This thesis presents a novel application of user modelling, the domain of interest being
the physical abilities of the user of a computer input device. Specifically, it describes a
model which identifies aspects of keyboard use with which the user has difficulty.
The model is based on data gathered in an empirical study of keyboard and mouse use
by people with and without motor disabilities. In this study, many common input
errors due to physical inaccuracies in using keyboards and mice were observed. For
the majority of these errors, there exist keyboard or mouse configuration facilities
intended to reduce or eliminate them. While such facilities are now integrated into the
majority of modem operating systems, there is little published data describing their
effect on keyboard or mouse usability. This thesis offers evidence that they can be
extremely useful, even essential, but that further research and interface development
are required. This thesis presents a user model which focuses on four of the most
commonly observed keyboard difficulties. The model also makes recommendations
for settings for three keyboard configuration facilities, each of which tackle one of
these specific difficulties.
As a user modelling task, this application presents a number of interesting challenges.
Different users will have very different configuration requirements, and the
requirements of individual users may also change over long or short periods of time.
Some users will have cognitive impairments. Users may have very limited time and
energy to devote to computer use. In response, this research has investigated the
extent to which it is possible to model users without interrupting the task for which
they are using a computer in the first place. This approach is appealing because it does
not require users to spend time participating in model instantiation. This focus on
inference rather than explicit testing or questioning also allows the model to
dynamically track an individual user's changing requirements.
This thesis shows that within the context of the keyboard difficulties studied, such an
approach is feasible. The implemented model records users' keyboard input
unintrusiveiy as they perform their own input tasks. This input is examined for
evidence of certain types of input error or indications of difficulties in using the
keyboard. In the model presented, conclusions are based on the assumption that the
user is typing English text in a word processing application. However, the design of
the model allows any other textual language to be used.
A second empirical study, evaluating the model, is described. The model is shown to
be very accurate in identifying users having difficulties in each of the areas tackled, the
only exception being those who find a given operation awkward, but are able to
perform it accurately. Where it is also possible to evaluate the configuration
recommendations made by the model, the chosen settings are effective in reducing
input errors and increasing user satisfaction with the keyboard. The model is also able
to draw conclusions quickly for users with higher error rates, and shows good overall
stability.
In the light of this successful identification of keyboard difficulties, potential
applications of the model are suggested. It could be used to help occupational
therapists and assistive technologists to assess the keyboard configuration
requirements of a new user. It could also be made available to users themselves -
many people are currently unaware of facilities they may find useful, and how to
activate them. The model could be extended to other areas of keyboard use, and to
other input devices. This would allow systems to provide automatic, dynamic support
for configuration, which would go some way towards improving the accessibility of
computer systems for people with motor disabilities