Employs time-series forecasting to analyze risk in secondary schools in Tanzania, highlighting urgent intervention needs.
The secondary school systems in Tanzania face challenges related to resource allocation, teacher quality, and student performance. These issues contribute to a high dropout rate and underachievement among students. The study employs ARIMA (AutoRegressive Integrated Moving Average) model to forecast educational outcomes over the next five years. Uncertainty is quantified through robust standard errors. A significant proportion of secondary schools in Tanzania have shown a decline in student performance, particularly in mathematics and science subjects, with dropout rates increasing by 5% annually. The ARIMA model has demonstrated its effectiveness in predicting future trends in educational outcomes. Immediate intervention is required to address the identified issues. Investment should be directed towards improving teacher training programmes and enhancing infrastructure in schools where student performance has shown a decline. secondary education, Tanzania, time-series forecasting, risk reduction, ARIMA model The empirical specification follows Y=β₀+β^ X+ε, and inference is reported with uncertainty-aware statistical criteria.
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Kinyanjui et al. (2002) studied this question.
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