Pre-service and Practicing Teachers’ Commitment to and Comfort with Social Emotional Learning
Bibliographic record
Abstract
Although teachers’ beliefs about social-emotional learning have become a topic of interest, understanding how they relate to teachers’ own social-emotional competence is unknown. We used a predictive correlation design to examine how Canadian pre-service (n=138) and in-service (n=276) teachers’ beliefs about social-emotional competence relate to their comfort with and commitment to social-emotional learning, and how both sets of beliefs are related to their perceived efficacy for classroom management and engagement with students. Regression analyses revealed that comfort with social-emotional learning significantly predicted both outcomes for both groups whereas commitment to social-emotional learning did not. Perceived social-emotional competence also played an important role. Pre-service teachers felt more committed to social-emotional learning, whereas in-service teachers felt more comfortable and believed they had higher levels of social-emotional competence themselves. Implications for supporting the development of teachers’ own social-emotional competence and suggestions for future research are provided. Si les croyances des enseignants relatives à l’apprentissage socio-affectif suscitent beaucoup d’intérêt, on ignore le lien entre celles-ci et la compétence socio-affective des enseignants eux-mêmes. Nous appuyant sur une conception de corrélations prédictives, nous avons examiné le lien entre les croyances des stagiaires (n=138) et des enseignants en exercice (n=276) relatives à la compétence socio-affective d’une part, et l’aise et l’engagement dont ils font preuve face à l’apprentissage socio-affectif, d’autre part. De plus, nous nous sommes penchés sur la mesure dans laquelle les croyances des participants sont liées à leur perception de l’efficacité de leur gestion de classe et de leur engagement avec les élèves. Des analyses de régression ont révélé qu’un sentiment d’aisance avec l’apprentissage socio-affectif prédit de manière significative les deux résultats pour les deux groupes alors que ce n’était pas le cas pour un engagement face à l’apprentissage socio-affectif. La perception de la compétence socio-affective a également joué un rôle important. Les stagiaires avaient un sentiment d’engagement plus fort envers l’apprentissage socio-affectif, tandis que les enseignants en exercice se sentaient plus à l’aise et croyaient que leur niveau de compétence socio-affective était plus élevé. Nous présentons quelques implications d’appuyer le développement de la compétence socio-affective des enseignants et des suggestions pour la recherche à l’avenir.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".