LEAD TEACHERS IN COLLABORATIVE ACTION RESEARCH: PERCEPTIONS OF ROLE AND RESPONSIBILITY
Bibliographic record
Abstract
In 2008-09, the Elementary Teachers’ Federation of Ontario (ETFO) sponsored a professional learning initiative entitled, Teachers Learning Together: The Math Journey. The context for teachers was one of team-based, collaborative action research (CAR) dealing with a mathematics topic of their own choosing. University researcher teams in provincial regions were also enlisted to facilitate the CAR activities and to conduct case study research and reporting. Each teacher team designated a Lead Teacher (LT) for the duration of the project. This paper highlights the case study research findings pertaining to perceptions of role and responsibility of the LTs, and focuses on four emergent roles, namely that of manager, motivator, model, and mediator. Lead Teachers are shown to be essential to the collaborative action research process. Notwithstanding, recommendations regarding the actual LT designation, and a clearer communication of LT role and responsibility are also made.
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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 | 0.051 | 0.074 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.018 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| 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 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".