A Model for Increasing Reform Implementation and Teacher Efficacy: Teacher Peer Coaching in Grades 3 and 6 Mathematics.
Bibliographic record
Abstract
This study examined the effects of peer coaching on mathematics teaching practices and teacher beliefs about their capacity to have an impact on student learning. Twelve teachers in grades 3 and 6 participated in a brief but intensive professional development program over six months. The program focused on effective math ‐ ematics teaching strategies and peer coaching opportunities. Data sources included classroom observations, teacher self ‐ assessments, interviews, and field notes. Data were analysed using a two ‐ level qualitative coding strategy with multiple inter ‐ preters. Findings showed that teachers implemented key strategies for effective mathematics teaching, especially in facilitating student interaction and improving the quality of tasks assigned. Key words: mathematics, teaching strategies, professional development Cette etude a trait aux effets de l’enseignement mutuel en mathematiques sur les methodes pedagogiques des enseignants et leurs croyances quant a leur capacite d’avoir un impact sur l’apprentissage de leurs eleves. Douze enseignants en 3 e et 6 e annees ont participe a un programme de perfectionnement intensif sur une periode de six mois. Le programme etait axe principalement sur des strategies efficaces pour l’enseignement des mathematiques et les possibilites d’enseignement mutuel. Les sources des donnees etaient multiples : observation de la classe, auto ‐ evaluation de l’enseignant, entrevues et notes prises sur le terrain. Les donnees ont ete analysees a l’aide d’une strategie de codage qualitatif a deux niveaux avec de multiples interpretes. Les resultats indiquent que les enseignants ont mis en œuvre des strategies cles pour enseigner efficacement les mathematiques, notamment en facilitant les interactions entre les eleves et en ameliorant la qualite des tâches assignees. Mots cles : mathematiques, strategies pedagogiques, perfectionnement professionnel.
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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 | 0.012 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".