Developing a measurement tool for assessing animal-assisted activity effectiveness on children with special educational needs’ socialization: A pilot study
Bibliographic record
Abstract
Objective: This study aimed to develop an observational tool to assess the social interactive behaviors of children with special education needs during animal-assisted activity and to examine its reliability and validity. Methods: The study comprised two phases: developing and evaluating the measurement tool. The tool was created through literature reviews and expert interviews. The pilot observational study was conducted in a special educational school in Hong Kong, China, involving 138 children with intellectual disability participating in animal-assisted activity sessions to examine the tool’s reliability and validity. Results Initially, the measurement tool included 26 observational variables across three dimensions (inter-rater reliability of 0.74). After excluding variables with low discriminability, the final tool contained seven observational variables. The tool demonstrated strong reliability (inter-rater reliability of 0.81) and satisfactory validity, significantly discriminating among different intellectually disabled students ( p s < 0.05). Conclusions: This study developed and validated an observational tool for measuring the social behaviors of children with special education need during animal-assisted activity sessions. More extensive studies are needed to further evaluate the instrument.
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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 | 0.028 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".