Assessment of aided language comprehension and use in children and adolescents with severe speech and motor impairments
Bibliographic record
Abstract
There is limited knowledge about aided language comprehension and use in children who use aided communication and who are considered to have a relatively good comprehension of spoken language. This study's purpose was to assess their aided language skills. The participants were 96 children and adolescents who used communication aids (aided group) and 73 children and adolescents with natural speech (reference group), aged 5 to 15 years. All of the participants who used aided communication were regarded by their teachers or professionals as having age-appropriate language comprehension. All of the participants completed (a) standardized tests of visual perception, non-verbal reasoning, and comprehension of spoken language, and (b) tasks designed for this study that measured comprehension and production of graphic utterances through communicative problem solving. Using their own communication systems, the participants achieved an average of 72% correct on the graphic symbol comprehension task items, and 63% on the expressive tasks. The participants with natural speech achieved an average of 88% correct on comprehension items, and 93-96% accuracy on production items. The differences between groups were significant on all the tasks and standardized tests. There was considerable variation within the group of participants who used aided communication, and the results reveal a need to develop instruments with norms for aided language competence that can inform the implementation of interventions to support aided language development.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".