Prediction of Mobile Phone Dependence Using Bayesian Networks

Bayesian Networks have been widely used in various domains, but they have been rarely used in educational domain. In this paper, we discover a Bayesian Network model to figure out variables related to adolescents' mobile phone dependence and their influences. For this study, Markov Blanket is used to identify the strongly related variables with the Korea Children and Youth Panel Survey (KCYPS) data. From the analysis with the discovered BN, "attention ability", "depression", "caregiver's abuse", "fandom activity", and "aggression" are extracted as the variables related to adolescents' mobile phone dependence. These results suggest that considering the variables and their interactions are useful to adjust adolescent's mobile phone dependence. This paper also shows Bayesian Networks are adequate to find the interdependence of variables and their causal relationships in educational domain.