Assistive technology outcomes in post-secondary students with disabilities: the influence of diagnosis, gender, and class-level
Bibliographic record
Abstract
This study investigated how outcomes of assistive technology (AT) services for college students with disabilities are influenced by diagnosis, gender and class-level (e.g., Freshman). Students' pre- and post-intervention ratings of their performance and satisfaction of common academic tasks (using the Canadian Occupational Performance Measure, COPM) were analyzed, as well as students' responses on a survey about AT service provision, use, and preferences. Data from 455 students revealed "learning disability" to be the most prevalent diagnosis (38%), similar numbers of females and males served, and Freshmen (23.1%) as the largest class-level seeking AT services. For COPM data, each two-way analysis of variance (ANOVA) (grouping variable = diagnosis) revealed that pre-post change scores significantly improved for the entire sample, and that students with a mood disorder experienced the greatest changes compared to other diagnoses. COPM scores significantly and similarly improved for females and males, and across class levels. AT Survey ratings about timeliness of services and independent AT use were significantly lower for students with mobility deficits/pain and neurological damage, respectively. Gender and class-level variables did not significantly impact AT Survey ratings. The study results reveal that features of a college student's diagnosis may influence AT service outcomes, and student-perceptions of AT services ability to use AT. Implications for Rehabilitation College students who are Freshman and/or who have a learning disability are the most prevalent students referred for campus-based assistive technology services. While student ratings of academic task performance significantly increase across diagnostic groupings, these improvements were greatest for those with a mood disorder compared to other diagnostic groups. Service-providers should consider that features of certain diagnoses or disabilities may influence the student?s perception of AT service provision and their ability to use AT. A student's gender and class-level (e.g., Freshman) do not appear to influence the outcomes of AT services for college students with disabilities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.022 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".