Preliminary validity and estimated reliability of the Canadian Assessment of Physical Literacy (CAPL-2) in the Indonesian Physical Education System
Bibliographic record
Abstract
Background and purpose Physical literacy assessment an innovative and current option has been suggested for classifying and evaluating health in children and adolescents holistically. This study aims to adapt CAPL-2 to assess the improvement in the physical literacy of children between the ages of 8 to 12 years and prove the construct validity, content validity, and determine the estimated reliability of the CAPL-2 according to the characteristics of Indonesian elementary school children. Material and methods Preliminary validity and reliability estimates of the CAPL-2 (Indonesia) were studied using cross-sectional methods resulting from public elementary school students in Central Lombok, NTB, Indonesia. A total of 7 experts/academics (expert judgment) to prove the content validity of CAPL-2, and as many as 84 children (43 boys and 41 girls; mean age = 10.05; standard deviation = 0.74) to prove construct validity and estimated reliability of CAPL-2. The measurements in this study were designed to provide descriptive results on 3 core domains of physical literacy: (1) Motivation & Confidence; (2) Physical Competence (CAMSA Score); (3) Knowledge & Understanding. Results The descriptive statistical results show the low level of physical literacy of children assessed by CAPL-2, which can raise concerns and doubts in the implementation process. However, the findings of this research also show strong empirical support for the construct validity, content validity, and estimated reliability of CAPL-2 that can be used to assess the physical literacy of children between the ages of 8 to 12 years in Indonesia. Proof of preliminary validity shows an acceptable value of validity, whereas, a low estimated value of reliability is produced only on the Knowledge and Understanding questionnaire. Conclusions Future studies are recommended to further evaluate the CAPL-2 protocol in larger samples in different regions of Indonesia, so as to provide psychometric evidence, validity, and reliability more specifically for each of its components.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".