Improving On-Task Behaviour in Grade Four and Five Indigenous Students with the use of Movement Integration.
Bibliographic record
Abstract
The purpose of this study was to examine the effects of movement integration on the on-task behavior of Indigenous grade four and five participants at an on-reserve school. Movement integration is the use of physical activity in the classroom during normal classroom time. Movement integration can improve learning behaviors and outcomes for children. This community-based research project utilized participatory action research methodology, which engaged teachers and community leaders in its design. On-task behavior was assessed for thirteen participants through direct observation. A two way [time x period] repeated measures ANOVA revealed a significant interaction [F(1, 12) = 36.067, p< .001]. The movement integration intervention was effective in improving the on-task behavior of the participants. Keywords:Indigenous participatory action research; community-based; on-task behavior; movement integration. RESUME Le but de cette etude est d’examiner les effets de l’integration d’activites de mouvement sur le comportement approprie (“on-task behaviour”) d’eleves autochtones de 4e et 5e annee dans une ecole situee dans une reserve autochtone. L’integration d’activites de mouvement est une utilisation d’activites physiques en classe durant les heures normales de classe. Ce projet de recherche communautaire a utilise une methodologie de recherche-action participative ou les enseignants et les leaders de la communaute se sont impliques dans la planification. Le comportement approprie de 13 eleves a ete evalue par une observation directe. Une ANOVA a deux facteurs (temps X periode) sur des mesures repetees a revele une interaction significative. L’integration d’activites de mouvement s’est averee efficace pour augmenter les comportements appropries des participants.Mots cles: autochtone; recherche-action participative; communaute; comportement approprie;integration d’activites de mouvement.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".