Online Independent Intervention Program Training for Parents of Children with Autism: An Evaluation
Bibliographic record
Abstract
Independent Intervention Program (IIP) Training or Pelatihan Program Intervensi Mandiri (PIM©©) is an Indonesian training model designed to develop parents’ ability in intervening the social skill of their children with autism. The offline training, however, came with some limitations; it had limited number of participants—all coming locally and were only accessible on certain time slots. As a response to these limitations, the IIP training is held online. The research began with spreading of the information regarding the training, analyzing the registered individuals, and appointing them participants when the main criterion is fulfilled: the participant must be a parent of a child with autism. Out of 84 registered individuals, 11 participants were selected, all agreeing to follow through all the training steps. The effectivity of the training was measured using a self-evaluation questionnaire for the participants, as well as evaluation given by instructors. Based on the findings, the online IIP training comes with several advantages: 1) improving parents’ knowledge and ability regarding the intervention on the social skill of their children with autism; 2) having a wider target of participants compared to its offline counterpart; 3) in terms of time and place, offering greater flexibility for participants to access materials for the training. As an implication of the evaluation result, a new strategy is needed to ease online interaction process between instructors and parents in planning the intervention program and implementing it on their children.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".