age-related differences in search strategy and performance when using a data-rich web site
DESCRIPTION
Erica Olmsted-Hawala presented these findings at HCII 2013 in Las Vegas. Data are from a lab-based experimental usability study, in which we showed that older adults have greater difficulties with cognitively challenging tasks. However, even young adults have difficulties with complex data tables that are often found on government Web sites.TRANSCRIPT
1
Age-Related Differences in Search
Strategy and Performance When Using
a Data-Rich Web Site
Erica L. Olmsted-Hawala, U.S. Census Bureau; Jennifer Romano Bergstrom, Fors Marsh Group;
Wendy A. Rogers, Georgia Institute of Technology
HCII July 24, 2013
What We Studied • How adults search for information on a Web site
• Whether age-related differences between younger, middle-age, and older adults actually exist
• Identify any performance or strategy differences
Why?
• Understand the nature
of the difficulties people
have in order to provide
guidance for Web site
design and training
Conclusion Preview
• With a more cognitively challenging search
task, age-related differences are apparent
• Online data tables are difficult for all age
groups
Agenda
Methods
Findings
Conclusions
Agenda
Methods
Findings
Conclusions
Methods
• 61 participants in Metro DC area
• Each session was eye tracked
• Three age groups
– Young adults ages 18-28
– Middle-age adults ages 40-51
– Older adults ages 65-76
• Worked in silence
Internet Experience
Age group Significance
Younger Middle-age Older
Ease in learning to use
new Web sites* 1.5 1.4 2.3 F (2,53)=6.08, p<.01
Ease in using the
Internet* 1.1 1.2 1.4 F (2,53)=2.93, p=.06
*Scale: 1 (Not difficult at all) – 5 (Extremely difficult).
Example Tasks
• Easy task: You want to learn more about Maryland, and specifically about how many people live there. How many people live in Maryland?
• Hard task: You are working on a project that involves work environments in the US, and you are interested in the history of coal mining. How many coal mining companies were in the US in 2007?
Usability Metrics
• Accuracy
– Percent of users who successfully completed
task
• Efficiency
– Mean time to make first click
– Mean time to complete task
• Successful completes only
– Mean number of clicks to complete task
• Successful completes only
Eye-tracking Metrics
• Eye movement patterns in pre-
defined Areas of Interest (AOIs)
• Total number of fixations
– Do participants look at correct
area of the screen?
• Total number of unique visits
– Do participants re-check the
correct answer before deciding it
was correct?
Agenda
Methods
Findings
Conclusions
Hard Task Performance Measure
0 20 40 60 80
Younger
Middle-Age
Older
Accuracy by age group
Accuracy by age group
Efficiency
• Easy task: No age related differences
• Hard task:
– Older adults took longer to make the first click
when initially starting their task
– No age related differences in how long it took
to complete the task
– No age related difference in number of clicks
to the answer page
p<.05
Eye tracking
• Easy task start page – No age-related differences in where participants
looked on main page on AOIs
– No age-related differences in how many times participants re-checked the AOI before making a click
• Easy & Hard task answer page – No age related differences in where participants
looked
– No age related differences in how many times participant re-checked their answer • All participants re-checked!
Agenda
Methods
Findings
Conclusions
Limitations
• Measures were on successful completions
only
• Fewer older adults made it to the correct
answer page (17 younger adults vs 9 older
adults)
• Older adults that made it to the end of the
task may have been higher functioning
than average older adults
Conclusions
• More cognitively challenging tasks indicate
some age related differences
• Number of clicks and time to complete
tasks -- with a larger user group
differences might be apparent
• Eye tracking (as measured by number of
fixations in AOIs) did not differ by age
Future Work
• Additional analyses on eye-tracking
patterns for unsuccessful searchers to
understand their performance difficulties
Future of Data Tables
• Putting complex data tables online appears to cause usability issues for all age groups (they all re-check their answers)
• When displaying complex data online should consider new ways to
visualize
– Simplified interface
– Reduced distracters
– Access to apps