From leadership research to district action: A Network Analysis of Emotional Intelligence in Chinese Preschool Teachers

AI-assisted editorial implementation guide. Proposed district actions are separate from the original authors’ findings and recommendations. Independent peer review of this guide is not asserted.

Read source Search paper agent CC BY 4.0

Evidence and transfer

Education-related source: verify which participants, institutions and outcomes were actually studied before district adoption. Source publication type: research-article. License and identity checks do not establish study quality or causality.

Original authors’ abstract, reproduced under the source license:

Emotional intelligence significantly influences various aspects of teachers’ professional and personal lives, notably affecting preschoolers’ social skills and emotional development during formative years. This study utilizes a network analysis approach to explore the complex relationships among four components of emotional intelligence: emotional labor, emotional regulation, professional well-being, and professional identity. Participants included 2069 frontline Chinese teachers (34 males, 2035 females; M = 28.64, SD = 5.98; M years of teaching = 6.88, SD = 5.29) with no leadership roles, categorized into three stages of their careers based on years of teaching experience: novice (0–3 years; n = 612), advanced beginners (4–6 years; n = 537), and competent (7–40 years; n = 920). Findings revealed that joy of teaching, role value, and professional value were identified as the most critical elements within the emotional state network of early childhood education teachers. The strongest connections in teachers’ emotional networks were found between school connectedness and joy of teaching (r = 0.474), surface acting behavior and natural acting behavior (r = 0.419), and professional value and professional behavior (r = 0.372). Furthermore, teachers across different career stages exhibited similar characteristics and intrinsic connections among emotional state components. These findings deepen our understanding of the emotional state networks of ECE teachers, highlighting shared features and interconnected mechanisms, and suggest that enhancing teachers’ emotional intelligence through targeted professional development can improve both teacher well-being and preschoolers’ social–emotional outcomes. Policies that foster strong school connectedness and reduce emotional labor are key to promoting sustained joy in teaching, particularly for novice and advanced beginner teachers.

Study methods

Participants in this study were recruited from 123 kindergartens located in Shenzhen, China (see Table 1). Among these, 83 were classified as public schools, as they received government subsidies. A total of 2345 responses were collected through paper questionnaires. However, 276 responses were either incomplete or duplicated, resulting in 2069 valid samples for analysis (34 males, 2035 females; mean age = 28.64, SD = 5.98; mean working year = 6.88, SD = 5.29). The proportion of male teachers in the study is representative of that in the country, being less than 1%. All participants were front-line teachers without holding leadership positions, distributed across teaching levels K1 (n = 691), K2 (n = 674), K3 (n = 694) and 10 teachers teaching mixed-age classes. Following Booth et al.’s [101] model, participants were categorized into five career stages: novice (0–3 years; n = 612), advanced beginners (4–6 years; n = 537), competent (7–18 years; n = 839), proficient (19–30 years; n = 77), and expert (31–40 years; n = 4). Due to small sample sizes in the proficient and expert stages, they were merged into the competent stage to ensure sufficient statistical power. Consequently, participants were classified into three career stages for this study.

Limitations

Before delving into our findings, itis crucial to acknowledge several limitations of our study. Firstly, it was cross-sectional, limiting our ability to discern the direction of associations among teachers’ mood state subgroups or how these dimensions interact over time [162]. Prospective and longitudinal studies are necessary to uncover differential associations between subgroups. Secondly, our data were sourced from 120 schools, potentially introducing nesting effects, though our analyses didn’t account for this multilevel structure due to technological constraints. While contemporary network analysis techniques can handle time-series data, the absence of repeated observations in our dataset limits the suitability of the current approach. Future research could refine network analysis methods to better accommodate nested data structures. Thirdly, the network structure’s shape hinges on specific node variables [92], and the exclusion of crucial nodes, like teachers’ emotional knowledge and beliefs in our study, may compromise inferences about centrality. Subsequent studies should incorporate more comprehensive indicators of teachers’ emotional development to provide a deeper understanding of key features within teachers’ emotional states. Lastly, network analyses may be influenced by demographic and cultural disparities. The underrepresented male teachers in the sample might show different network patterns in comparison to the female teachers, which should be explored in the future research from the perspective of male educators in preschool settings. Furthermore, endeavors to gather data from diverse cultural contexts should entail a thorough assessment of teachers’ emotional states.

A 90-day district inquiry

Days 1–15 · Appraise. Read the source methods, recruitment, comparator, outcomes and limitations. Record how the study setting differs from your district and which claim the design can support.
Days 16–30 · Design. Choose one school improvement question with teachers. Protect a short shared planning cycle, agree an instructional change and use a common rubric for examining student work. Agree participation, privacy protections, baseline and stopping rules before starting.
Days 31–60 · Observe. Collect the pre-agreed measures, keep a log of implementation changes and invite confidential voluntary feedback. Preserve existing support for staff and learners.
Days 61–90 · Decide. Review implementation fidelity, teacher time and independently scored student work against a recorded baseline. Examine access differences and competing explanations before attributing changes to leadership. Make a dated decision to stop, revise or extend the inquiry.

Board decision brief

Present the local problem, source setting, evidence limits, intervention, responsible owner, total cost, measured changes and uncertainty. Separate staff perceptions, implementation measures and student learning outcomes.

Attribution and reuse

Sha Xie; Beiyi Su; Siman Yang; Jing Li; Hui Li. A Network Analysis of Emotional Intelligence in Chinese Preschool Teachers. Behavioral Sciences (2024-11-25). https://doi.org/10.3390/bs14121132

Prepared 2026-11-07. Source authorship and DOI are preserved. The abstract and source passages are attributed extracts; this editorial guide is offered under the same CC BY 4.0 license.