Developing a Model for Performance Evaluaion of Teachers in Electronic Education System Using Adaptive Neuro Fuzzy Inference System (ANFIS)

According to the significant evolution of learning systems in recent years and the prevailing conditions of human life due to the epidemic of COVID 19 virus, the importance of e-learning in the learning management system is undeniable. This has made the role of teachers in education systems more prominent than ever. Accordingly, the aim of this study is to provide an intelligent adaptive neuro fuzzy inference system (ANFIS) to evaluate the performance of teachers in e-learning system, especially in academic institutions.

In terms of method, this research is descriptive and from the objective point of view it's applied. In this research, a quantitative approach has been used to design a model for evaluating the performance of teachers in the e-learning system. The statistical population of the study included experts in the field of information technology management of the Islamic Azad University of Yazd Province. Based on the pre-determined specifications, it includes 29 people. Due to the limited number of under study elements, a questionnaire was sent to all elements of the statistical population where 17 experts answered the questions. In this study, an adaptive neuro fuzzy inference system (ANFIS) method has been used to analyze the performance of teachers in educational institutions.  

This system is based on 4 main factors (teaching learning process, teaching method, research orientation and individual capabilities) and 16 sub-factors in the teacher evaluation process. The designed ANFIS system classifies the performance of teachers into four predefined categories: teachers need for training, teachers with good skills, teachers who are very good and teachers who are excellent.

The designed system is a useful tool for evaluating teachers and providing appropriate feedback on their strengths and weaknesses to improve their performance.