Exploring Science Teachers’ and Science Teacher Administrators’ Experiences of Instructional Leadership
Bibliographic record
Abstract
Purpose: Examine how high school science teachers and principals experience instructional leadership; specifically, science educators’ understanding and lived experiences of the phenomenon of instructional leadership. Research Method: This study used a qualitative phenomenographic approach to gather the experiences of science teachers and principals in high schools located in Alberta, Canada. This approach explains and supports interviews as the data source and the number of participants (N = 9) of the study. Findings and Analysis: Data revealed three closely related categories from participants’ experiences: definitions of instructional leadership, thematic elements identified from data, and their reflections on the value of science teaching knowledge for instructional leadership. Findings identified the interdependence of the factors affecting instructional leadership, how instructional leadership is organized, and the factors’ relevance for developing science teaching knowledge. Pedagogical content knowledge (PCK) and pedagogical context knowledge (PXK) to support science teaching knowledge were found to be significant. Science teachers and principals accepted the importance of instructional leadership, but principals did not view it as their primary responsibility; they reported being preoccupied with other duties. Participants’ experiences portrayed some common themes to support science teaching knowledge and instructional leadership: collaboration, spontaneous interactions and feedback, peer instructional leadership, shared conversations about professional development needs, teachers’ input in making decisions about the needed development, science principals’ classroom knowledge, PCK and PXK to guide science teaching, trusting relationships, microworlds of science educators, professional socialization, and reflection-in-action of their practice. Conclusions: Instructional leaders’ iii content knowledge, PCK, and PXK are central components of science teaching knowledge for instructional leadership.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.009 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| 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".