The relationship between teacher factors and social and emotional learning program implementation
Bibliographic record
Abstract
The children and youth of today will need social-emotional competence to help them navigate the challenges of an uncertain future. School-based social and emotional learning (SEL) programs have been shown to be effective in helping youth develop these vital, malleable skills, and that the positive outcomes endure. However, achieving these positive outcomes requires quality implementation by classroom teachers. There are many factors that contribute to teachers’ motivation, readiness, and ability to deliver an SEL program as intended. Using data collected in four experimental evaluations of SEL programs, two studies were conducted to explore the relationship between program implementation quality and teacher factors such as teaching efficacy, stress, job satisfaction, and beliefs about SEL. Study 1 explored relations of teachers’ (N = 32) pre-implementation factors including SEL experience, job satisfaction, and SEL beliefs, to program implementation quality. Correlational and multiple regression analyses revealed no significant relationships between teacher factors and implementation quality. However, the total number of lessons in the SEL programs surfaced as a significant predictor of implementation quality, where fewer lessons predicted greater implementation quality. Study 2 explored how changes in teacher factors including SEL beliefs, occupational stress, efficacy, and job satisfaction were related to teachers' program implementation quality. Teachers (N = 23) were grouped into low- and high-quality implementation categories based on their total implementation quality scores. Paired-samples t tests showed that teachers’ depersonalization, a symptom of occupational stress, and teaching efficacy scores significantly changed after implementing an SEL program; however, these changes were not in the hypothesized direction. Specifically, teaching efficacy scores decreased and depersonalization scores increased. Taken together, these findings indicate the need for further research to examine the relationship between teacher factors and SEL program implementation. Study contributions, limitations, and directions for future research are discussed, as well as practical implications for supporting teachers’ implementation.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".