Qualitative_data_analysis

276 QUALITATIVE DATA ANALYSIS
the achievement of traditional ideals. For example, it is now more feasible to reach a
‘saturation’ point, where all the relevant data have been incorporated into the
analysis. To assess the strength of data supporting any particular conceptualization
is now a much more straightforward matter. Auditing the analysis has become a
much more manageable task. The computer supports a more complex and
comprehensive analysis than was previously possible.
The real issue is not so much whether the computer will replace thinking, but
how it may shape it. Here, the new technology offers real advances, most obviously
in its powerful search facilities, and in the ability to create Hypertext links between
different bits of data. Neither may be an unmitigated blessing, as text retrieval
systems may encourage misplaced confidence in the computer’s ability to identify
relevant data (Pfaffenberger 1988:52–6), while Hypertext procedures may
encourage excessive complexity in the analysis (Cordingley 1991). However, both
these facilities can support ways of thinking about data which were difficult if not
impossible using traditional methods. Search facilities support a more rigorous and
theoretically driven process of ‘interrogating’ data, exploring and testing for
connections between concepts through more or less sophisticated forms of data
retrieval. Hypertext facilities provide ways of overcoming the fragmentation of data,
mitigating if not eliminating some of the dualisms characteristic of qualitative
analysis, such as the tension between analysing data in context and through
comparison. Of these dualisms, perhaps the most significant is the fragmentation of
data into bits which we nevertheless want to interrelate. Through electronic linking,
we can at least partially overcome this fragmentation. We can observe, record and
store links between bits of data, which can then be retrieved as a means of
examining substantive connections between categories. Here again, the computer
offers a significant advance in flexibility and rigour by comparison with what was
possible using traditional methods.
Of course, what the computer offers, and what we do with it, may be two
different things. It may be that, in our enthusiasm for handling large volumes of
data, or our fascination with the technology, we let the tool define the task, rather
than allowing the task to dictate our use of the tool. As John Seidel puts it, we
should be aware of what the computer can do to us, as well as for us (1991:116). But
problems arise when the analyst is mechanical, not the computer. The computer
cannot think for us, and not much good will come of it if we entertain unreasonable
expectations of what it can do. If the computer is to be used rather than abused, it
must be understood in the context of the analytic tasks required of us, the analysts.