摘要：In the entire world, there is a widespread recognition that evaluation framework is a key to building stronger and fairer academic institution system. All countries emphasize the evaluation not as end in itself but instead an important tool for achieving improved student outcomes. Teacher evaluation typically has two major purposes. First, it seeks to improve the teacher’s own practice by identifying strengths and weaknesses for further professional development and involves helping teachers learn about, reflect on and adjust their practice. Second it is aimed at holding teacher’s accountability for their performance in enhancing student learning. It typically entails performance based career advancement and/or salaries, bonus pay, or the possibility of sanctions for underperformance and usually involves evaluating performance at nodal points in a teacher’s career. The term soft computing represents the combination of emerging problem solving technologies, such as fuzzy logic, probabilistic reasoning, neural networks and genetic algorithms. Each of these technologies provides us with complementary reasoning and searching methods to solve complex real world problems. We have proposed a soft computing model for evaluating teachers’ overall performance using fuzzy logic. There are two different modules namely teachers’ overall performance module-1 (TOP-M1) and teachers’ overall performance module-2 (TOP-M2). First module TOP-M1, calculates teaching performance. Second module TOP-M2, calculates academic and administrative performance. On the bases of teaching performance and academic and administrative performance we calculate overall performance. Software has been developed in MATLAB. This soft computing model for evaluating teachers’ overall performance using fuzzy logic will not only be useful for decision makers to evaluate teachers’ abilities and improve student outcomes but may also be adopted in writing Annual Confidential Reports(ACR) for appraisal of all the teachers of an academic institution. Simulation results verify the performance of our proposed soft computing model for evaluating teachers’ overall performance using fuzzy logic.
