Collecting, modeling, and visualizing network data from educators: A tutorial. | Zendy

Jennifer Watling Neal | Zendy; Zachary P. Neal | Zendy

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Collecting, modeling, and visualizing network data from educators: A tutorial.

Author(s) -

Jennifer Watling Neal,

Zachary P. Neal

Publication year - 2021

Publication title -

school psychology

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.395

H-Index - 69

eISSN - 2578-4226

pISSN - 2578-4218

DOI - 10.1037/spq0000479

Subject(s) - psycinfo , dropout (neural networks) , computer science , field (mathematics) , intervention (counseling) , data science , social network analysis , social network (sociolinguistics) , psychology , world wide web , medline , social media , mathematics , machine learning , psychiatry , political science , pure mathematics , law

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. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

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