Instructional Rounds as a professional learning model for systemic implementation of Assessment for Learning
Bibliographic record
Abstract
The purpose of this research was to examine the implementation of a professional learning project aimed at building educators’ knowledge and skills in assessment for learning (AfL) within two school districts in Ontario, Canada. Specifically, the research examined the value of a two-tier Instructional Rounds (IR) professional learning model. This professional learning model was unique because it engaged both teachers and principals in collaboratively learning and implementing AfL strategies in order to develop systemic capacity in assessment. In total, 12 principals, 48 teachers, two superintendents and two school district assessment consultants participated in the study. Data were collected through observations of IR sessions, classroom observations, interviews, IR session reflections and a post-project survey. Findings from this study report on positive changes in teachers’ and principals’ conceptions and implementation of AfL as well as on the value and challenges of IR as a professional learning model. The paper concludes with a discussion on developing systemic capacity in AfL through an IR model of professional learning.
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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 | 0.024 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.004 |
| 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".