In the 2006 U.S. election, it was estimated that over 66 million people would be voting on direct recording electronic (DRE) systems in 34% of the nation's counties [8]. Although these computer-based voting systems have been widely adopted, they have not been empirically proven to be more usable than their predecessors. The series of studies reported here compares usability data from a DRE with those from more traditional voting technologies (paper ballots, punch cards, and lever machines). Results indicate that there were little differences between the DRE and these older methods in efficiency or effectiveness. However, in terms of user satisfaction, the DRE was significantly better than the older methods. Paper ballots also perform well, but participants were much more satisfied with their experiences voting on the DRE. The disconnect between subjective and objective usability has potential policy ramifications.

In the United States, computer-based voting machines are rapidly replacing other older technologies. While there is potential for this to be a usability improvement, particularly in terms of accessibility, the only way it is possible to know if usability has improved is to have baseline data on the usability of traditional technologies. We report an experiment assessing the usability of punch cards, lever machines, and two forms of paper ballot. There were no differences in ballot completion time between the four methods, but there were substantial effects on error rate, with the paper ballots superior to the other methods as well as an interaction with age of voters. Subjective usability was assessed with the System Usability Scale and showed a slight advantage for bubble-style paper ballots. Overall, paper ballots were found to be particularly usable, which raises important technological and policy issues.

Users of modern GUIs routinely engage in visual searches for various control items, such as buttons and icons. Because this is so ubiquitous, it is important that the visual properties of user interfaces support such searches. The current research is aimed at deepening our understanding of how the visual spacing between icons affects visual search times. We constructed an experiment based on previous icon sets [8] where spacing between icons was systematically manipulated, and for which we had a computational cognitive model that predicted performance. In particular, the model predicted that larger spacing would lead to slower search times. While this prediction was borne out, there was an unanticipated finding: users in this new experiment were substantially slower than in previous similar experiments with smaller spacing. In fact, results from this new experiment were better fit with a model that employed a fundamentally different, and less efficient, search strategy. A second experiment was conducted to explicitly test the surprising result that this varied and larger icon spacing would lead to increased search times. Results were consistent with this hypothesis. These results imply that while small differences in visual layout may not intrinsically produce large differences in user performance, they may cause users to adopt suboptimal strategies that do produce such differences.