Improving the emotional intelligence competencies of \nprincipals and vice-principals in an educational \norganization: an exploratory study
Bibliographic record
Abstract
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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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".