Improving the emotional intelligence competencies of \nprincipals and vice-principals in an educational \norganization: an exploratory study
Notice bibliographique
Résumé
Research has recognized that the principal is second only to the teacher in regards to impact on student learning (Leithwood, Day, Sammons, Harris, & Hopkins, 2006) and the importance of emotional intelligence competencies of school leaders has been highlighted by Fullan (2014). As \nschool districts strive to improve student learning and achievement, the emotional intelligence competencies of the principal/vice-principals can play a critical role in leveraging this influence. \n \n \nWhile studies have shown that emotional intelligence competencies can be improved upon over time \n(Groves, McEnrue, & Shen, 2008), research has not focused on whether all individuals benefit from specific training or what other factors may be influencing any improvement. This research study examined both of these aspects by investigating whether the emotional intelligence competencies of principals and vice-principals improved through participation in a focused professional development \ntraining program and what factors influenced any change. Participants in the study held positions of educational leadership within specific publically funded school districts in Ontario, Canada. \n \nIn this study, a mixed method research approach was utilized with a two phase sequential design. Phase #1 involved quantitative data collection using the EQ-360 measurement tool (Bar-On, 2006). Participants completed a pre-test prior to engaging in the professional development training program and post-test following the training. Demographic information permitted participants to be \nsorted into sub-groups and statistical comparisons to be drawn between these groups. \n \n \nPhase #2 involved qualitative in-depth interviews with a probability sample group of participants who had been surveyed in Phase #1. Five key factors that also impacted emotional intelligence capacity emerged from the analysis of the Phase #2 interview data: Journey of Learning; Way of \nBeing; Past Experience; Personal Supports and Professional Networks; and Way of Working. \n \nThe findings presented in this study reaffirm that emotional intelligence competencies can be improved through professional development training. As well, variables that impact the ability of principals and vice-principals to improve their emotional intelligence competencies were identified and described. It was then illustrated how these variables interact with one another to support the \nindividual’s journey of learning. These variables included Journey of Learning, Way of Being, Past Experience, Personal Supports and Professional Networks, and Way of Working. Whilst these variables were not in the design of the professional development training, they did contribute to the improvement of the participants’ emotional intelligence development. The identification and \nexploration of the interrelationship of these variables provide new knowledge, not previously identified in the literature. \n \nFurther, the study presents a framework for developing emotional intelligence competencies. This framework focuses on fostering commitment, adopting a professional learning \nmodel, developing readiness, targeting audience and promoting supports. It is from an exploration \nof this framework that a number of recommendations were made which will assist school districts in becoming more aware of the effectiveness of professional development training programs and better able to support the \ndevelopment of the emotional intelligence competencies of its principals and vice-principals. \n \n \nWhilst this study focused on the experiences in a professional development training program of a \ngroup of principals and vice-principals in five Ontario school districts, the general findings \nshould have significance to other school districts that provide similar large scale professional \ndevelopment training. Consideration and implementation of the recommendation from the findings \nfrom this study have the potential to enhance the effectiveness of similar professional development \ntraining in their education district, \nregion or system. \n
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».