Children with ASD transitioning into primary school: Inclusive Education
Bibliographic record
Abstract
Introduction: Although research related to children with Autism Spectrum Disorder (ASD) entering school has described on one hand parents' dissatisfaction with school systems and on the other teachers' struggles to support with those children, links between both perspectives on the same child have been less examined. The objective here is to present the mutual experience of parents (perceptions of support, partnership, empowerment and family quality of life) and teachers (sense of self‐efficacy; efforts to support children and families) as children with ASD transition from kindergarten to first grade. Methods: A multiple case study approach was used to explore the transition of 8 students with ASD in the Montreal area. Using IPods in a photovoice approach, 50 interviews were conducted to describe changes over time (9 months) in special and mainstream classes. Results: Results illustrate similarities across cases; such as, a very high level of parents' involvement and a common teacher's willingness to support the child and his family. Differences were found such as parent advocating more for their child rights in a mainstream context, and special education teachers struggling more with academic learning. Implications: Implications regarding the principle of inclusive education will be discussed based on paired data from parents and teachers.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".