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Record W4387793722 · doi:10.1145/3597638.3614549

Co-designing new keyboard and mouse solutions with people living with motor impairments

2023· article· en· W4387793722 on OpenAlexaff
Rodolfo Cossovich, Steve Hodges, Jin Kang, Audrey Girouard

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldHealth Professions
TopicAssistive Technology in Communication and Mobility
Canadian institutionsCarleton University
Fundersnot available
KeywordsEnablingProcess (computing)Human–computer interactionRapid prototypingComputer scienceDesign processCo-designEngineering design processPsychologyKnowledge managementEngineeringWork in process

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.075
GPT teacher head0.395
Teacher spread0.320 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2023
Admission routes1
Has abstractyes

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