A Study of Teacher Growth, Supervision, and Evaluation in Alberta: Policy and Perception in a Collective Case Study
Bibliographic record
Abstract
Teacher effectiveness has long been identified as critical to student success and, more recently, supporting students attaining the skills and dispositions required to be successful in the early 21st century. To do so requires that teachers engage in professional learning characterized as a shift away from conventional models of evaluation and judgment. Accordingly, school and system leaders must create “policies and environments designed to actively support teacher professional growth” (Bakkenes, Vermunt, & Webbels, 2010). This paper reports on the Alberta Teacher Growth, Supervision, and Evaluation (TGSE) Policy (Government of Alberta, 1998) through the eyes of teachers, school leaders, and superintendents. The study sought to answer the following two questions: (1) To what extent, and in what ways, do teachers, principals, and superintendents perceive that ongoing supervision by the principal provides teachers with the guidance and support they need to be successful? and, (2) To what degree, and in what ways, does the TGSE policy provide a foundation to inform future effective policy and implementation of teacher growth, supervision, and evaluation? Results affirm international findings that although a majority of principals consider themselves as instructional leaders, only about one third actually act accordingly (OECD, 2016).
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".