Using Action Research and Provincial Test Results to Improve Student Learning, 6(20)
Bibliographic record
Abstract
During the 1999/2000 school year, seventeen elementary school teachers and five consultants, from two Ontario school boards, conducted action research based on the 1999 EQAO provincial test results for Grades 3 and 6 and used feedback/corrective action to improve those results. Paired with a “critical friend,” individual teachers analyzed their schools’ results and identified areas for improvement. They developed action research questions, investigated the questions in their own classrooms, collected data to evaluate the impact of their work, and recorded their investigations. The teachers’ own assessments and the 2000 EQAO test results indicated substantial success. Teachers began to see provincial test results as friendly data that schools can use to improve student learning and action research and feedback/corrective action as powerful methods to do so. The study contributes to understanding how provincial testing can be used to improve student learning and what constitutes effective teacher in-service education. It shows how professional teachers can play a leading role in school improvement by taking charge of their own professional learning.
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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 | 0.018 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".