Speaker
Description
Classroom social network diagnostics have been proposed to be one of effective anti-bullying measures for monitoring bullying and victimization in schools. However, it is not well understood how the classroom climate and the individual personalities of each student are related to the structure of the classroom social networks. In this study, we used network analysis techniques to visualize the network structure, extract communities through modularity optimization, and explore the relationships between network structure indicators, classroom climate, and personality traits. A sample of 160 adolescents (aged 15-16) from four classrooms, each with 40 students, filled in self-report questionnaires on Social Preference, Big Five Inventory and Classroom Climate Inventory. As a result, we found that overall degree centrality had significantly positive correlation with extraversion and school wellness indicating students with high sociability tend to have more friends and a positive attitude toward school. Among the indicators of classroom climate across the four classes—satisfaction, closeness, and discord—significant differences were observed between classes. In a class with higher discord, the overall degree of connectedness within the class was lower. In the communities extracted through modularity optimization within each classroom, those with higher network degree centrality formed communities with greater satisfaction, while those in lower-degree communities had unfairness. These results are expected to offer valuable insights for organizing classes in ways that reduce the likelihood of bullying.
Keywords
social network analysis, classroom climate, big five personality traits
| Please indicate what type of scientific contribution it is | Quantitative method study |
|---|---|
| Please also indicate what kind of contribution it is: | Scientific |
