Forecasting Success Rates in the 2025-2030 High School Exam in Jordan Using Time Series Analysis

This study applied the ARIMA (1,1,2) model to develop a predictive framework for general success rates of General Secondary Education Certificate students in Jordan, based on annual data from 2005 to 2024 (n = 20). Using the Box–Jenkins time series analysis methodology—including model identification, parameter estimation, diagnostic checking, and forecasting—the ARIMA (1,1,2) specification was identified as the best fit according to the Akaike Information Criterion (AIC) and the Hannan–Quinn Criterion (HQ). All model parameters were statistically significant, and the model passed key accuracy diagnostics. Forecasts for the years 2025 through 2030 indicate a projected increase in success rates, ranging between 61% and 65%. These forecasts closely reflect observed historical trends, confirming the model’s robustness and predictive validity. The study recommends adopting ARIMA modeling in educational forecasting to support data-driven planning and policymaking. Keywords: Forecasting, Success Rate, High School, Box-Jenkins Methodology, Time series.