Analysis of the behavior of children with ASD during physical activity
Bibliographic record
Abstract
Interventions in physical activity for children with ASD (Autism Spectrum Disorder) remain a challenge for educators for the following reasons: first, information processing, an essential foundation for physical practice, is a persistent impairment for this population due to the sensory deficits associated with this condition. Second, their reluctance to engage and participate in physical activity due to challenging behaviors. The aim of the present study toward quantitatively measuring the behaviors of children with ASD in relation to motor task design during a physical activity session.Eight children were recruited for this study (6 boys; 2 girls), aged between 6 and 12 years (mean = 10.0 1.5 years). All participants were classified at level 2 (moderate) according to the APA (2015), which takes into account the amount of support the child needs to function in their environment. The inclusion criteria adopted in this study were as follows: regular, full-time attendance at the association where the study was conducted, absence of regular participation in extracurricular sports activities, absence of comorbidities that would impair physical activity (e.g., visual impairment), and absence of medical treatment (e.g., psychotropic medications) likely to influence the study's outcomes. Three types of motor tasks (closed, play-based, and interaction-based) were designed in this study to assess their impact on the behaviors of children with ASD. Live and video scoring allowed us to evaluate both positive and problematic behaviors of the participants.The results revealed that task design plays a crucial role in the emergence of behaviors in children with ASD. Specifically, the more task is tailored to their unique characteristics, the more problematic behaviors decrease and positive behavior increase. This is particularly true for play-based tasks, which demonstrated a more pronounced effect and a preferential advantage compared to other tasks. Indeed these tasks led to significant improvements in most items (5 out of 7 items), due to their approach rootes in unconscious learning, which proved to be beneficial for these children during physical activity.The findings of this study may provide a promising pathway for the development of programs and the design of physical activity learning situations for this community with very specific needs.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| 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".