Analysis of the Relationship Between Countries’ Economic and Social Indicators and PISA Scores Using Bayesian Confidence Network and Fuzzy Inference Methods

The Program for International Student Assessment (PISA) is one of the important indicators that determine the state of education in countries. In this study, it has been tried to learn relationships between economic indicators for education and Pisa scores. The effects of indicators such as education expenditures, teacher salaries education index, and living quality index on Pisa scores were examined by applying Bayesian network method and fuzzy inference rules. The conditional probabilities between the nodes of the network are expressed with linguistic values. A conditional probability table was used to determine the effect of economic factors on PISA scores fuzzy inference method was applied on the conditional probabilities table for the selected indicators.