Integrating Research-Supported Coaching Practices Into Secondary Teachers’ Team Meetings: Early Indications of Potential to Impact Collaborations, Classroom Interactions, and Student Engagement
Bibliographic record
Abstract
The My Teaching Partner-Secondary (MTPS) program demonstrated improvements in classroom interactions and student outcomes in secondary schools using one-on-one coaching between study staff and teachers. Despite promising results, the time, cost, and oversight from a university research team may pose barriers to adoption of coaching programs like MTPS at scale. The My Teaching Team (MTT) project sought to translate key ingredients from MTPS into existing professional development contexts that are already built into many middle and high school educators’ weekly schedules: co-planning or professional learning community meetings. Six teams of secondary teachers (N = 30 teachers) participated in a pilot test of the usability of MTT materials across 5 months in one school year. Three teams elected to use MTT materials, and three elected to be a comparison group who continued their typical practices. Teams adopting MTT materials were observed to do so with good implementation integrity, and reported satisfaction with the intervention. Compared to typical practice teams, those using MTT were observed to spend more meeting time discussing teaching practice and less time discussing logistics/mechanics, and engaged in more video sharing and feedback to team members in the MTT sessions that explicitly encouraged this. The number of MTT meetings completed by a team, as well as spending more time discussing teaching practices and video sharing (but not feedback provided) during team meetings, predicted students’ self-reports of greater engagement and observations of higher levels of emotional support provided in the classroom. Implications for translating empirically supported interventions from the lab to real-world school settings are discussed.
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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 | 0.018 | 0.047 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".