Enhancing Language Teachers' Well‐Being Through Positive Psychology Interventions: A Mixed‐Methods Study Focusing on Gratitude Journaling
Bibliographic record
Abstract
ABSTRACT Despite increasing attention to teacher well‐being over the past years, few studies have explored the outcomes resulting from implementing low‐cost, teacher‐directed interventions grounded in a positive psychology perspective. In addressing this gap, this study investigated the effects of an 8‐week gratitude journaling intervention on the well‐being of language teachers in Iran, using a convergent mixed‐methods approach. A total of 40 EFL teachers were selected using purposive and convenience sampling techniques and participated in a randomized controlled trial. Data were collected through validated scales measuring gratitude and subjective well‐being. Quantitative results analyzed using mixed ANOVA demonstrated significant improvements in all well‐being dimensions post‐intervention, with the largest effect observed in social well‐being (partial η 2 = 0.252, p < 0.001). These findings suggest that gratitude journaling effectively enhances both individual and social facets of well‐being among teachers. Furthermore, multivariate tests indicated significant interactions between time (pre‐ and post‐intervention) and group (experimental vs. control), particularly highlighting the role of the intervention in these improvements. The qualitative strand, analyzed through thematic analysis, revealed three primary themes: (1) enhanced emotional resilience, (2) strengthened social well‐being, and (3) promoted personal and professional growth, which provided deeper insights into the teachers' experiences and the subjective benefits of the intervention. The study reveals the potential of gratitude interventions in improving well‐being and fostering a positive educational environment. The findings have implications for enhancing teacher well‐being and also to the practical application of positive psychology in educational settings.
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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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".