Impacts of Teachers� Pedagogical Approach on the Inclusion of Adolescents with Exceed Weight into Physical Education and Sports in Emirate of Ajman/United Arab Emirates
Bibliographic record
Abstract
Background.Physical Education and Sports (PES) is essential to the student's overall education.It has physical, affective, psychological, and social repercussions.Overweight adolescents are sometimes underestimated based on their lower physical performance and suffer from discriminatory attitudes by their peers and their physical education teachers.Objectives.This study aimed to investigate the impacts of teacher pedagogy and overweight or obesity on the inclusion of obese students in classrooms and to understand how PES teachers adapt their pedagogical interventions toward this category.Methods.A sample of 48 overweight or obese students and 20 teachers were approached from different schools in Ajman Emirate.Two questionnaires for obese students and PES teachers were used to collect the data.Results.According to the data collected through the questionnaire, 85.42% of obese students report that they rarely practice or do not practice physical activity outside of school, and 73.42% go to school by bus or car.In addition, 66.7% of the surveyed students said being overweight is a barrier to PSE practice.Similarly, 75% of the surveyed teachers said that obese students are not integrated with the PES course, but only 55% of teachers reported that the obese student became an obstacle in PES sessions, while 80% of teachers reported that obese or overweight students were marginalized by their colleagues.Conclusion.Our study confirmed an urgent need for effective teaching strategies/ pedagogies to include overweight or obese students in physical education engagement and learning.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".