Page 195 -

182 CHAPTER 7 Case studies

Informal case studies are often most effective as intermediate steps in larger re-
search processes. This can be true of studies that are used as pilot investigations of
user needs prior to more formal study with multiple cases or as initial investiga-
tions of a tool in use before conducting larger summative evaluations (Chapter 10).
Descriptions of these case studies and how they influence the subsequent investiga-
tions can be valuable pieces of your eventual write-up.

7.12 SUMMARY
As every individual who uses computing tools does so in a unique context, with spe-
cific goals, backgrounds, and abilities, every use of a computer interface is, in some
sense, an HCI case study. Close examination of these contextual factors can give re-
searchers a rich, detailed understanding of the factors that influence system require-
ments and determine the success or failure of proposed designs. Unlike controlled
experiments, which attempt to find general answers to fairly narrow questions, case
studies are deep and narrow, focusing on thorough exploration of a small set of cases.
If your research leads you to a situation that seems to be in some sense notable
or perhaps unique, you might find yourself considering a case study. Possibilities
include studying a domain expert's information management techniques in order to
inform the design of a new system; comparing two installations of a new collabora-
tive tool in different contexts; or describing your use of a new participatory design
technique in the development of a new tool. Regardless of the context, you should be
clear about your goals, as they impact how you design and conduct your study. If you
are interested in generalizing from your cases to make broader claims, you should
be particularly careful about your research design and analysis, making sure that the
data favor your arguments over alternative explanations. Open-ended explorations
aimed at generating ideas and descriptions of a unique or unusual situation may not
make any broader claims, but they will still benefit from a clearly thought-out design
and analysis plan.
Case study research is harder than it may look. Although the small number of
participants and the lack of quantitative analysis may be appealing, the studies pres-
ent substantial analytical and logistical challenges. Selecting cases is often difficult,
whether you are identifying the most promising participants from a large pool or
worrying about the representativeness of the sole case that you have been able to
find. Collecting multiple, corroborating pieces of data may be difficult and teas-
ing interesting insights out of potentially messy and inconsistent data can be tricky.
Scheduling the appropriate meetings and working around the needs of your partici-
pants can often be a real chore.
The case study's focus on deep, narrow investigation leads to inevitable concerns
about validity. How can we learn anything general from the study of a small set—
sometimes only having one member—of instances of a given phenomenon? With
rigorous evaluation involving multiple participants and (very often) statistically ana-
lyzed quantitative results playing such a pivotal role in recent HCI research, it may