Pengembangan Permainan Edukasi Berbasis Kinect Bagi Penderita Asperger Syndrome Untuk Menangani Empathy Disorder
Bibliographic record
Abstract
In Indonesia, the handling of empathy disorder in asperger syndrome sufferers was not welcomed by parents due to cost and transportation factors. In addition, treatment of empathy disorder in asperger syndrome sufferers is given the same treatment with other Autism Spectrum Disorder (ASD) classification. This research aims to develop Kinect-based educational game that can help a person with asperger syndrome in understanding feelings of the others, so that empathy toward each other can grow. At the end of 2013 until 2014, Kinect considered feasible for dealing with therapy and rehabilitation in people with neurological disease and Traumatic Brain Injury (TBI). In this research, Kinect applied in educational game that relies on the movement of the right hand. This research was tested on 5 asperger syndrome sufferers with empathy disorder. The results of this research achieved after asperger syndrome sufferers using Kinect-based educational game, that resulted increased score on each level and emotion, as well as descreased total Toronto Empathy Questionnaire (TEQ) of 12.8% from average of total TEQ before asperger syndrome sufferers using Kinect-based educational game.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".