Applications of Fuzzy Logic and Artificial Neural Networks in Evaluation and Ranking of Teachers Based on “Framework for Teaching” Model

Abstract

Evaluation of teachers is considered as one of main educational policy. And suggests teaching improvement strategies to achieve educational development. Framework for teaching is one of evaluation models to achieve this goal (Danielson,1996). This model includes four, planning and preparation, the classroom environment,. instruction, and professional responsibilities aspects. These aspects describe properties and behaviors of teachers. According to ranking, teachers classified in four groups by their performance. This method based on four-valued logic. Evaluation of teachers by four values leads to failure in relative justice, unrealistic equality and inequalities. Also, there are complexities of evaluation process and probable human errors in this method. In this study , we will develop a solution based on Neuro-fuzzy evaluation system. In this method the inputs of the system are based on fuzzy logic that includes advantage of every criterion. Outputs of fuzzy will be inputs of the neural network system and finally we will isolate patterns by artificial neural network. This system will be implement in the software environment and it makes the evaluation process easier and more precisely than before. Overall, this model could be as a basement method for precise evaluation of educational activities, deserve to achieve educational degrees, ranking and payment of teachers’ salaries in education system.