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How does the social capital of novice teachers impact their career decision to stay in or leave their current teaching position?

How does the social capital of novice teachers impact their career decision to stay in or leave their current teaching position?
How does the social capital of novice teachers impact their career decision to stay in or leave their current teaching position?
Teacher turnover within the first five years remains a persistent challenge in England. While existing literature has identified a range of individual and organisational factors that contribute to beginning teacher turnover, less attention has been paid to beginning teachers’ social networks, and the role of personal networks in teacher retention remains underexplored. This study addresses the gap by studying how the support beginning teachers receive from their network members shape their career decisions to stay in or leave their teaching position.
This study adopted an interpretivist paradigm and informed by Interpretive Description design. Online interviews were conducted with 23 participants with less than five years of teaching experiences in England, including four teachers who had already left teaching, 11 with a leaving intention, and eight with a staying intention. Qualitative egocentric social network analysis was adopted in this study, with which beginning teachers’ network diagrams were used as both descriptive visual data and interview stimuli, and interview data were used to reflect and interpret their working experience from a network perspective. Reflexive thematic analysis was used to analyse the qualitative interview data. Four subthemes were generated through the analysis of the data — emotional, instrumental, appraisal and informational support — which align with House’s social support theory.
The findings demonstrate that beginning teachers’ career decisions are significantly impacted by people in their networks through their provision of support. The emotional, instrumental, informational, and appraisal support received by beginning teachers impacted how they experienced the individual and organisational factors that contribute to teacher turnover. Furthermore, the presence and absence of such support shaped beginning teachers’ professional identity, sense of belonging, individual agency, and their work commitment. Among beginning teachers’ network members, leaders play the most important role in shaping their work commitment as they are equipped with the organisational power to improve working conditions, create a supportive and invitational school culture, and interpret and implement relevant school policies.
teacher turnover, social network analysis, novice teachers, egocentric analysis
University of Southampton
Zeng, Yanan
276880ce-d2b3-4af6-9390-5f90280e38ae
Zeng, Yanan
276880ce-d2b3-4af6-9390-5f90280e38ae
Downey, Chris
bb95b259-2e31-401b-8edf-78e8d76bfb8c
Hyde, Rosalyn
a8c0ae26-bcbf-4ce4-96cc-16fe07447f8e

Zeng, Yanan (2026) How does the social capital of novice teachers impact their career decision to stay in or leave their current teaching position? University of Southampton, Doctoral Thesis, 199pp.

Record type: Thesis (Doctoral)

Abstract

Teacher turnover within the first five years remains a persistent challenge in England. While existing literature has identified a range of individual and organisational factors that contribute to beginning teacher turnover, less attention has been paid to beginning teachers’ social networks, and the role of personal networks in teacher retention remains underexplored. This study addresses the gap by studying how the support beginning teachers receive from their network members shape their career decisions to stay in or leave their teaching position.
This study adopted an interpretivist paradigm and informed by Interpretive Description design. Online interviews were conducted with 23 participants with less than five years of teaching experiences in England, including four teachers who had already left teaching, 11 with a leaving intention, and eight with a staying intention. Qualitative egocentric social network analysis was adopted in this study, with which beginning teachers’ network diagrams were used as both descriptive visual data and interview stimuli, and interview data were used to reflect and interpret their working experience from a network perspective. Reflexive thematic analysis was used to analyse the qualitative interview data. Four subthemes were generated through the analysis of the data — emotional, instrumental, appraisal and informational support — which align with House’s social support theory.
The findings demonstrate that beginning teachers’ career decisions are significantly impacted by people in their networks through their provision of support. The emotional, instrumental, informational, and appraisal support received by beginning teachers impacted how they experienced the individual and organisational factors that contribute to teacher turnover. Furthermore, the presence and absence of such support shaped beginning teachers’ professional identity, sense of belonging, individual agency, and their work commitment. Among beginning teachers’ network members, leaders play the most important role in shaping their work commitment as they are equipped with the organisational power to improve working conditions, create a supportive and invitational school culture, and interpret and implement relevant school policies.

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More information

Published date: April 2026
Keywords: teacher turnover, social network analysis, novice teachers, egocentric analysis

Identifiers

Local EPrints ID: 510544
URI: http://eprints.soton.ac.uk/id/eprint/510544
PURE UUID: 2fea051f-6a0a-464c-b3bd-f8753cf0090c
ORCID for Yanan Zeng: ORCID iD orcid.org/0000-0001-9865-9329
ORCID for Chris Downey: ORCID iD orcid.org/0000-0002-6094-0534
ORCID for Rosalyn Hyde: ORCID iD orcid.org/0000-0001-8208-2983

Catalogue record

Date deposited: 13 Apr 2026 16:43
Last modified: 14 Apr 2026 02:03

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Contributors

Author: Yanan Zeng ORCID iD
Thesis advisor: Chris Downey ORCID iD
Thesis advisor: Rosalyn Hyde ORCID iD

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