Instructional Rounds as a professional learning model for systemic implementation of Assessment for Learning
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it