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Learner flow through patterns in the Western Cape using CEMIS datasets from 2007 to 2014: A longitudinal cohort analysis


  • Chris van Wyk

    () (Department of Economics, Stellenbosch University)

  • Anderson Gondwe

    () (Department of Economics, Stellenbosch University)

  • Pierre de Villiers

    () (Department of Economics, Stellenbosch University)


The aim of the study was to track learners as a group or cohort over a specified period of time. This longitudinal data cohort analysis was to determine how successful learners progressed through the Western Cape public education system and how many eventually dropped out of this system. The Central Education Management Information System (CEMIS) datasets from 2007-2014 were used to create a longitudinal dataset of individual learners. The study shows the importance of unit-level records. With the availability of unit-level learner records key questions can be answered such as: “What is the profile of the learners who dropped out of the system, or what is the profile of the learners who progressed without any repetition?” When individual learner-unit records are available one can track learners as a group or cohort over a specified period of time. Longitudinal cohort tracking provides a more complete picture and true reflection of the education system about the progress (dropout and repetition) of learners. In order to achieve the goals in this study, the following methods were used: cross-sectional analysis of patterns and trends in the flow of learners in the Western Cape between 2007 and 2014 and a longitudinal cohort analysis to determine progression of learners through the education system without repetition, repetition of learners who nevertheless remain in the system and dropping out of learners. The study clearly shows high repetition in primary school. Most learners progressed through the system without repeating, but a high percentage also repeated one or more grades but remained the system. The study shows evidence of high dropout in secondary school. This is in contrast with the primary school phase where a high repetition rate but a lower dropout was recorded. Although there is movement out of public schools into independent schools, and out of the Western Cape to other provinces, the most likely cause of dropping out of the CEMIS data in high schools is actual dropping out of school. Furthermore, the study has shown a particularly high repetition rate of Grade 9 learners and a high dropout of learners after Grade 9. Hence, it was informative to follow a number of Grade 9 cohorts in order to determine the consistency of trends in repetition, dropout and completion over time. Perhaps more important is the clear evidence that repetition in Grade 9 is the precursor to almost inevitable dropping out of school without completing matric.

Suggested Citation

  • Chris van Wyk & Anderson Gondwe & Pierre de Villiers, 2017. "Learner flow through patterns in the Western Cape using CEMIS datasets from 2007 to 2014: A longitudinal cohort analysis," Working Papers 02/2017, Stellenbosch University, Department of Economics.
  • Handle: RePEc:sza:wpaper:wpapers278

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    Blog mentions

    As found by, the blog aggregator for Economics research:
    1. Bad boys, what you gonna do?
      by Johan Fourie in Johan Fourie's Blog on 2018-03-26 06:30:25


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. Hendrik van Broekhuizen & Nic Spaull, 2017. "The ‘Martha Effect’: The compounding female advantage in South African higher education," Working Papers 14/2017, Stellenbosch University, Department of Economics.
    2. Marisa von Fintel & Servaas van der Berg, 2017. "What a difference a good school makes! Persistence in academic performance and the impact of school quality," Working Papers 07/2017, Stellenbosch University, Department of Economics, revised 2017.
    3. Servaas van der Berg & Gabrielle Wills & Rebecca Selkirk & Charles Adams & Chris van Wyk, 2019. "The cost of repetition in South Africa," Working Papers 13/2019, Stellenbosch University, Department of Economics.

    More about this item


    longitudinal cohort analysis; unit-level records; cross-sectional analysis; repetition; unique identifier; pseudo cohorts; primary school; secondary school;

    JEL classification:

    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • Y10 - Miscellaneous Categories - - Data: Tables and Charts - - - Data: Tables and Charts

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