Evidencia de la relación directa e indirecta del modelo conceptual de desarrollo motor en población infantil
Bibliographic record
Abstract
Studies examining the relationship between actual and perceived motor competence (MC), physical fitness (PF) and the practice of physical activity (PA) are limited. The objective of the present study is to examine the direct and indirect reciprocal relationship between these four factors of the conceptual model of motor development. Volunteer participants included fifth- and sixth-grade primary school students (n = 679; 50.8% girls). Actual and perceived MC was measured by using the Canadian Agility and Movement Skill Assessment (CAMSA) and Perceived Movement Skill Competence (PMSC), respectively; PF was measured through the Progressive Aerobic Cardiovascular Endurance Run (PACER) test, and PA was measured through the Physical Activity Questionnaire for Children (PAQ-C). Correlation, multiple regression and mediation analyses were carried out. The results showed a reciprocal relationship between the variables being studied (r = .237 – .477; p < .01), explaining between 28-30% of variance between actual MC and PA. PF and perceived MC mediated the relationship between actual MC and PA and vice-versa. Physical education teaching programming should focus on and enhance learning and motor experience of students not just at a physical level, but paying attention to psychological aspects such as competence perception.
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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 | 0.010 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".