The Influence of Self Regulated and Traditional Learning Model on the Development of Students’ Cognitive Process and Sport Enjoyment in Basketball Learning Process
Bibliographic record
Abstract
One of the critical issues in physical education is creating a fun physical education which can develop students’ cognition without ignoring the mastery of basic technique through the implementation of a learning model. To overcome the critical issue, an experiment using self regulation and traditional learning models have been applied to 60 junior high school students using randomized pretest-posttest control group design. The instruments used are questionnaire of cognition process development and sport enjoyment of which the validity and reliability have been tested. Based on the data analysis, results showed that there is an influence between the learning model and the development of cognition and sport enjoyment in basketball game learning; however, self regulation learning model gives more significant influence compared to that of traditional learning model. This model is recommended to be used by physical education teachers in junior high school. This model can be an alternative of innovation to the learning process of physical education because it is proven to significantly influence students’ cognitive development and sport enjoyment in basketball learning process.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".