Bibliographic record
Abstract
This study investigated principal leadership for Collaborative Inquiry (CI) as a strategy for teachers’ ongoing professional learning and school improvement. A qualitative methodology was employed to generate insight into how the Ontario elementary school principals have led and supported this strategy in their school contexts. The findings show that principals’ roles in the CI process include (1) fostering the CI culture; (2) providing teachers with time and resources; (3) acting as an active co-learner, co-facilitator, and coach; (4) supporting models of shared decision-making and distributed leadership; (5) adapting CI to the school context; (6) setting the direction for the CI inquiry teams; and (7) sustaining CI. The capacity principals need to lead and support CI includes knowledge of CI and data, facilitation skills, and a growth mindset and perseverance for CI, which can be acquired in various ways including: reading CI resources, engaging in the CI process, attending professional learning sessions, accessing Ministry resources, participating in professional networks of colleagues, and listening to teachers who are involved in the CI process. The challenges and barriers principals encounter include (1) lack of time and resources for the teachers to conduct CI, (2) facilitation skills to develop a culture of inquiry and learning, (3) getting teachers to buy into the CI culture, (4) embedding a true learning CI culture at school, and (5) the stance of teacher unions which is claimed to be one source of teachers’ resistance to engagement in the CI process. To overcome these barriers and challenges, principals use some common strategies such as (1) finding time creatively for the teachers to conduct CI, (2) keeping things as focused and practically manageable as possible, (3) setting norms for building trust and ensuring a variety of opinions, (4) not using the term CI but associating CI with the existing norms and practices of collaboration and learning at school. Overall, the findings of this study corroborate and extend upon findings in the literature indicating how principals lead and support CI endeavors in schools.
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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 | 0.031 | 0.049 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.006 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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; 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".