The Correlation between English Emotional Intelligence and Work Engagement of Secondary School Teachers in China
Bibliographic record
Abstract
Emotional intelligence is distinguished as a key factor that influences work engagement. However, there is limited research exploring the relationship between emotional intelligence and work engagement among secondary school English teachers in China's ethnic regions. Therefore, this study utilizes self-determination theory to support how emotional intelligence affects work engagement in such educational contexts. This study used purposive sampling to survey 301 secondary school English teachers from different ethnic regions in China. SPSS 27.0 was used for correlation analysis. The results of the study showed that (1) English teachers have higher levels of emotional intelligence and work engagement, reflecting the overall high psychological quality of the participants. (2) There is a positive correlation between the variables, showing their positive relationship. Ultimately, this study provides pedagogical insights for educational policy makers and practitioners to guide the improvement of teacher training and support systems so that they can work together to promote educational quality and equity in ethnically diverse regions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".