Assessment and training of physical literacy in early childhood educators
Bibliographic record
Abstract
Educators working in early childhood education and care receive little to no training in physical activity or physical literacy. However, they are expected to adhere to government standards for physical activity and skill development during the childcare day. This dissertation sought to determine what characterizes a successful intervention aiming to train educators in physical activity and/or physical literacy, what barriers and facilitators educators identify in meeting daily activity standards, what the physical literacy of educators is, and if educator physical literacy is associated with their behaviours and intentions to provide physical activity or physical literacy activities regularly. A systematic review was undertaken to parse apart the distinct characteristics of effective training interventions in physical activity or physical literacy. Training programs that provided ongoing support, relied on a theoretical framework, and objectively measured study fidelity were more successful. Educators were interviewed (n=24) to assess facilitators and barriers they face when implementing policy mandated activity standards. Results demonstrated that the personal values of educators facilitated adherence, and if physical space was poor, or resources were low, adherence was inhibited. Finally, a cross-sectional study measured the physical literacy of educators (n=94), and utilized regression analysis to determine relationships between measured physical literacy and self-reported behaviours and intentions to provide physical activity and/or physical literacy opportunities daily. Physical activity behaviour and understanding were high, but the remaining components of physical literacy were moderate. A relationship was found between educator self-reported intentions and behaviours for providing physical activity opportunities and the physical literacy component of understanding, but no relationship was found for the other components of physical literacy. The results of these three studies demonstrate that educators are trainable in physical activity and physical literacy, but high-quality training programs that provide continued support and/or training for educators are needed. Training programs may not need to focus on the personal physical literacy of educators. Mandating training for educators to provide quality physical literacy opportunities to children should be a high public health priority.
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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 | 0.007 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".