Predicting Long-term Outcomes of Educational Interventions Using the   Evolutionary Causal Matrices and Markov Chain Based on Educational   Neuroscience
  We developed a prediction model based on the evolutionary causal matrices (ECM) and the Markov Chain to predict long-term influences of educational interventions on adolescents development. Particularly, we created a computational model predicting longitudinal influences of different types of stories of moral exemplars on adolescents voluntary service participation. We tested whether the developed prediction model can properly predict a long-term longitudinal trend of change in voluntary service participation rate by comparing prediction results and surveyed data. Furthermore, we examined which type of intervention would most effectively promote service engagement and what is the minimum required frequency of intervention to produce a large effect. We discussed the implications of the developed prediction model in educational interventions based on educational neuroscience. 
Hyemin Han, Kangwook Lee and Firat Soylu
stat.AP