A scoping review of the playground experiences of children with AAC needs*
Bibliographic record
Abstract
Unstructured play on playgrounds is beneficial to children’s development, but children with disabilities are often unable to use playgrounds in the same ways as their peers without disabilities. No research to date has focused exclusively on the playground experiences of children who use augmentative and alternative communication (AAC). Therefore, in this scoping review, information from 10 studies published between 1990 and 2020 that investigated the playground experiences of children with disabilities, including those with limited speech, is synthesized. Included studies used experimental or non-experimental designs and involved the collection of either quantitative or qualitative data. The findings indicate that children with limited speech have diverse playground experiences and can benefit in some of the same ways as children with typical development from playground play but that they encounter barriers to participation that go beyond a lack of physical access. Additional research focusing specifically on understanding the communication experiences of children who use AAC on playgrounds is essential to address the complex issues associated with playground participation, including access to aided AAC systems on the playground. To foster more inclusive playgrounds, accessibility standards must address the unique needs of children with limited speech to support participation and access to communication on the playground.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.022 | 0.022 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".