Evaluation of Teacher Performance using HybPSOFA - A Hybrid Approach

Evaluating teacher performance is essential for enhancing educational quality, but accurately estimating the performance is very challenging due to the complexity and subjectivity of the assessment criteria. It is a good real-time problem where optimization algorithms have utmost application. This paper investigates the use of metaheuristic algorithms, such as Particle Swarm Optimization (PSO), the Firefly Algorithm (FA) and proposed HybPSO-FA approach, to estimate the teacher performance. By combining the strengths of both PSO and Firefly algorithms, the hybrid technique aims to optimize performance estimation while minimizing computational complexity. The results of the proposed method indicate that the hybrid algorithm significantly outperforms the standalone methods in terms of achieving the optimal value for teacher performance evaluation and convergence speed. This study highlights the potential of using hybrid optimization techniques for performance evaluation in academics having various criteria, making them more reliable and efficient for use in educational institutions.