.899



Reader Comments

Before posting a comment, read our privacy policy.

Post a comment (login required)

Crossref Citations

No related citations found.