Enhancing Teacher Placement in Workforce Management using the Staff Placement Model and J48 Classification

Abstract

Introduction: Effective teacher placement plays a crucial role in ensuring workforce efficiency, improving the quality of education, and enhancing institutional excellence. However, the Ministry of Education Malaysia (MOE) continues to face challenges in aligning teachers’ expertise with school needs. The reliance on administrative considerations through the Teacher Placement Committee (TPC) without predictive capabilities has led to inefficiencies and suboptimal assignments.
Objectives: To develop a systematic, data-driven teacher placement model using classification techniques to enhance decision-making efficiency and to evaluate its effectiveness by comparing its placement decisions with those made by the Teacher Placement Committee (TPC).
Methods: This study employs a methodology that includes a literature review, model development, data collection, and model validation. Data mining techniques were used to analyze teacher placement patterns. The proposed model, adapted from the Staff Placement Model (SPM), integrates factors such as subject specialization, workforce demand, and institutional needs. An experiment was conducted using 5,526 teacher placement applications from the year 2022, considering four key components: demographics, environment, staffing requirements, and human factors
Results: The results indicate that the J48 technique achieved the highest accuracy (96.30%) compared to Decision Tree, Naïve Bayes, Random Forest, and K-Nearest Neighbors. The model's effectiveness was further evaluated using 3,096 new application records. The results showed that the proposed model approved 1,554 placements compared to 1,5421 in the actual decisions. The t-test results also showed a high p-value (p > 0.05), proving that the model's decisions were comparable to those made by the TPC with no significant difference.
Conclusions: In conclusion, the developed staff placement model can be effectively applied to develop a teacher placement model (TPM) at MOE. This TPM model has the potential to serve as an essential decision-support tool for MOE in improving the efficiency of teacher placement in the future.