A Cohort Practicum Model: Physical Education Student Teachers' Experience
Bibliographic record
Abstract
The Faculty of Education at the University of Alberta has recently moved to a cohort practicum policy that encompasses a reflective practitioner model, encouraging whole-school experiences while maintaining positive one-on-one mentorships. The intent of this case study was to investigate the lived world of 10 physical education student teachers who were placed together in groups of five at two secondary school sites for their final eight-week field experience. Specifically, the benefits of the cohort experience were explored through a continual process of triangulation, employing a variety of data-collecting techniques: observing and recording field notes, conversing, journal-writing, and interviewing. Findings revealed overwhelmingly positive responses to the cohort field experience, as expressed by the participating student teachers and cooperating teachers through the emergent themes: Collegial Support, Multiple Ways of Knowing and Doing, Lifelong Learning, Time to Talk, Whole- School Experiences, and Becoming Critically Reflective. At the two school sites a supportive learning environment that valued trust, openness, and mutual respect allowed professional growth to occur. What began as a mentorship of a student teacher with a cooperating teacher evolved into a collaboration of "experts." Having several student teachers in one department was advantageous in many ways, fostering reflective practice, joint thought, and collaborative action. Insights from this study have implications for the preservice education of physical education teachers and other teacher education programs.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.006 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".