DEALING WITH MESSINESS AND UNCERTAINTY IN PRACTITIONER RESEARCH: THE NATURE OF PARTICIPATORY ACTION RESEARCH
Bibliographic record
Abstract
This article reports on the experiences and perceptions of K ‐ 12 teachers as they engaged in a participatory action research (PAR) project, Science Across the Curriculum . Although the experiences and professional learning of two of the project participants are highlighted, the challenges that all participants experienced as they conceptual ‐ ized and implemented action research are also reported. The author concludes that messiness and uncertainty are inherent and necessary elements of action research and that these elements need to be explicit for the benefit of those who engage in and facilitate PAR. Key words: science education, teacher development, teacher inquiry Cet article presente les experiences et les perceptions d’enseignants de la maternelle au secondaire qui ont pris part a une recherche ‐ action participative (RAP), Science Across the Curriculum . Ce sont surtout les experiences et l’apprentissage professionnel de deux des participants qui sont mis en lumiere, mais l’article fait egalement etat des defis auxquels ont fait face tous les participants dans la conceptualisation et la mise en œuvre de la recherche ‐ action. L’auteure conclut que la desorganisation et l’incertitude sont des elements intrinseques de la recherche ‐ action et que ces elements doivent etre explicites pour le plus grand bien des personnes qui participent et animent une RAP. Mots cles: recherche ‐ action participative, perfectionnement des enseignants, recherche sur les enseignants
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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 | 0.452 | 0.359 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.009 | 0.006 |
| Science and technology studies | 0.018 | 0.168 |
| Scholarly communication | 0.039 | 0.041 |
| Open science | 0.007 | 0.034 |
| Research integrity | 0.012 | 0.015 |
| 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".