Predicting Long-term Outcomes of Educational Interventions Using the Evolutionary Causal Matrices and Markov Chain Based on Educational Neuroscience

Publication date: Available online 24 November 2016 Source:Trends in Neuroscience and Education Author(s): Hyemin Han, Kangwook Lee, Firat Soylu 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.
Source: Trends in Neuroscience and Education - Category: Neuroscience Source Type: research