Byrne, Michael D.2020-09-222020-09-222020-082020-09-16August 202Wang, Xianni. "Computational Modeling Reveals How Navigation Strategy and Ballot Layout Lead to Voter Error." (2020) Master’s Thesis, Rice University. <a href="https://hdl.handle.net/1911/109363">https://hdl.handle.net/1911/109363</a>.https://hdl.handle.net/1911/109363Bad ballot design has affected the outcome of multiple elections in the United States. In order to build an automated tool for evaluation of ballots for potential usability problems, a range of voting behaviors on different ballot layouts have to be understood and modeled. The current studies are focussed on full-face paper ballots. Study 1 is an eye-tracking study. The ways that voters seek information on a full-face paper ballot was examined and the insights from the analysis results were integrated into Study 2. Study 2 is a cognitive modeling study. A family of 160 voting strategies were modeled using ACT-R to investigate how errors arise from the interaction of strategy and ballot design. The model was then validated by testing on a well-known bad ballot: the ballot from Kewaunee County, Wisconsin 2002. The Wisconsin error was reproduced successfully.application/pdfengCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.votingballot layoutusabilityACT-Rcomputational modelingThesis2020-09-22