Information Technology Reference
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INTRODUCTION
derived from extensive literature and empirically
validated, and so offer a sound basis for heuristic-
based evaluation of mobile computing. As well
as introducing the reader to the practical use of
heuristic evaluation, the article also describes
potential future research in the area.
This work has been carried out in the context of
MAIS
1
, a project whose research goal is to provide
a flexible environment to adapt the interaction, and
the information and services provided, according
to ever changing requirements, execution contexts,
and user needs.
The rest of the article is organized as follows:
Section 2 highlights some of the challenges posed
by mobile devices, applications and context; Sec-
tion 3 discusses the standard heuristic evaluation
method; Section 4 describes the methodology
we adopted to appropriate heuristic evaluation
for mobile computing and the results that we
obtained; Section 5 contains reflections regarding
this research activity; and Section 6 concludes the
article and highlights some future work.
Our focus in this article is on usability problems
in mobile devices and a discussion of their sources.
However, this should be set against a broader
view of the fantastic world of new opportunities,
advantages, and benefits that mobile devices and
contexts bring. While we will not touch explicitly
on this again, the article should be read in the light
that the problems and limitations are ones worth
tackling because of the opportunities offered by
the technology.
Expert-based evaluation techniques, such as heu-
ristic inspection (Nielsen et al., 1990) and cogni-
tive walkthrough (Wharton et al., 1994) typically
benefit from providing evaluators with guidance
(for instance, a set of heuristics or a checklist)
for identifying a prioritized list of usability flaws
(Kjeldskov et al., 2005). Expert-based evaluation
techniques are also well-known methods that can
realize a relatively quick and easy evaluation.
According to Po (2003), mobile computing
devices are typically 'smart products' or 'infor-
mation appliances', and are generally consumer
products. Their users are thus a 'heterogeneous
group' (Sade et al., 2002) and so it may be more
difficult to find suitable surrogate users for user-
based testing in mobile computing (Po, 2003). Po
further observes that even if appropriate surrogate
users were found, the realistic re-creation of the
user context in laboratories would be challenging
because of user mobility, which makes observa-
tion and video recording difficult (Vetere et al.,
2003). “Given the problems associated with user-
based evaluations of mobile devices, expert-based
usability techniques are considered to be more
appropriate” (Po, 2003). However, it is worth
noting that expert-based techniques have in the
past been criticized for finding proportionately
fewer problems in total, and disproportionately
more cosmetic problems (Karat et al., 1992). In
mobile computing the capacity of expert-based
techniques to adequately capture the multiple
contextual factors that affect user-system inter-
actions in real settings has been questioned (for
instance: Kjeldskov et al., 2003; Johnson, 1998).
We believe that heuristic evaluation can be
enriched and adapted toward capturing contextual
factors. This article describes how standard heu-
ristic evaluation can be made more appropriate/
relevant for mobile computing. In particular, the
article describes a modified collection of usability
heuristics that are designed to be appropriate for
this area. The heuristics have been systematically
Mobile Devices, Applications,
and their Context
In order to better understand how usability in
mobile computing can be evaluated and improved,
it is useful to outline specific limitations inherent
in mobile devices, applications and their context.
These fall into two broad categories: limitations
due to the nature of the devices themselves, and
limitations due to context of use and style of
interaction.
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