Time Series Analysis of Mathematics Results at a High School in Zimbabwe - Nsingo, Edward; Chirume, Silvanos (Universitas Muhammadiyah Surakarta, 2026)
This research involves time series analysis and forecasting of the Ordinary Level Mathematics results. During 2008 to 2009 many educators had left the country seeking higher salaries, leading to severe staff shortages in schools. This and other reasons were anticipated to impact negatively on “O” Level Mathematics results. Data for the years 2010 to 2022 were collected from one high school in Bulawayo. The data were meticulously analysed, with a particular emphasis on identifying the underlying trend through data smoothing techniques. Advanced computer software R studio was used to conduct regression analysis and generate trend lines and time series graphs. Additionally, an ARIMA (autoregressive integrated moving average) forecasting model was applied to forecast and predict the school’s future pass rate in Ordinary Level Mathematics. Interviews with the 10 qualified teachers at the school were carried out to identify potential causes for changes in the pass rate of Mathematics at the High School. By understanding how pass rates may evolve over time, stakeholders like parents, the school and government authorities can make informed decisions and implement strategic measures to enhance academic performance in the long run. The study noted that the pass rate of the school was going to slightly improve, and the school was therefore recommended to deploy the hardworking teachers, who had a history of improving the pass rate to the examination writing classes so that the pass rate could increase uniformly and to give them more teaching and revision time and incentives. The study also recommends further research.