Canadian Postsecondary Students with Learning Disabilities Describe Experiences with Assistive Services
Bibliographic record
Abstract
Colleges and universities typically assist students with learning disabilities. In Canada, such programs are legally mandated to ensure equal access to educational opportunities. However, there is little in the current research literature on the experiences Canadian students with learning disabilities have with using assistive services provided by their postsecondary school, especially for students who have successfully completed postsecondary education. This generic qualitative study used the framework in disability studies in education as a foundation. The information for this study was gathered through online interviews with individuals with learning disabilities who were enrolled or had successfully completed their postsecondary education. A thematic data analysis provided clear insights into the lived experiences postsecondary students with learning disabilities have in using assistive services from their school. In general, the findings revealed that regardless of the negative experiences students with disabilities had in grade school being accommodated and recognized, they had much better experiences being accommodated in college and university. This study may contribute to positive social change by offering insights to colleges and universities to increase or improve the assistance provided to students with learning challenges. It may also motivate students with learning disabilities who may be afraid to enroll in postsecondary education, out of the fear of not being “good” enough.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.015 | 0.005 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".