Co-designing new keyboard and mouse solutions with people living with motor impairments
Bibliographic record
Abstract
In this report we share a co-design process for developing more accessible alternatives to traditional keyboard and mouse interfaces, involving individuals with motor impairments. We describe our methodology, including initial discovery phases that inspired three subsequent co-design workshops with three individuals with motor impairments and 26 designers. Based on our experience, we highlight the importance of creating an equitable and effective dialogue between designers and individuals with motor impairments, emphasizing the personal nature of each participant’s experiences and the potential of technology as an enabler rather than a generic solution. Guided simulations and hands-on prototyping were employed to trigger meaningful conversations. We underscore the significance of “being with” during the co-design process and the importance of a transparent prototyping and development process for creating genuinely accessible and inclusive interactive systems. By sharing our findings and recommendations, we aim to assist researchers running future co-design workshops that involve prototyping with technology and people of diverse backgrounds.
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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 | 0.018 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".