THE THEORY OF COGNITIVE FIT - Human-Computer Interaction and Management Information Systems: Foundations - page 157

cognitive fit remain unchanged). The findings of this experiment show that when the schema
comprehension tasks involve only data extraction (i.e., cognitive fit exists), knowledge of the
application domain has no effect on problem-solving performance; problem solvers can address
problems with reference only to the IS task materials. On the other hand, on more complex tasks
for which problem solvers need to transform the data extracted from the conceptual schema (i.e.,
cognitive fit does not exist), knowledge of the application domain, although not essential, facili-
tates problem solution.
DISCUSSION AND IMPLICATIONS
The theory of cognitive fit was first introduced into the IS community in 1991 to explain the results
of numerous studies that sought to address performance differences in the use of graphs versus
tables. At the same time, the theory was thought to be one aspect of a general theory of problem solv-
ing, applicable across domains and possibly also across different dimensions of fit. In this study,
therefore, we sought to determine how the theory of cognitive fit has been applied over time, whether
the basic tenets of the theory are still applicable or whether the theory needs to be modified in some
way, and, thereby, to assess whether it can be regarded as a general theory of problem solving.
This section discusses our findings and presents the contributions of our research. We conclude
with the implications for future research into the theory of cognitive fit.
Discussion of the Findings
In this paper, we sought to address how the theory of cognitive fit has stood the test of time. The
bulk of the paper is devoted to an analysis of published studies. Other recent studies are used to
present theoretical advances that incorporate recent thinking in cognitive science into the basic
model of cognitive fit and that extend the model to problem solving in situations involving two
interacting tasks.
In our analysis of published studies based on the theory of cognitive fit, we classified studies
according to whether they tested concepts found in the two foundational papers that present the
theory (Vessey, 1991, 1994), whether they applied the theory to new domains of investigation, and
whether they developed/used new dimensions of fit. By far the majority of studies in this analysis
addressed more complex problem-solving tasks. We discuss each of these three situations in turn.
Studies of core cognitive fit conducted in both the realm of simple information acquisition and
information evaluation tasks, and of more complex tasks, largely support expectations. There is
one exception. According to the theory, graphs should result in more accurate and quicker solu-
tions to simple spatial tasks than tables; this is the finding in the majority of studies examining
simple spatial tasks (see Vessey, 1991; Mahoney et al., 2001). However, if the spatial task is too
simple, the fact that problem solvers are not as familiar with graphs as they are with tables—see,
for example, Vessey and Galletta (1991), among other authors—means that they incur some cog-
nitive overhead in using graphs. In this case, the problem may be solved either more accurately
using tables (Vessey, 1991) or equally as well (Chan, 2001).
The prediction that problem solvers will change strategy when requested to perform complex
symbolic tasks using analytical processes, which are best supported by tables, to perceptual
processes, which are best supported by graphs, is confirmed in this analysis. In fact, the complex
symbolic task used by Speier and Morris (2003) was so complex that decision makers had little
hope of using analytical processes to solve the problem. They therefore used perceptual
processes. This type of task is referred to as a limiting task (Johnson and Payne, 1985; Vessey,