Building teachers’ capacities one teacher at a time within a learning community framework: A retrospective analysis
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 paper is to present how teachers build capacity within a learning community. Two participant researchers, acting as facilitators and co-teachers in an Ontario elementary public school literacy initiative, applied a learning community model for professional development to determine its impact on teachers’ capacity, and on students’ standardized test scores. Data collection included meeting notes from weekly modelling sessions and bi-weekly learning community meetings, field logs, reflection statements from teachers and principal, and documents (such as team-constructed lesson plans and lesson materials). Findings indicated that the use of a learning community to promote collaborative planning, sharing of effective or best practices for teaching, and modelling of literacy components, was valued by teachers. As well, the collaborative learning experience encouraged teachers to take on increasing responsibilities for planning and delivering lessons, promoting a cohesive learning situation for students, as indicated by significantly improved standardized test scores as measured by the Education Quality and Accountability Office Test (EQAO Test), and staff attitudes towards the use of the learning community, as a means of professional development.
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 | 0.010 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.007 |
| Insufficient payload (model declined to judge) | 0.001 | 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