Supporting Teachers in Implementing Movement Integration: Addressing Barriers Through a Job-Embedded Professional Development Intervention
Bibliographic record
Abstract
Purpose: Movement integration (MI) is a method to increase physical activity with numerous learning outcomes. However, MI implementation is low. The purpose of this study was to investigate the effects of a job-embedded professional development intervention on teachers’ MI barriers. An implementation science approach was used. Methods: The intervention was developed and delivered through six procedures. Mixed-methods data were used to develop the intervention and assess outcomes. The intervention was delivered over 3 weeks to 12 participants. Results: Reported barriers included time constraints, lack of space, fear of losing control, and limited confidence and competence. Results indicated a significant increase in teachers’ self-reported MI use from pre- to postimplementation (Z = −2.138, p = .0165, r = .6), improved confidence (p = .048), and a strong positive correlation (τb = .627, p = .018) between confidence and competence. Conclusion: Job-embedded professional development may be an effective strategy to support teachers in overcoming barriers to MI.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".