Soft-computing methods applied in parameter analysis of educational models

Abstract

Educational environments are different in each country, though the subjects are almost the same: students, families, teachers, schools, school systems, government supervision — ministry. The system parameters' relationships are determined using similar factors: the overall economic situation, the organization of the education system, the financial support of the state, and others. But still, the effectiveness of the systems is different. The aim of this research is to explore the correlations of the factors in the education systems, furthermore, to model its functionality and examine the effectiveness of various education systems. A possible method for these examinations is the fuzzy cognitive map technology, since it provides an opportunity for the qualitative description of the relationships and parameters. The first experimental group of this study is taken from the Serbian education system. The first task was to collect the data set and the basic statistical processing of the collected data. Then the authors started with the construction of the basic rules of inference, based on the experts' knowledge about the correlations between the system parameters. The Mamdani type inference system was constructed, using statistical analysis of the parameters to determine the membership functions. Summarizing the observations from the previous model and based on statistical correlations of the system parameters, the authors then constructed a static cognitive map, which was tested with various scenarios. This cognitive map form the basis for further investigation and the trained fuzzy cognitive map construction. The tools implemented here are presented in the second section of the paper, while the third section describes the realization of the model. The authors' vision for further developments and ideas are given in the closing section.