Integrated specialized learning application (ISLA) to teaching addition to high functioning children with autism spectrum disorder (ASD)
Bibliographic record
Abstract
L'autisme est : A neurological disorder affecting the way the brain processes information and which can affect all aspects of the development of a person. Autism is four times more common in boys than in girls. The Autistic Spectrum Disorders (ASDs) are characterized by impairments in language and communication, in social interaction, in imaginative ability and by the presence of repetitive and restricted patterns of behavior. (DSM-IV). Cette recherche contribue a l'avancement des systemes tutoriels intelligents affectifs en proposant un systeme tutoriel intelligent affectif pour surmonter le manque d'intervention personnalisee dans le domaine de l'education specialisee visant les personnes ayant des troubles envahissants du developpement. ISLA est une application adaptative dans le domaine de l'education specialisee qui evolue avec les besoins de l'etudiant. ISLA est unique et sa contribution comporte le modele d'accompagnement pour aider les enfants autistes a gerer leurs emotions en analysant la trace d'apprentissage de l'etudiant et en permettant de repondre en consequence afin d'aider l'etudiant autiste a calibrer ses emotions durant une situation d'apprentissage de mathematique telle que l'addition.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.016 | 0.004 |
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".