• Figure 2. The Walking UI for a music player interface—an example of an adaptation to a temporary, situationally induced impairment. Larger buttons address the difficulty of pointing accurately while walking; larger fonts for song titles help with impaired reading speed; and differences in font size between titles and additional song information help direct fragmented attention. (Screenshots courtesy of Shaun Kane.)

The Walking UI prototype (Figure 2) provides an example of adapting to the changing abilities of mobile users. It provides different UIs for users when stationary and in motion [ 8]. Both versions use a similar design to ensure that users do not have to learn two separate UIs, but the walking variant has larger interactors to compensate for mobile users’ impaired dexterity and larger fonts for song titles to accommodate reduced reading ability. It also manipulates the visual saliency of important information. The walking variant illustrates two differences between the design requirements for mobile users and users with permanent impairments. First, because mobile users’ abilities change, frequently adaptations must support the transfer of user skills between interfaces. Second, manually designed adaptations for the most common mobile situations may be feasible because most users will experience similar impairments. The latter point makes mobile situational impairments a productive domain in which to initially explore the design space of user interface adaptations for dexterity, visual acuity, and attention impairments.

 

March + April 2012

interactions

fastest to use for that user. Despite a large space of possible solutions, Supple finds the optimal design in seconds; the resulting interfaces have improved the performance and satisfaction of users with motor impairments. Automatic user interface generation is a scalable approach and one that enables highly personalized and dynamic solutions. One of its limitations, however, is that the resulting interfaces are unlikely to capture all the nuances of the applications’ semantics, and the approach is fundamentally limited by what types of abilities can be modeled.

Empowering user communities
to design and share specialized
interfaces. Allowing users to rede-
sign the interfaces they use most
often is an alternative to relying
on automation. Challenges to this
solution include enabling deep
end-user redesign of existing user
interfaces and providing tools for
communities with similar abilities
and needs to share and collaborate
on the redesigns. Collaborative
user interface design is already
available for some gaming plat-
forms, and dedicated gamers have
developed interfaces optimized
for particular strategies or game
tasks. In the non-gaming world,
the AdaptableGIMP project has
developed infrastructure for com-
munity-based UI innovations [ 7].
In this project, users can develop
variants of the GIMP toolbox spe-
cialized for different tasks and eas-
ily post their designs on a shared
wiki so others can reuse these
adaptations. We see user-driven
design and sharing of specialized
interfaces as an important com-
ponent in our vision, and some-
thing that is largely unexplored.

Moving Forward

At CHI 2011 we organized a workshop on Personalized Dynamic Accessibility (though at the time we called it Dynamic Accessibility). Our goal was to provide an opportunity for researchers with diverse backgrounds but a shared interest in this topic to develop a common understanding and prioritize the research agenda.

One broad consensus among participants was that automated approaches to adaptation will likely be part of the solution landscape for Personalized Dynamic