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task. On the one hand, interaction with the mobile device/application requires, to some extent, user's
innate resources (such as attention). On the other hand, the primary task does often require, to an
even higher degree, the user's physical, visual and cognitive involvement/resources (such as hands,
visual attention, mental focus). The user's physical, visual and cognitive involvement/resources are
therefore likely to get constrained. Ideally, the mobile application (including interactions with the
device/the non-primary tasks) should support the user in carrying out the primary task rather than
“support the user in tampering” with the primary task. We should minimize distracting the user
from the primary task or disrupting the user's primary task, unless the disruption/distraction is of
genuine (and great) value or of critical importance. In adopting ways to meet the requirement, it
is also critical to consider the status of a user's attention in the timing of the tasks on the mobile
device (i.e., non-primary tasks). It might be worth counting the costs and gains of deferring an
operation/activity to another time when that operation/activity will be less of a distraction. Where
necessary, the mobile application should enable/allow the user to temporary halt a task on the device
and to resume the interrupted task.
One of the challenges with new or innovative technology/application is that its users may try
to use it in situations or ways the designers and developers had never thought of. This is no less true
in mobile computing. There is, therefore, a sense in which the user may perform tasks on the device
in unpredictable and opportunistic ways. Taking care of all possible use scenarios for a product is a
non-trivial challenge for the mobile application analysts and designers. It is also worth observing
that the variability of the environment/natural setting may affect the course of a task. Therefore,
analysts and designers may also need to account for such variability in the task analysis.
The Model Human Processor model (
Card et al.
,
1983
) has been a benchmark for a lot of
work in HCI. The model is a simplified view of human processing while interacting with computers.
It focuses on the internal cognition driven by the cooperation of: the perceptual system, the motor
system, and the cognitive system. Each of the systems maintains its own processing and memory.
However, as the role and domain of the computers (and devices) have widened, researchers and
designers have been considering models that take into account the relationship between the internal
cognition and the outside world (
Dix et al.
,
2004
). Some researchers are exploring the following
three main models of cognition for possible application in mobile computing: activity theory model,
situated action model, and distributed cognition model (
Abowd, Mynatt, and Rodden
,
2002
). The
activity theory model is built on concepts such as goals, actions, and operations. Goals and oper-
ations are flexible depending on the dynamic nature of the outside world. Moreover, an operation
can shift to an action due to a changing situation/context. The model also supports the recog-
nition/acknowledgement of the transformational properties of artifacts. The situated action model
allows knowledge in the outside world to constantly mould the ongoing interpretation and execution
of a task. The distributed cognition model views the user (internal cognition) as only a part of much
larger system. It was observed earlier that tasks on the mobile device (and elsewhere) do sometimes
tend to be unpredictable and opportunistic. It is interesting to note that the foregoing models of
activity theory, situated action, and distributed cognition could be resourceful in this respect. It is
