Assistance Dogs in Schools: What Does This Change for Teachers?
Bibliographic record
Abstract
Students with Autism Spectrum Disorder (ASD) often receive less instruction in reading and writing due to challenges related to daily life skills. However, these academic skills are crucial for promoting social inclusion. The use of assistance dogs—particularly those trained by the organization Mira—is recognized for supporting both social and cognitive development in these students. Despite this, the actual impact on teaching practices remains underexplored. This exploratory study, based on a questionnaire completed by 29 teachers who had integrated an assistance or therapy dog in their classroom, analyzes their experiences using the theoretical framework of Bélanger et al. (2012). Results show that while teachers generally feel competent in integrating the dog, the support they receive is mostly limited to behavioral rules (e.g., no touching or calling the dog), with little to no pedagogical guidance. The dog is seen as an emotional support for the student user but is rarely included in learning activities. Some teachers, however, express a desire for more flexibility in the rules to promote better social and educational inclusion. The study suggests a need to reconsider current practices and regulatory frameworks around assistance dogs to better harness their educational potential.
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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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.009 | 0.012 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".