Cognitive Fit: An Empirical Study of Information Acquisition

From a broad perspective, our research can be viewed as investigating the fit of technology to task, the user's view of the fit between technology and task, and the relative importance of each to problem-solving or decision-making performance. The technology investigated in this research is the mode of information presentation. Although there has been a considerable amount of research into problem solving using graphs and tables, until recently the circumstances in which each is more effective have been largely unresolved. Recent research has suggested that performance benefits accrue when cognitive fit occurs, i.e., when factors such as the problem representation and problem solving tools match the characteristics of the task. In this paper, we investigate the effects of the basic paradigm of cognitive fit and extensions to the paradigm in a laboratory experiment that examined the nature of subjects' mental representations as well as problem-solving performance. The experiment, using 128 MBA students in two identical, repeated measures designs, produced the following results: • Performance improved markedly for symbolic tasks when the problem representation matched the task. Performance effects also resulted from matching specific problem-solving skills to the problem representation and the task, and to a lesser extent when the skills matched the task alone. • The incremental effects of matching skills to the problem representation and/or the task were small compared with the primary effects of cognitive fit-that of matching problem representation to task. • A large proportion of problem solvers have insight into the concept of supporting tasks with certain types of problem representation and vice versa. • Participants preferred to use tables rather than graphs; they also preferred to solve symbolic rather than spatial problems. Finally, the problem representation more significantly influenced the mental representation than did task conceptualization. This research suggests that providing decision support systems to satisfy individual managers' desires will not have a large effect on either the efficiency or the effectiveness of problem solving. Designers should, instead, concentrate on determining the characteristics of the tasks that problem solvers must address, and on supporting those tasks with the appropriate problem representations and support tools. Sufficient evidence now exists to suggest that the notion of cognitive fit may be one aspect of a general theory of problem solving. Suggestions are made for extending the notion of fit to more complex problem-solving environments.