Elementary teachers’ planning for mathematical reasoning through peer learning teams
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
Many elementary teachers find the complexity of understanding and teaching mathematical reasoning challenging. Teachers can benefit from professional learning programs designed to develop strategies to identify reasoning and implement it in mathematics lessons. This paper reports on a professional learning program designed to support a Peer Learning Team (PLT) of elementary teachers in Canada who were assisted by a researcher to peer-plan, peer-observe, and reflect on lessons fostering reasoning. Recorded data from PLT meetings were analysed against a planning framework to study the teachers’ growth in understanding reasoning. The findings revealed teachers engaged in a PLT which plans together to embed reasoning in a lesson, followed by peer-observation and reflection is a powerful and effective model of professional learning for understanding mathematical reasoning and pedagogical approaches that foster students’ reasoning.
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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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