Geographic Information Systems (GIS) enable decision makers to view tabular data geographically, as maps. This simple yet powerful visual format appears to facilitate problem solving, yet how it does so is not clear, nor do we know the types of problems that benefit from this representation. To begin to understand the contributions of geographic representations over tabular representations, we conducted a three-factor experiment in problem solving. The experiment contained two different representations (map and table), three different geographic relationships (proximity, adjacency, and containment), and three levels of task difficulty (low, medium, and high). We found that maps generally produced faster problem solving than tables, and that problem-solving time increased with task difficulty. Most importantly, for the proximity and adjacency geographic relationships we found that maps kept problem-solving time low, while tables tended to increase time dramatically. However, we found that the number of knowledge states for each task explains performance times quite well and is a useful tool for understanding performance differences and interaction effects. As tasks become more difficult, representing them as maps generally keeps the number of knowledge states small, while for tables, the number of knowledge states increases dramatically. Correspondingly, problem-solving times increase dramatically with tables, but not with maps.In sum, as difficulty increases, maps are more effective for problem-solving tasks. Using maps, the tasks are simplified using visual heuristics that keep problemsolving times and error rates from rising as quickly as they do with tables.

This research examines how people make movements with pointing devices during human-computer interaction. It specifically concerns the perceptual-motor processes that mediate the speed and accuracy of cursor positioning with electromechanical mice. In three experiments we investigated the spatial and temporal characteristics of positioning movements made with a mouse, analyzing subjects' speed and accuracy as a function of the types of targets that the movements had to reach. Experiment 1 required rapid and accurate horizontal movements to targets that were vertical ribbons located at various distances from the mouse's starting location. The targets for Experiments 2 and 3, respectively, were vertical lines having various heights and rectangular boxes having various heights and widths. Constraints on movement distance along the primary (that is, horizontal) line of motion had the greatest effects on total positioning times. However, constraints on movement distance along a secondary (vertical) line of motion also affected total positioning times significantly. These effects may be localized in different phases of movements (e.g., movement execution and verification). The duration of movement execution (i.e., physical motion) depends primarily on the target distance, whereas the duration of movement verification (i.e., check for endpoint accuracy) depends primarily on target height and width. A useful account of movement execution is provided by stochastic optimized-submovement models, which have significant implications for designing mice and menu-driven displays.

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This paper reports on an experiment that investigated factors which effect selection time from walking menus and bar or pull-down menus. The primary focus was on the use of impenetrable borders and on expanding target areas on the two menus types. The results show that both factors can be used to facilitate menu selection, with the use of borders being most beneficial. In addition, the results suggest that even on large monitors, the time required to access items from a bar menu is less than that required for the best walking menu.

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