Teacher perspectives and approaches toward promoting inclusion in play-based learning for children with developmental disabilities
Bibliographic record
Abstract
As school authorities strive toward inclusive models of education for children with neurodevelopmental delay and disability (NDD), many kindergarten curricula have mandated pedagogy centered on learning through play. Children with NDD tend to experience greater social isolation and lower rates of social play engagement compared to typically developing peers. Consequently, issues related to social participation and inclusion may be particularly salient in play-based kindergarten classrooms. The current qualitative study explored how eight kindergarten teachers in Ontario, Canada conceptualized and promoted inclusion in play for children with NDD. Classroom observation and teacher interviews were conducted with a focus on the teacher’s role in play. Teachers endorsed the use of several indirect (i.e., environmental) strategies to promote social participation, alongside proactive teacher support in play. Teachers who shared multiple aspects of an interventionist viewpoint toward disability, and identified the social benefits of inclusion in play for children with NDD, tended to provide more proactive support to all children in play. Teachers also provided reactive support in play to address emerging social conflict. Implications for fostering the meaningful inclusion of children with NDD in play-based learning are discussed.
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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 | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.014 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| 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".