Exploring the relationship of emotions in physical education to physical literacy and self-esteem
Bibliographic record
Abstract
UNESCO and the WHO have identified quality physical education (QPE) as a key contributor to achieving an active society through fostering physical literacy in children. Physical literacy has been proposed as a multidimensional construct consisting of psychological, social, and physical attributes which lead to being active for life. Physical literacy research has been focused primarily on motor competency, with limited research on affective or cognitive factors. To address this gap, a cross-sectional study was conducted with 4th and 5th-grade students (n=145) immediately after PE class (5 schools, 14 classes) using the Discrete Emotions in Physical Education Scale, Physical literacy self-description (PLAYself), and self-esteem from the Physical Self-Description Scale (PSDQ-S). Each emotional variable (pride, enjoyment, shame, anger, boredom, and overall emotional valence) showed moderate correlations with physical literacy and self-esteem (rho= -0.47 to 0.65, p<0.001), with positive and negative emotions showing positive and negative correlations respectively. The most prevalent emotions were pride and enjoyment (91% and 92%), which co-occurred in 86% of students. Among students who reported both positive and negative emotions, 97% had positive overall emotional valence, indicating that experiencing negative emotions did not preclude a positive experience. Students who experienced both positive and negative emotions demonstrated lower levels of physical literacy and self-esteem than students who experienced only positive emotions (p<0.001, effect size=0.4 to 0.45), and students who reported only negative emotions (3% of the sample) had the lowest scores in both physical literacy and self-esteem. In a natural experiment, this study also compared circus arts instruction in PE (CAI-PE, 4 schools, n=101) to standard PE (S-PE, 2 schools, n=44). Students in CAI-PE were more likely to report pride and enjoyment (Odd ratio=3.0 and 5.0, p<=.05). These findings support existing evidence that the inclusion of circus arts in PE enhances students’ positive emotional experiences, even when compared to specialist teachers delivering QPE. Overall, this study demonstrates that positive emotions in PE may act as a counterbalance to negative emotions and that both positive and negative emotions are linked to the physical literacy cycle and the development of self-esteem.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".