Advertisement

Medium-Fidelity Usability Evaluation for the American Community Survey Website

Using Eye-Tracking Data to Examine Fixation Differences by Task Performance
  • Temika HollandEmail author
  • Erica Olmsted-Hawala
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9175)

Abstract

The American Community Survey (ACS) website provides supplementary information about ACS participation and about ACS data (e.g., data collection, data utilization, survey procedures, etc.). Additionally, the ACS website is a portal to the American Fact Finder (AFF) for access to ACS data. The U.S. Census Bureau is undergoing a new initiative to change the look and feel of Census sites, and various design features have been modified on a web based prototype for the redesigned American Community Survey (ACS) website, including navigational tools and layout. Feedback on whether users of the site would be able to obtain the information they need given the new design features was warranted. The site was tested in its early stages of development using a web-based prototype with limited functionality (i.e., medium-fidelity). Eye tracking was incorporated in the evaluation of the site to gain an in-depth understanding of users’ visual interaction and to add support to observed findings. In addition, differences in eye-fixation duration on Areas of Interest during optimal task performance and non-optimal task performance were explored.

Keywords

Usability Eye tracking Task performance Fixation duration 

References

  1. 1.
    Romano-Bergstrom, J., Olmsted-Hawala, E., Chen, J., Murphy, E.: Conducting iterative usability testing on a web site: challenges and benefits. J. Usability Stud. 7, 9–30 (2011)Google Scholar
  2. 2.
    Frøkjaer, E., Herzum, M., Hornbaek, K.: Measuring usability: are effectiveness, efficiency and satisfaction correlated? In: SIGCHI Conference on Human Factors in Computing Systems, The Haag (2000)Google Scholar
  3. 3.
    Olmsted-Hawala, E., Holland, T., Quach, V.: Usability testing. In: Romano-Bergstrom, J., Schall, A.J. (eds.) Eye Tracking in User Experience Design, pp. 49–80. Morgan Kaufmann, Waltham (2014)CrossRefGoogle Scholar
  4. 4.
    Pan, B., Hembrooke, H.A., Gay, G.L., Granka, L.A., Feusner, M.K., Newman, J.K.: The determinants of web page viewing behavior: an eye-tracking study. In: ETRA 2004: Proceedings of the 2004 symposium on Eye tracking research & applications, pp. 147–154 (2004)Google Scholar
  5. 5.
    Guo, K., Mahmoodi, S., Robertson, R.G.: Longer fixation duration while viewing face images. Exp. Brain Res. 17, 91–98 (2006)CrossRefGoogle Scholar
  6. 6.
    Tobii: User Manual: Tobii studio 1.X User Manual (2008)Google Scholar
  7. 7.
    Poole, A., Ball, L.J.: Eye tracking in human-computer interaction and usability research: current status and future prospects. In: Ghaoui, C. (ed.) Encyclopedia of Human Computer Interaction, pp. 211–219. Idea Group, Hershey (2005)Google Scholar
  8. 8.
    Romano-Bergstrom, J., Olmsted-Hawala, E., Jans, M.E.: Age-related differences in eye tracking and usability performance: website usability for older adults. Int. J. Hum.-Comput. Interact. 29, 541–548 (2013)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.U.S. Census BureauCenter for Survey MeasurementWashington DCUSA

Personalised recommendations