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Rotten apples or just apples and pears? Understanding patterns consistent with cheating in international test data

Author

Listed:
  • Martin Gustafsson

    (ReSEP, Stellenbosch University, and Department of Basic Education)

  • Carol Nuga Deliwe

    (Department of Basic Education)

Abstract

The Southern and Eastern Africa Consortium for Monitoring Educational Quality (SACMEQ) programme has succeeded in generating valuable knowledge about the outcomes of schooling in the region, and in developing capacity to use data, including test data, in governments and amongst researchers. However, there is room for improvements in the programme. The current paper examines the extent to which patterns in the 2000 and 2007 test data suggest cheating occurred. The risk of cheating during the administration of the SACMEQ tests clearly exists, both because in-built controls can be subverted and because all pupils write exactly the same test, which is unlike the situation in a programme such as TIMSS, which employs a matrix sampling test design approach. Data analysis methods developed by Jacob and Levitt (2003) to detect cheating are adapted and then applied to the SACMEQ, but also TIMSS, data. It is concluded that whilst cheating does not substantially change the overall picture of performance derived from the 2000 and 2007 data, or country rankings, noteworthy patterns highly consistent with cheating can be found in some countries, and some regions within countries. Country-level indicators of cheating in SACMEQ correlate remarkably well with World Bank indicators of general corruption. An analysis of conditional correlations within the SACMEQ data reveals that schools serving more socio-economically disadvantaged pupils are more likely to cheat. In one country, having a male school principal is associated with a higher likelihood of cheating.

Suggested Citation

  • Martin Gustafsson & Carol Nuga Deliwe, 2017. "Rotten apples or just apples and pears? Understanding patterns consistent with cheating in international test data," Working Papers 17/2017, Stellenbosch University, Department of Economics.
  • Handle: RePEc:sza:wpaper:wpapers293
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    File URL: https://www.ekon.sun.ac.za/wpapers/2017/wp172017/wp172017.pdf
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    References listed on IDEAS

    as
    1. Battistin, Erich & De Nadai, Michele & Vuri, Daniela, 2017. "Counting rotten apples: Student achievement and score manipulation in Italian elementary Schools," Journal of Econometrics, Elsevier, vol. 200(2), pages 344-362.
    2. Gustafsson, Martin, 2015. "Enrolment ratios and related puzzles in developing countries: Approaches for interrogating the data drawing from the case of South Africa," International Journal of Educational Development, Elsevier, vol. 42(C), pages 63-72.
    3. Dong, Bin & Torgler, Benno, 2013. "Causes of corruption: Evidence from China," China Economic Review, Elsevier, vol. 26(C), pages 152-169.
    4. Brian A. Jacob & Steven D. Levitt, 2003. "Rotten Apples: An Investigation of the Prevalence and Predictors of Teacher Cheating," The Quarterly Journal of Economics, Oxford University Press, vol. 118(3), pages 843-877.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Martin Gustafsson, 2019. "The case for statecraft in education: The NDP, a recent book on governance, and the New Public Management inheritance," Working Papers 16/2019, Stellenbosch University, Department of Economics.
    2. Martin Gustafsson & Carol Nuga Deliwe, 2020. "How is the COVID-19 pandemic affecting educational quality in South Africa? Evidence to date and future risks," Working Papers 23/2020, Stellenbosch University, Department of Economics.

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    More about this item

    Keywords

    SACMEQ; TIMSS; assessment data; cheating; corruption; gender;
    All these keywords.

    JEL classification:

    • C89 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other
    • D73 - Microeconomics - - Analysis of Collective Decision-Making - - - Bureaucracy; Administrative Processes in Public Organizations; Corruption
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education

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