Effect of Adapted Game-Aided Physical Education Program on the Motor Skills of Children with Autism Spectrum Disorders: Longitudinal Case Study
Bibliographic record
Abstract
The aim of this study is to reveal the effect of long term adapted game aided physical education intervention programconducted on an individual with ASD and to conserve the achieved skills. The participant was fourteen years oldduring study and was fifteen years old when research was completed. The study took 15 months in total including 12months of implementation process and 3 months of interval before retention test conducted on the participant. TheShort Form of 2nd version of Bruininks-Oseretsky Motor Proficiency Test (BOT-2 SF) was used as a measuring set.Obtained data were evaluated graphically. According to the obtained data, we determined a development but BOT-2SF started in different periods in 8 sub-dimensions under the title of fine and gross motor skills. When permanencytest was obtained after an interval of 3 months for examined intervention program, it was clear that all skills exceptpower sub-dimension were conserved. There was a decrease in a certain amount only in power sub-dimension. In thelight of all these consequences, we can say that even though it is late, adapted intervention programs conducted onthe individuals with ASD affect motor skill levels positively and it can be said that this development will be effectivein increasing life quality of the individuals with ASD.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".