Educational outcomes: Pathways and performance in South African high schools
Keywords:
education pathways, foundation phase, early development, TIMSS, secondary education, mathematics
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.References
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2. Organisation for Economic Co-operation and Development (OECD). Review of national policies for education: South Africa. Paris: OECD; 2008.
3. Reddy V. State of mathematics and science education: Schools are not equal. Perspect Educ. 2005;23(3):125–138.
4. Reddy V. Mathematics and science achievement at South African schools in TIMSS 2003. Pretoria: HSRC Press; 2006.
5. 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
6. Fleisch B. Primary education in crisis: Why South African schoolchildren underachieve in reading and mathematics. Cape Town: Juta & Co; 2008.
7. 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
8. 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
9. 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.
10. 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
11. 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
12. 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
13. 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
14. 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
15. United Nations Educational, Scientific and Cultural Organization (UNESCO). Education for all, the quality imperative, EFA global monitoring report 2005. Paris: UNESCO; 2004.
16. 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
17. 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
18. Wrigley T. ’School effectiveness’: The problem of reductionism. Brit Educ Res J. 2004;30(2):227–244.
19. Yu G. Research evidence of school effectiveness in sub-Saharan Africa: EdQual Working Paper No. 7. Bristol: EdQual RPC; 2007.
20. 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
21. 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.
22. 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
23. 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
24. Khoo ST, Ainley J. Attitudes, intentions and participation, LSAY research report No. 41. Melbourne: ACER; 2005.
25. 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
26. Cosser M. Studying ambitions: Pathways from Grade 12 and the factors that shape them. Pretoria: HSRC Press; 2009.
27. Reddy V, Bantwini B, Visser M. Youth into science strategy tracking studies’ report. Report commissioned by the Department of Science & Technology. Pretoria: DST; 2009.
28. 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.
29. Cosser M, Sehlola S. Ambitions revised: Grade 12 learner destinations one year on. Pretoria: HSRC Press; 2009.
30. 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.
31. Marks GN. The occupations and earnings of young Australians: The role of education and training. LSAY Research Report No. 55. Melbourne: ACER; 2009.
32. 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
33. 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
34. 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.
35. Blanden J, Machin S. Recent changes in intergenerational mobility in Britain. Report for the Sutton Trust. London: Sutton Trust; 2007.
36. 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
37. 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
38. 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
39. 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