Evaluation of Multimedia-Based Intervention for Students With Autism Spectrum Disorder: A Pilot Study
Bibliographic record
Abstract
This pilot study evaluated the possible risks and prospects of a multimedia-based intervention in improving the social and adaptive skills of students diagnosed with autism spectrum disorder (ASD). Thirty Filipino special education teachers served as evaluators and teacher-respondents. Using a validated and reliability-tested evaluation grid, they evaluated the intervention using the following constructs: alignment and appropriateness, utility and relevance, visual appeal, and overall engagement. The findings of this preliminary study indicate that the overall evaluation of this relatively unexplored multimedia-based intervention was favourable (M = 4.502); in other words, teacher-respondents found that the intervention has the potential to enhance the social and adaptive skills of students on the spectrum, including their attention, task performance, social learning, and engagement. Furthermore, the findings highlight the positive perception of the multimedia-based intervention among the participating teachers and suggest that its potentiality was contingent neither on their number of years in the field nor the number of students with ASD enrolled in their classes (p-values > 0.05). The results of both descriptive and inferential statistics, in conjunction with valuable recommendations from the teacher-respondents, led to the formulation of a targeted action plan for enhancing the efficacy of the proposed multimedia-based intervention.
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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 | 0.003 | 0.007 |
| 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 | 0.000 |
| 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".