Action research as a developmental tool for health and physical education teachers
Bibliographic record
Abstract
At present there is a global need to assume an inquiry stance to address problems to locate solutions, as complex problems surface in all walks of life. With new Health and Physical Education provincial curricula emerging in 2019, the province of Ontario (Canada) is also making inquiry a priority. Educators in Ontario are expected to lead students in inquiry efforts yet in order to do this requires teacher training that is authentic, appropriate and professional. One inquiry mode used to enhance and improve is Action Research with its inquiry-based learning elements complements the role of educators and students alike. Action Research is an inquiry tool that can help participants achieve certain resolutions within our educational landscape. Action Research can infuse and nurture teacher self-development within teacher training while improving interpersonal relationships and developing pedagogy via practical experiences. Teacher change through action research occurs within the interactions, experiences and professional development that seems to enlighten teacher training.
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.
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 | 0.141 | 0.115 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.007 | 0.021 |
| Scholarly communication | 0.019 | 0.016 |
| Open science | 0.006 | 0.017 |
| Research integrity | 0.006 | 0.012 |
| Insufficient payload (model declined to judge) | 0.013 | 0.005 |
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".