Developing an Instructional Unit in Vocational Education Curriculum, based on the International Standards of Nutrition and Sports, and Investigating its Effectiveness on Improving the Physical Self-Concept among Eighth Grade Female Students in Jordan
Bibliographic record
Abstract
The aim of this study was to identify the effectiveness of a developed Instructional Unit Based on International Standards in Nutrition and Sports and Examine its Effectiveness on Improving the Physical Self-Concept Among Eighth Grade Female Students in Jordan. The students were selected from the eighth grade students in the first Secondary university schools –Femal- in the capital Amman during the Second semester of the academic year 2017/2018. The researchers identified the private schools that include two divisions of the eighth grade and chose one of them. One of the two divisions was randomly assigned to be an experimental group (26) and the other to be a control group (29) students. In order to achieve the objectives of the study, the measure of the self-concept of the body was composed of (24) items. An Instructional Unit was developed in the vocational education curriculum based on international standards in nutrition and sports to measure its effectiveness in improving the concept of the physical self. The developed unit consisted of (8) international standards in nutrition and sport, where (36) outcomes were derived, and were implemented in (20) Forty-five-minute lessons. The results showed a statistically significant effect on the developed unit based on the global standards in nutrition and sport. The level of the self-concept of the students in the experimental group was higher than the students of the control group.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".