The term e-Government refers to providing citizens a series of services that can be conveniently conducted over the Internet. However, the potential to redefine and transform e-Government increasingly relies on citizens successfully establishing and managing a user account profile online. E-Government has not adequately addressed user-centric designs for social inclusion of all citizens on e-Government websites. There is a lack of research on the usability of user account management, and a clear lack of innovation in incorporating user-friendly authentication interfaces to accommodate a diverse user population given the wealth of existing research in web authentication techniques within Identity Management. The problem is e-Government has no standardized approach to evaluate and compare the usability of user account interfaces to accommodate a diverse user population and encourage improvements in making user account interfaces more user-friendly and accessible to citizens online.
This study proposed extending a well-established usability evaluation methodology called GOMS to evaluate e-Government security interfaces for usability. GOMS, which comprises of Goals, Operations, Methods, and Selection, was used to compare the task time users took to complete similar goals on different websites. GOMS was extended to include Security Cases, which are security related goals users desire to accomplish along with the selected link and trail necessary to satisfy those goals.
An observational study was conducted to capture the task time 31 users took to complete similar Security Cases on three popular e-Government websites (DMV.CA.gov, HealthCare.gov, and USPS.com). The study initially defined a catalog of six Security Cases specific to user account management and then established benchmark time predictions for each of the Security Cases using CogTool. The six Security Cases selected were as follows: Registration, Login, Change Settings, Forgot Password, Change Password, and Logout. The task time to complete each of the six Security Case on the three websites, along with statistical analysis and CogTool’s benchmark time predications, were used to quantify and compare the usability of these three websites. In order to capture demographic data and assess participant’s satisfaction using the website, the study conducted a post evaluation survey using the System Usability Scale (SUS). The survey captured age, gender, education, user satisfaction, and computer/security knowledge for each participant to assess design considerations to accommodate a diverse population. Finally, a library of Security Cases was established to compare and highlight the more effective user account interface designs on the three selected e-Government websites.
This study found task time data from similar Security Cases could be categorized and used to successfully compare and highlight more effective user account interface designs. The study revealed gender and education had no distinctions in task time when performing user account management related tasks. The study also revealed seniors took significantly longer than any other age group to complete complex user account management interfaces. Additionally, CogTool did not prove to be effective in establishing reliable task time predictions to establish as benchmarks.
The study concluded the GOMS method could successfully be used to establish a set of task time metrics in a catalog of Security Cases that can be used to evaluate and compare the usability of user account interfaces to accommodate a diverse user population on e-Government websites. Future usability research should be conducted to evaluate if there is a performance relationship between age and security interface complexity. Future research should also further evaluate GOMS as a viable methodology to evaluate other security interfaces not limited to e-Government and expand upon the library of Security Cases to highlight effective security interfaces designs on other websites to accommodate a diverse user population.
| Identifer | oai:union.ndltd.org:nova.edu/oai:nsuworks.nova.edu:gscis_etd-1043 |
| Date | 01 April 2015 |
| Creators | Din, Amran |
| Publisher | NSUWorks |
| Source Sets | Nova Southeastern University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | CEC Theses and Dissertations |
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