‘Dreaming in colour’: disabled higher education students’ perspectives on improving design practices that would enable them to benefit from their use of technologies
Bibliographic record
Abstract
Abstract The focus of this paper is the design of technology products and services for disabled students in higher education. It analyses the perspectives of disabled students studying in the US, the UK, Germany, Israel and Canada, regarding their experiences of using technologies to support their learning. The students shared how the functionality of the technologies supported them to study and enabled them to achieve their academic potential. Despite these positive outcomes, the students also reported difficulties associated with: i) the design of the technologies, ii) a lack of technology know-how and iii) a lack of social capital. When identifying potential solutions to these difficulties the disabled students imagined both preferable and possible futures where faculty, higher education institutions, researchers and technology companies are challenged to push the boundaries of their current design practices.
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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 | 0.014 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.013 | 0.026 |
| Scholarly communication | 0.018 | 0.006 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.004 | 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".