age-related differences in search strategy and performance when using a data-rich web site

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

Contact info

Erica L. Olmsted-Hawala

erica.l.olmsted.hawala@census.gov

301-763-4893