Optimum Learning for All Students Implementing Alberta’s 2018 Professional Practice Standards A Longitudinal, Mixed Methods Research Study: 2019-2020 Provincial Year 1 Survey Research Report
Bibliographic record
Abstract
Alberta Education commissioned this 4-year longitudinal, mixed methods research study, which is designed to assess, deepen, and extend the implementation process for Alberta’s three professional practice standards: The Teaching Quality Standard (TQS) the Leadership Quality Standard (LQS), and the Superintendent Leadership Quality Standard (SLQS). This report presents the survey findings from the first year of the study. Findings are presented for each of the three standards. Results overall indicate: 1. educators across the province are in the adapting stage of implementation--– where teachers, school leaders, and superintendents are still adapting in their practice to novel problems– they reported much flexibility. The public health situation in 2020 and 2021 have required such flexibility and continuing adaptivityThe standards and their implementation do not appear to be rigidifying practice since interquartile ranges and standard deviations remain professionally healthy for fostering discussion and multiple perspectives. 2. leaders must engage the wider community in schools. Those competencies in leading those within the system are stronger than for leading those beyond the system. While small gains have been made in year 2 of the study, leaders must continue to engage with the public to continue constructing public confidence. 3. forms and formats of professional learning and leadership development have shifted markedly over the past year, and will continue to shift after the pandemic. More technological delivery of customized courses, more collegial approaches in virtual learning space, and greater demand for both credentialed and non-credentialed learning will be necessary. What that means for changing educator behaviour and enacting standards to support “optimal” learning remains unclear.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".