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Learner flow through patterns in the Western Cape using CEMIS datasets from 2007 to 2019: A longitudinal cohort analysis

Author

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  • Chris van Wyk

    (Department of Economics, Stellenbosch University)

Abstract

The availability of individual learner-unit records allows one to track learners as a group or cohort over a specified period. Longitudinal cohort tracking provides a more complete picture of the progress of learners (dropout and repetition) in the education system. Expanding on the findings of Van Wyk, Gondwe and De Villiers (2017) by using a longitudinal dataset, the aim of this study was to track learners from Grade 1 to Grade 12 as a group or cohort over a longer specified period (2007-2019). This longitudinal data cohort analysis explored how successful learners progressed through the Western Cape public education system and how many eventually dropped out of this system. We used the Central Education Management Information System (CEMIS) datasets from 2007-2019 to create a longitudinal dataset of individual learners. The analysis reveals the importance of unit-level records. With the availability of unit-level learner records, key questions 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?” can be answered. In order to achieve the goals of this study, we first conducted a cross-sectional analysis of the patterns and trends of the flow of learners between 2007 and 2019 in the Western Cape. Thereafter, we conducted a longitudinal cohort analysis of learners to determine progression with or without repetition and who dropped out of the Western Cape public education system. The findings show considerable repetition in primary school. While most learners progressed through the system without repeating, a relatively high percentage also repeated one or more grades but remained in the system. We also found higher repetition and high dropout in secondary school. These findings contrast with the primary school phase, where lower dropout was evident. A further key finding was a significant decrease of repetition rates since 2015, particularly in Grades 1 and 9, and to a lesser extent in Grades 10 and 11. These findings point to enhanced internal efficiency in the Western Cape public education system over this period.

Suggested Citation

  • Chris van Wyk, 2021. "Learner flow through patterns in the Western Cape using CEMIS datasets from 2007 to 2019: A longitudinal cohort analysis," Working Papers 01/2021, Stellenbosch University, Department of Economics.
    • Handle: RePEc:sza:wpaper:wpapers361
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    References listed on IDEAS

    as
    1. Bentaouet Kattan, Raja & Szekely, Miguel, 2014. "Dropout in upper secondary education in Mexico : patterns, consequences and possible causes," Policy Research Working Paper Series 7083, The World Bank.
    2. Jesal Kika & Janeli Kotze, 2019. "Unpacking Grade Repitition Patterns in Light of the Progression Policy in the Further Education and Training Phase," SALDRU Working Papers 243, Southern Africa Labour and Development Research Unit, University of Cape Town.
    3. Nicola Branson & David Lam & Linda Zuze, 2012. "Education: Analysis of the NIDS Wave 1 and 2 Datasets," SALDRU Working Papers 81, Southern Africa Labour and Development Research Unit, University of Cape Town.
    4. 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.
    5. Servaas van der Berg & Chris van Wyk & Rebecca Selkirk & Kate Rich & Nicola Deghaye, 2019. "The promise of SA-SAMS & DDD data for tracking progression, repetition and drop-out," Working Papers 17/2019, Stellenbosch University, Department of Economics.
    6. 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.
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    More about this item

    Keywords

    longitudinal cohort analysis; unit-level records; cross-sectional analysis; repetition; unique identifier; pseudo cohorts; primary school; secondary school; internal efficiency;
    All these keywords.

    JEL classification:

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

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