Bibliographic record
Abstract
IntroductionIn Ontario, over the past few years, and despite some improvement in PISA test scores (CECM, 2012) and provincial testing (OQRE, 2014), studies have shown that Francophone students are still falling behind their Anglophone peers in several subjects, such as mathematics.Since 2005, the Ontario Ministry of Education has been asking their principals to implement a new organizational structure: a professional learning community (PLC). This practice, if well developed, generates many benefits. For teachers, it provides a way of working which contributes to professional satisfaction and development, and reduces non-attendance (Linder, Post and Calabrese, 2012). For students, we observed higher academic success and reduced absenteeism (Hord and Sommers, 2008). Several studies show that principals do not know how to implement PLCs because they have not received the required training (Cranston, 2007). Moreover, Marshall (2010) argues that some principals do not have the necessary competencies to implement PLCs. BackgroundEducators recognize the importance of shifting learning from the individual process prevalent in traditional schools, to a collaborative process that is aligned with the aim to improve student learning (DuFour, DuFour and Eaker, 2008). However, a few research studies have been conducted in primary and secondary Francophone schools in Ontario Leclerc and Moreau (2011) identified some conditions that principals must apply to successfully implement PLCs: vision/mission, collaborative culture, scheduled meetings and analysis of student data.Since studies have proven that a professional learning community contributes to professional development for teachers and academic success for students, the Ministry of Education strongly encourages principals to implement one in their school. To apply this new organizational structure, principals need the required competencies and knowledge regarding the conditions favoring the implementation of a PLC. Whereas some schools are considered advanced in their application of this model, others do not know how to implement the necessary changes (IsaBelle, Génier, Davidson and Lamothe, 2013).Methodology The aim of our study is to investigate how schools with advanced PLCs have been able to apply this novel structure. We performed qualitative research in eight elementary and secondary schools in Ontario. We interviewed and filmed eight principals, twenty teachers and three education leaders. ResultsIn addition to the common conditions previously identified as necessary for the implementation of a PLC, other key elements were discovered: responsibility for student success, commitment from the district school board, etc. Besides these results, online resources (videos) from eCAP will also be presented at the conference.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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; both teacher heads agree on what is shown here.
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".