The Help America Vote Act, passed into law in 2002, mandated that all polling places provide privacy and independence to all voters. Given this, many jurisdictions have been forced into making a choice between providing traditional voting methods (such as paper ballots) and offering newer electronic voting systems. Electronic voting machines have been seen as the solution to many usability and accessibility problems, but very little literature exists to indicate whether this is the case among specific populations such as disabled, elderly, and non-English speaking voters. An audio accessible voting interface for visually disabled voters (CHILVote) was designed using specifications from both the Voluntary Voting System Guidelines and a largescale survey of blind individuals conducted by Piner and Byrne [in proceedings of The Human Factors and Ergonomics Society 55th Annual Meeting, pp. 1686-1690 (2011)]. CHILVote’s interface utilizes the given design guidelines and includes use of a male text-to-speech voice, a flexible navigation structure, adjustable speed and volume, and an optional review section. Relatively low error rates (M=1.7%) and high SUS scores (M=89.5) among blind subjects are consistent with previous findings. Error rates and satisfaction are not significantly different than those of sighted voters using both paper and DRE, and blind voters using a non-electronic interface. CHILVote significantly reduced the time it takes for blind subjects to vote, from 25.2 minutes (VotePAD) to 17.1 minutes (CHILVote). This is an improvement, but still over 2.5 times slower than sighted subjects voting on an identical ballot. The integration of accessibility into mainstream technology often has benefits beyond allowing more of the population access to a system. This research provides a comparison point and guidelines for future studies of accessibility solutions.
Identifer | oai:union.ndltd.org:RICE/oai:scholarship.rice.edu:1911/72022 |
Date | 16 September 2013 |
Creators | Piner, Gillian |
Contributors | Byrne, Michael D. |
Source Sets | Rice University |
Language | English |
Detected Language | English |
Type | thesis, text |
Format | application/pdf |
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