Characterizing Middle School Students' Physical Literacy Development: A Self-Determination Theory-Based Pilot Intervention in Physical Education
Bibliographic record
Abstract
Purpose: Positive youth development (PYD) can be achieved through effective and purposeful instructions in physical education (PE) and other relevant experiences both in and beyond schools. Students' PYD is associated with their physical literacy (PL) development, which has become a primary emphasis of PE, especially in the United States, in recent years. This study aimed to (a) characterize middle school students' physical literacy (PL) and (b) capture their PL developing trajectories in light of receiving a self-determination theory (SDT)-based pedagogical workshop, with the long-term vision on PYD. Methods: Participants (N = 226) completed the Canadian Assessment of Physical Literacy (CAPL-2) in physical education (PE). A subsample (n = 49) received four workshop sessions over 8 weeks; and completed the CAPL-2 and participated in focus group interviews before and after the workshop. Results: Both boys and girls' CAPL-2 scores were in the “progressing” stage. Significant differences in PL and PL domains were observed by gender, grade, socioeconomic status (SES), body mass index (BMI), and race/ethnicity. The low PL group showed improvements in PL and PL domains. Interview data delineated positive PL developing trajectories for physical activity (PA) type, frequency, and intensity; perceived motives; and participation barriers. Conclusion: PL is a dynamic state that can be improved through purposeful PE. Future work should examine the effect (and implementation) of opportunities in (e.g., PE) and beyond schools (e.g., youth sports programs) to ultimately advance PYD.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".