Causal Path Analysis of Teaching Competency based on the Structural Causal Model: Focusing on the Comparison across South Korea, England, and Finland using TALIS 2018 data

Based on the structural causal model, this study derived a causal graph that shows the causal relationship between the factors predicting the teaching competency of lower secondary school teachers in South Korea, the UK(England), and Finland. Also, it compared and analyzed the causal path to each country’s teaching competency. To this end, the data of lower secondary school teachers and principals, who participated in TALIS 2018, in Korea, the UK(England), and Finland were analyzed. First, the top 20 factors that predict teaching competency by each country were extracted by applying the mixed-effect random forest technique in consideration of the multi-layer structure of the data. Then, the causal graphs were derived by applying the causal discovery algorithm based on a structural causal model with the extracted predictors. As a result, there were common factors and discrimination factors in the top 20 predictors extracted from each national data, and the causal paths to teaching competency were compared and analyzed in the context of each country based on the causal graph by country. In addition, in the field of education, the possibility of using causal inference based on structural causal models was discussed, and the limitations and implications of this study were presented.