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Data · dataset · 2026

Rural science teachers' collaboration, advice-seeking, and friendship networks: Social network analysis data

Listed in Teesside University Research Data Repository

This dataset contains longitudinal social network data from rural science teachers collected in 2023 and 2024.

Description

The dataset includes three types of professional networks: collaboration, advice seeking, and friendship. These networks were constructed from teacher survey nominations and are represented as directed adjacency matrices with consistent node ordering across both time points.

The data are structured to support cross sectional Exponential Random Graph Model (ERGM) analyses and longitudinal Separable Temporal ERGM (STERGM) analyses of tie formation and persistence. In addition to the network matrices, the dataset includes a dyadic geographic distance matrix representing estimated driving distances between teachers’ primary school locations. These distances were calculated using Google Maps and were used as edge level covariates in network models examining the role of geographic proximity in professional relationship formation.

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A matched teacher attribute dataset is also included. This file contains anonymized demographic, professional background, subject specialization, grade level assignment, regional affiliation, and participation indicators for the Technology Mediated Lesson Study (TMLS) professional development program. These attributes were used as node level predictors in ERGM and STERGM analyses examining how teacher characteristics and contextual factors relate to professional network development over time.

All identifiers were anonymized prior to public release. Numeric codes do not correspond to actual individuals, schools, or districts. Diagonal entries in the network matrices reflect occasional self-nominations recorded in the original survey data and were retained for transparency.

For most network modeling applications, these self-ties should be constrained to zero. The dataset is intended to support replication of published analyses on rural teacher professional networks and to facilitate secondary research on professional learning, teacher collaboration, and geographically distributed professional development.

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Longitudinal study 65%
Provenance · 1 source records, 8 field assertions
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Teesside University Research Data Repositoryoai:data.mendeley.com/29kfrxdx5r.115 h agoJSON v1
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