An edutainment system for assisting qatari children with moderate intellectual and learning disability through exerting physical activities
Bibliographic record
Abstract
Children with Moderate Intellectual Disability (MID) and those with Moderate Learning Disability (MLD) are growing up with extensive exposure to computer technology. Computers and computer-related devices have the potential to help these children in education, career development, and independent living. However, most of the software, games, and web sites that MID and MLD children interact with are designed without consideration of their special needs, making the applications less effective or completely inaccessible. This paper introduces an edutainment system specifically designed to help these children have an enhanced and enjoyable learning process, while addresses the need for integrating physical activity into their daily lives. The proposed system consists of a padded floor mat that includes sixteen square tiles supported by sensors, which are used to interact with a number of software games specifically designed to suit the mental needs of children with ID. The system aims for enhancing both MID and MLD children learning capabilities, understanding, communications, thinking, memorization, and obesity problems.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.010 | 0.001 |
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".