cognitive abilities and email: impact of interface and task - dissertation presentation 2004.05.06
TRANSCRIPT
2004-05-06
Cognitive Abilities and Email: Impact of Interface and Task
Jacek Gwizdka
Final Oral Examination – 2004-05-06
Interactive Media LabKnowledge Media Design Institute
University of Toronto
www.emailresearch.org
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Outline
•Motivation & Background•Research Questions•Field study•“TaskView” controlled study•“WebTaskMail” controlled study•Contributions•Future Work
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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
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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
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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
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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+3users
Keep in email 8 users
1+1users
4 users
Message arrives
Future info to PIM applications
FS
n =19 users
do task
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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?
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Selected Cognitive AbilitiesWM - working memory:
recall a number of distinct elements for reproductionVM - visual memory:
remember location & orientation of visual informationFC - 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 sessionUI Visual 1st sessionUI Text 2nd sessionUI Visual 2nd session
•Effect UI * Task on time− Header task faster in UI-Text− Date task faster in UI-Visual
Results: UI*TaskS1
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Results – Cognitive AbilitiesS1
•Visual Memory & Task
2nd session: Effect of Task * MV2 on time
0
10
20
30
40
50
Header Date Task
time sec
MV2 lowMV2 high
2nd session: Effect of Task * MV1 on time
0
10
20
30
40
50
Header Date Task
time sec
MV1 lowMV1 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 lowFC high
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Controlled User Study #2S2
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 20Question #
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 20Question #
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 TextUI 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 session2nd 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 session2nd 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 20Question #
time sec
Low WM
High WM
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Results – User Clusters
Factorsdiffering between
clusters
Email Handling ClustersCluster #1 – The Cleanerstransfer pending tasks out of
Cluster #2 – The Keeperskeep 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:
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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
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Acknowledgements
l My academic advisor - Professor Mark Chignelll PhD Committee members: Professors R. Baecker, C.D. Sadleir & E. Tomsl External Examiner: Professor Chris Neuwirthl KMDI l TimeStore: Professor Ron Baecker & Peter Wolfl My colleague - Dr. David Modjeskal Colleagues from Interactive Media Labl Field Study @ Xerox PARC – Dr. Michelle Baldonado, Ken Pier, and othersl This research was financially supported, in part, by NSERC, OGS & BUL