Krzysztof Z. Gajos
Jacob O. Wobbrock
Daniel S. Weld
ABSTRACT
We evaluate two systems for automatically generating personalized interfaces adapted to the individual motor capabilities of users with motor impairments. The first system, SUPPLE, adapts to users' capabilities indirectly by first using the ARNAULD preference elicitation engine to model a user's preferences regarding how he or she likes the interfaces to be created. The second system, SUPPLE++, models a user's motor abilities directly from a set of one-time motor performance tests. In a study comparing these approaches to baseline interfaces, participants with motor impairments were 26.4% faster using ability-based user interfaces generated by SUPPLE++. They also made 73% fewer errors, strongly preferred those interfaces to the manufacturers' defaults, and found them more efficient, easier to use, and much less physically tiring. These findings indicate that rather than requiring some users with motor impairments to adapt themselves to software using separate assistive technologies, software can now adapt itself to the capabilities of its users.
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Index Terms
- Improving the performance of motor-impaired users with automatically-generated, ability-based interfaces
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Reviews
Mariana Damova
A contribution in the field of assisted computing for motor-impaired individuals, this paper presents experiments and evaluates the results from the use of two systems especially designed "to adapt user interfaces to the actual abilities of individual users with motor impairments." The purpose of the reported research is to verify usability and to compare acceptance by users of automatically generated user interfaces with that of commercially standard Windows user interfaces. The paper advances the idea that automatically generated interfaces are an important alternative to human-crafted interfaces because of the high cost of the latter and the variety of requirements for users with special needs. Creating cheaper and more easily adaptable interfaces is a step toward allowing all users equal access to computer facilities and regular activities. SUPPLE, one of the evaluated systems, uses "the ARNAULD preference elicitation engine to model a user's preferences regarding how he or she likes the interfaces to be created." The other evaluated system, SUPPLE++, "models a user's motor abilities directly from a set of one-time motor performance tests." The experiments are performed by 11 motor-impaired participants, with various conditions, and six able-bodied participants. The authors establish that all users perform better and prefer the ability-based interfaces; the preference-based interfaces rank second, and the standard baseline ones rank third. The paper shows, with a very detailed description of the methods and the calculation of the results, that evaluation takes place according to several parameters, such as widget manipulation time, interface navigation time, total time, error rate, and the following subjective criteria: ease of use, attractiveness, tiredness-producing, and efficiency. The ability-based and the preference-based interfaces score better than the baseline in all criteria except for attractiveness. The motor-impaired users were 8.4 to 42.2 percent faster with the ability-based interfaces. This study presents interesting insight in an intriguing field. The very promising results give hope that such applications will become fully accessible and usable after the prototypes become real systems. Supplied with extensive background research, comments, and illustrative pictures and graphs, this paper would be appropriate for those interested in applications for motor-impaired individuals and in interesting technological advances in general. Online Computing Reviews Service
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