article · Education Sciences
Teacher absenteeism across South African provinces represents a critical in-class factor influencing learner performance and the effectiveness of education. Using provincial data from the Department of Basic Education, statistical time series techniques including exponential smoothing, moving averages, and seasonal autoregressive integrated moving average models were used to examine absenteeism patterns. The performance of these models was evaluated using standard statistical measures, specifically mean square error and mean absolute percentage error. The analysis revealed that the rate of teacher absenteeism experienced a statistically significant increase between 2011 and 2017. Furthermore, this perspective was shared by over half of the general public, varying by province type. These analytical insights provide educational authorities and school leadership with clear evidence regarding absenteeism trends, supporting the design and execution of targeted interventions to address and reduce missed teaching time across schools.
Teacher absenteeism directly affects student learning outcomes and overall educational progress. Identifying provincial trends through rigorous time series forecasting gives education ministries and school administrators the factual basis needed to spot worsening patterns. Understanding these shifts helps decision-makers deploy targeted support and accountability measures to keep educators in classrooms where they are needed most.
The forecasting models represent early-stage analytical tools that could be integrated into administrative software used by education departments and school governance bodies. While not currently packaged as a commercial product, the methodology offers applied predictive capabilities for workforce monitoring. Real-world adoption would require translating these time series evaluations into operational dashboards for public sector education planners to track and manage staff attendance.
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The aim of this research was to analyze the changes in the rate of teacher absenteeism among South African provinces as a major in-class factor contributing to student performance and effective learning. Time series analysis of exponential smoothing, moving average, and seasonal autoregressive integrated moving average model (SARIMA) were applied to model and assess the designed hypothesis as a major factor for educational advancement using different provincial data input from the Department of Basic Education in South Africa. The performances of all the models were analyzed using statistical indexes: Mean Square Error (MSE) and Mean Absolute Percentage Error (MAPE). The overall performance showed that the absence rate increased statistically significantly from 2011 to 2017. Thus, this opinion was held by more than half of the general populace depending on the province type. The findings of this research could assist the management of the basic education department in general, and in schools in particular, to understand the problem of absenteeism and thereby enabling the implementation of effective strategies that can be used to curb the practice.
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DOI: 10.3390/educsci10080189
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