Teaching Generalized Imitation Skills to a Preschooler With Autism Using Video Modeling
Why this work is in the frame
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Bibliographic record
Abstract
This study examined the effectiveness of video modeling to teach a preschooler with autism to imitate previously mastered and not mastered actions during song and toy play activities. A general case approach was used to examine the instructional universe of preschool songs and select exemplars that were most likely to facilitate generalization. Experimental control was evident in a multiple baseline design across three imitation activities. In addition to video modeling, additive components that included highlighting critical features of the video examples, prompting/fading, and social reinforcement were required to demonstrate a functional relationship. The results also showed generalized imitative performance to actions that were not previously mastered. The findings suggest that general case analysis, video modeling, and additive procedures can be combined to both teach new imitative behaviors and promote generalization of previously-mastered behaviors. The results are discussed with reference to future research directions and implications for practice in educational settings.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it