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Submitted
January 22, 2026
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May 14, 2026
Published
July 26, 2026
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Abstract

This study applies time series analysis and ARIMA forecasting to the Ordinary Level Mathematics results of one high school in Bulawayo, Zimbabwe, for the period 2010 to 2022—a period following the 2008–2009 emigration of qualified teachers that was anticipated to disrupt mathematics performance. Secondary results data were smoothed and analyzed in R Studio to identify the underlying trend through regression analysis, and an ARIMA model was fitted to forecast the school's future pass rate. To explain the observed pattern face-to-face interviews were conducted with all ten qualified mathematics teachers at the school. The pass rate followed a repeating cycle of a fall in one year being usually followed by an improvement in the next two years and both the fitted ARIMA (1,1,1) model and trend line suggested a small improvement by the sixteenth year of the series, 2025. Interview evidence linked this cycle chiefly to the rotation of teachers between examination and non-examination classes. The study recommends that the school deploy teachers with a demonstrated record of improving pass rates to examination classes, allocate more revision time, and introduce performance-based incentives while extending this line of research to the district and provincial level.

Keywords

Time Series AnalysisForecastingOrdinary Level MathematicsZIMSEC resultsData smoothingR studioARIMA modelARMA model

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Copyright (c) 2026 Edward Nsingo, Silvanos Chirume

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite
Nsingo, E., & Chirume, S. (2026). ARIMA Forecasting of Ordinary Level Mathematics Pass Rates: A 13-Year Critical Review from a Zimbabwean High School. International Journal of Review in Mathematics Education, 1(3). https://doi.org/10.23917/ijrime.15830
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