Enhancing teacher recruitment and retention through decision-making models in education systems
摘要
Teacher recruitment and retention remain critical challenges for education systems worldwide, with far-reaching implications for educational quality and institutional sustainability. Traditional approaches often fail to address the complexity of these issues, neglecting the interplay of multiple conflicting criteria and the inherent uncertainty in decision-making. This gap necessitates advanced decision-making frameworks that can effectively evaluate and prioritize strategies for improving teacher recruitment and retention. To bridge this gap, this study introduces a novel decision-making framework integrating intuitionistic fuzzy sets (IFSs) to handle uncertainty more effectively. The Entropy method is employed to compute objective weights, while the ranking comparison (RANCOM) method determines subjective weights, ensuring a balanced consideration of qualitative and quantitative factors. The weighted aggregated sum product assessment (WASPAS) method is then applied. The framework is validated through sensitivity analysis to assess its robustness and comparative analysis to establish its superiority over traditional methods. The results identify the Golden Ticket Salary Plan