In the Nick of Time: A Pan-Canadian Examination of Extended Testing Time Accommodation in Post-secondary Schools
Bibliographic record
Abstract
Extended testing time accommodation (ETTA) is the most common accommodation assigned to post-secondary students with disabilities. We examined data on the processes of providing and monitoring the use of ETTA at 48 Canadian post-secondary institutions who provided accommodations to over 43,000 students with disabilities in every province in Canada. Findings indicated that students with learning disabilities were the most likely to be allocated ETTA. The most common duration of ETTA by far was 150% of the standard testing time provided to other students, and was typically assigned in over 70% of cases-- despite there being no valid empirical evidence to support this practice. In almost half of the institutions following this practice, this duration of ETTA was typically awarded upon intake based on guidelines, policies, or the belief that research exists to support this procedure, and in over 40% of these institutions there were no procedures in place for monitoring and modifying ETTA allowances once assigned. There was evidence of some exemplary practices in terms of the decision-making processes that went into determining and monitoring individual student’s ETTA durations. However, concerns were raised in some cases by the rationales for providing specific durations of ETTA, and by the lack of monitoring that together comprised ‘blanket’ accommodations.
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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 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.011 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.005 |
| 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".