Students with Disabilities Transitioning from High School to University in Canada: Identifying Changing Accommodations
Bibliographic record
Abstract
More students with disabilities are attending university in Canada, bringing increasing expectations for academic accommodations. This study compared accommodations offered in high school and university for 71 first-year undergraduates with disabilities at Queen’s University in Ontario, Canada. More than a third (34%) of the participants presented with a disability label at university different from what they had in high school. Eighty-six percent (86%) of participants received fewer accommodations in university (6.34 fewer on average). The most frequently lost accommodations were individualized instructional supports and extra time on exams. High school students who received human-assisted accommodations, and those who identified as exceptional, lost the highest number of accommodations. Accommodations increased for students who attended private high schools. These findings have practice implications for both high schools and universities. Instead of using disability labels, high school students with disabilities should be taught how to describe their disability-related functional limitations (FLs) within academic activities. High schools should align Grade 12 academic accommodations specifically to disability-related FLs for university-bound students with disabilities. Universities should communicate clear information about its accommodation process. This includes the conditions in which specific accommodations, such as memory aids, are granted. Universities should identify and support students whose accommodations change significantly upon their arrival from high school. Finally, universities ought to adopt Universal Design for Learning principles in teaching wherever possible. This will help create a welcoming learning environment for all students, including high school students experiencing significant changes to their accommodations as they transition to university.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".