Jacek Gwizdka Dissertation: "Cognitive Abilities and Email: Impact of Interface and Task" 2004

1. 2004-05-06
Cognitive Abilities and Email:
Impact of Interface and Task
Jacek Gwizdka
Final Oral Examination – 2004-05-06
Interactive Media Lab
Knowledge Media Design Institute
University of Toronto
jgwizdka@acm.org
www.gwizdka.com
www.emailresearch.org

2. 2004-05-06Jacek Gwizdka
2
Outline
•Motivation & Background
•Research Questions
•Field study
•“TaskView” controlled study
•“WebTaskMail” controlled study
•Contributions
•Future Work

3. 2004-05-06Jacek Gwizdka
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Motivation & Background
•Information overload in email
•Diversity of information in email à diverse task
•Email designed for asynchronous conversations
•Email not designed for:
− file transfer & management;
− contact management;
− maintenance of social image;
− personal information management;
− task and to-do management
MB

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Issues à Research Opportunities
•Handling messages related to pending tasks
problematic
•Effects of email interfaces on behaviour little known
•Role of cognitive abilities in email tasks unexplored
•More evaluation of email interfaces needed
MB

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Research Objectives & Questions
•More efficient processing of task-laden inboxes
•How are messages related to pending tasks handled
in email?
•What are the effects of user interface on email
performance?
•How is user performance affected by cognitive
abilities?
RQ
à Field Study
à Two Controlled Lab Studies

6. 2004-05-06Jacek Gwizdka
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Field Study – Findings
• Pending tasks kept in email
• User actions compensate for “missing” functionality
(e.g. email to self to keep important tasks on top of inbox)
• Individual differences :
read msg
msg
after task
delay
Transfer out of email
& Delete
Transfer out of email
& Keep in email
Keep Delete
7 users
7+3
users
Keep in email 8 users
1+1
users
4 users
Message arrives
Future info to
PIM applications
FS
n =19 users
do
task

7. 2004-05-06Jacek Gwizdka
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Controlled User Study #1
• User tasks – information finding :
− Header task (H) & Date task (D)
• What are effects of TaskView representation of pending tasks
on user performance?
• What are effects of cognitive abilities on user performance?
S1
UI-­”Text” – OutlookUI-­”Visual” – TaskView
• How can handling of “future” messages be made more efficient?

8. 2004-05-06Jacek Gwizdka
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Selected Cognitive Abilities
WM - working memory:
recall a number of distinct elements for reproduction
VM - visual memory:
remember location & orientation of visual information
FC - flexibility of closure:
extract information from distractive background
S1

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UI * TASK -­> time for 1st & 2nd session
0
10
20
30
40
50
Header Date Task
time sec
UI Text 1st session
UI Visual 1st session
UI Text 2nd session
UI Visual 2nd session
•Effect UI * Task on time
− Header task faster in UI-Text
− Date task faster in UI-Visual
Results: UI*Task
S1

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Results – Cognitive Abilities
S1
•Visual Memory & Task
2nd session: Effect of Task * MV2 on time
0
10
20
30
40
50
Header Date Task
time sec
MV2 low
MV2 high
2nd session: Effect of Task * MV1 on time
0
10
20
30
40
50
Header Date Task
time sec
MV1 low
MV1 high
`

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Results – Cognitive Abilities (cont’d)
S1
•Flexibility of Closure & UI * Task
2nd session: Effect of UI * FC on time for Date task
0
10
20
30
40
50
UI-­Text UI-­Visual UI
time sec
FC low
FC high

12. 2004-05-06Jacek Gwizdka
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Controlled User Study #2
S2
UI-­”Visual” UI-­”Text”
• Redesigned interface – WebTaskMail
• User tasks: Header, Date & Mixed

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Results – Subjective Preferences
•UI-Visual easier to use than UI-Text
•UI-Visual preferred for:
− handling to-do's & events
− overview of pending tasks

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Results – UI Learning (1st session)
Learning curve for UI-­Text
00:00
00:10
00:20
00:30
00:40
00:50
01:00
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Question #
time sec Learning curve for UI-­Visual
00:00
00:10
00:20
00:30
00:40
00:50
01:00
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Question #
time sec
S2
• Learning effect - both UIs
• Difference low/high working memory in UI-Visual
Low WM
High WM
Low WM High WM

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2nd session: Effect of UI * Task on time
00:00
00:10
00:20
00:30
00:40
00:50
Header Date Mixed Task
time sec
UI Text
UI Visual
Results –UI*Task
•Effect UI * Task on time
for 2nd session
− UI-Text = UI-Visual on Header task
− UI-Visual faster on Date task
− UI-Text faster on Mixed task
S2

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WM: short-term store & attention control
− Learning
− Interaction
− Performance time
Results – Roles of Working Memory
Effect of Working Memory on time
00:00
00:10
00:20
00:30
00:40
00:50
WM low WM high
time sec
1st session
2nd session
S2
Effect of Working Memory on sorting
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
WM low WM high
sort/Q
1st session
2nd session
Learning curve for UI-­Visual
00:00
00:10
00:20
00:30
00:40
00:50
01:00
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Question #
time sec
Low WM
High WM

17. 2004-05-06Jacek Gwizdka
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Results – User Clusters
Factors
differing between
clusters
Email Handling Clusters
Cluster #1 – The Cleaners
transfer pending tasks out of
email
Cluster #2 – The Keepers
keep pending tasks
in email
Flexibility of Closure low high
S2
• Two Email Handling Clusters (à Field study)
1) Transfer pending tasks (7 users)
2) Keep pending tasks (16 users)
• Differences between clusters:

18. 2004-05-06Jacek Gwizdka
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Contributions - 1
•Effects of cognitive factors on email tasks
− Effects at different interaction stages
– WM à learning & task performance
– FC & VM à task performance
− Different performance & interaction measures affected
– WM & FC à time, WM & VM à sorting, VMà scrolling
− Opposite direction of effects
– WM & VM on sorting
− Multiple roles of working memory in interaction
CO

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Contributions - 2
•Understanding differences in behaviour
− In email handling :
flexibility of closure & email experience
− In “interaction effort” :
cognitive abilities (CS, WM, VM) & email experience
•Methodological contributions
− Developed email reference task and metrics
− Demonstrated the effects of tasks on performance
CO

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Possible Future Work
•Narrow down role of cognitive abilities
− eye-tracker & working memory
•Field studies
•UI design
− personalized and adaptive UI
FU

21. 2004-05-06Jacek Gwizdka
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Acknowledgements
l My academic advisor - Professor Mark Chignell
l PhD Committee members: Professors R. Baecker, C.D. Sadleir & E. Toms
l External Examiner: Professor Chris Neuwirth
l KMDI
l TimeStore: Professor Ron Baecker & Peter Wolf
l My colleague - Dr. David Modjeska
l Colleagues from Interactive Media Lab
l Field Study @ Xerox PARC – Dr. Michelle Baldonado, Ken Pier, and others
l This research was financially supported, in part, by NSERC, OGS & BUL