Recent Technologies to Improving Social and Communication Skills in Children with ASD: Systematization of Approaches and Methods
Bibliographic record
Abstract
In the article recent technologies of formation and development of social and communication skills in children with autism spectrum disorders are analyzed. A systematic review summarizes the most effective and verified interventions of support to socialization of children with ASD: applied behavior analysis (ABA); cognitive-behavioral training (CBT); social stories method; social skills training (SST). We pay special attention to virtual technologies and video simulations so these methods allow to form social skills in children with ASD more efficiently and psychologically safe. Problems and prospects of using virtual technologies for children with ASD needs are discussed. The specificity of Russian practical experience and researches in development of heuristic technologies of development of social communication of persons with ASD is described: animal-assisted therapy, somatosensory correction, author art therapy and folk forms of intervention. On the basis of analytical work it is concluded that the gap between theory and practice needs to be neutralized, when scientifically unfounded practical developments are introduced in helping autistic people and researches of scientists are not always verified in an empirical manner.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".