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The Effects of Alternative Presentation Formats on Biases and Heuristics in Human Decision MakingVan Dyke, Thomas P. (Thomas Peter) 05 1900 (has links)
The purpose of this research was to determine whether changes in the presentation format of items in a computer display could be used to alter the impact of specific cognitive biases, and to add to the knowledge needed to construct theory-based guidelines for output design. The problem motivating this study is twofold. The first part of the problem is the sub-optimal decision making caused by the use of heuristics and their associated cognitive biases. The second part of the problem is the lack of a theoretical basis to guide the design of information presentation formats to counter the effects of such biases.
An availability model of the impact of changes in presentation format on biases and heuristics was constructed based on the findings of a literature review. A six-part laboratory experiment was conducted utilizing a sample of 205 student subjects from the college of business. The independent variable was presentation format which was manipulated by altering the visual salience or visual recency of items of information in a visual computer display. The dependent variables included recall, perceived importance, and the subjects' responses to three judgment tasks.
The results clearly demonstrate that changes in presentation format can be used to alter the impact of cognitive biases on human decision making. The results also provide support for the availability model, with the exception of the proposed influence of learning style. Learning style was found to have no significant impact on decision making whether alone or in combination with changes in presentation format.
The results of this investigation demonstrate that by using our knowledge of cognitive processes (e.g., the visual salience effect, the visual recency effect, and the availability heuristic), presentation formats can be altered in order to moderate the effects of certain biases and heuristics in human decision making. An understanding of these results may be useful in improving DSS design.
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