THE EFFECTS OF COMMUNICATION NETWORKS ON STUDENTS' ACADEMIC PERFORMANCE: THE SYNTHETIC APPROACH OF SOCIAL NETWORK ANALYSIS AND DATA MINING FOR EDUCATION

Social networks, as the most important communication tools, have had a profound impact on social aspects of community user interactions and they are used widely in various fields, such as education. Student interaction through different communication networks can affect individual learning and leads to improved academic performance. In this study, a combined approach of social network analysis and educational data mining (decision tree method) was used to study the impact of communication networks, behavior networks and the combination of these two networks on students’ academic performance considering the role of factors such as computer self-efficacy, age, gender and university. The results of this study, which included 139 students, indicate gender is highly prioritised in all three models. Moreover, according to the results all three models had enough confidence level that among them communication networks with higher confidence, accuracy and precision had significant impacts on the prediction of academic performance