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Collecting, Modeling, and Visualizing Network Data From Educators: A Tutorial
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DOI：10.1037/spq0000479.png)
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Abstract
En 中文
Understanding educators' networks can inform the field of school psychology by offering insight into how the structure of social relationships supports the implementation of school-based programs. However, the difficulties of collecting and modeling network data remain barriers to using network methods in school psychology. To overcome these barriers, we provide a step-by-step tutorial for collecting, modeling, and visualizing network data from educators. We draw on an example from a study designed to understand advice networks among middle and high school educators involved in implementing a system-level intervention to prevent school dropout. Impact and Implications Educators often work in teams to deliver services to children and adolescents within school settings. Collecting, modeling, and visualizing network data can help researchers in school psychology understand how these teams communicate or exchange advice and whether this has implications for the implementation of programs and practices. We provide a tutorial for researchers who are interested in collecting, modeling, and visualizing network data from educators.
Keywords:
social network
exponential random graph model
network data collection
network visualization
educators