Exploring the Design Space for Adaptive Graphical User Interfaces - - PowerPoint PPT Presentation

▶
exploring the design space for adaptive graphical user
SMART_READER_LITE
LIVE PREVIEW

Exploring the Design Space for Adaptive Graphical User Interfaces - - PowerPoint PPT Presentation

Jun 25, 2023 367 likes •1.43k views

Exploring the Design Space for Adaptive Graphical User Interfaces Krzysztof Gajos (University of Washington) Mary Czerwinski (Microsoft Research) Desney Tan (Microsoft Research) Daniel S. Weld (University of Washington) Scope Graphical

slide-1
SLIDE 1

Exploring the Design Space for Adaptive Graphical User Interfaces

Krzysztof Gajos Mary Czerwinski Desney Tan Daniel S. Weld (University of Washington) (Microsoft Research) (Microsoft Research) (University of Washington)

slide-2
SLIDE 2

Scope

Graphical User Interfaces where the system automatically adapts the presentation of the functionality

slide-3
SLIDE 3

Scope

Graphical User Interfaces where the system automatically adapts the presentation of the functionality The Split Interface

slide-4
SLIDE 4

Scope

Graphical User Interfaces where the system automatically adapts the presentation of the functionality The Moving Interface

slide-5
SLIDE 5

Scope

Graphical User Interfaces where the system automatically adapts the presentation of the functionality The Visual Popout Interface

slide-6
SLIDE 6

Scope

Graphical User Interfaces where the system automatically adapts the presentation of the functionality

slide-7
SLIDE 7

Motivation

slide-8
SLIDE 8

Motivation

slide-9
SLIDE 9

Motivation

slide-10
SLIDE 10

Motivation

They disorient the user!

slide-11
SLIDE 11

Motivation

They disorient the user!

They optimize the UI for the individual!

slide-12
SLIDE 12

Prior Work

slide-13
SLIDE 13

Prior Work

↑ Greenberg and Witten [1985] ↕

Trevellyan and Browne [1987]

↓ Mitchell and Shneiderman [1989] ↑ Sears and Shneiderman [1994] ?

McGrenere, Baecker and Booth [2002]

↓ Findlater and McGrenere [2004] ↔ Tsandilas and shraefel [2005]

slide-14
SLIDE 14

Commercial Deployments

slide-15
SLIDE 15

Commercial Deployments

slide-16
SLIDE 16

Our Goal

Uncover the factors and relationships that influence users’ satisfaction and actual performance when using adaptive UIs

slide-17
SLIDE 17

Road Map

Introduce and motivate the problem Video Experiment 1: qualitative results Experiment 2: quantitative results Synthesis Conclusions

slide-18
SLIDE 18
slide-19
SLIDE 19
slide-20
SLIDE 20

Potential Benefit Potential Disorientation

slide-21
SLIDE 21

Potential Benefit Potential Disorientation

Medium Low

The Split Interface

slide-22
SLIDE 22

Potential Benefit Potential Disorientation

Medium Low High Medium

The Split Interface The Moving Interface

slide-23
SLIDE 23

Potential Benefit Potential Disorientation

Medium Low High Medium Low Low

The Split Interface The Moving Interface The Visual Popout Interface

slide-24
SLIDE 24

Experiment 1

Goal: collect informative subjective data

slide-25
SLIDE 25

Participants

  • 26 volunteers (10 female)
  • aged 25 to 55 (mean=46)
  • moderate to high experience using computers (as

indicated by a validated screener)

  • intermediate to expert users of MS Office (as

indicated by a validated screener)

  • participants received software gratuity
slide-26
SLIDE 26

Tasks

  • Three classes of editing tasks:
  • Flow chart edits
  • Text edits
  • Combined text and graphical edits
slide-27
SLIDE 27

Procedures

slide-28
SLIDE 28

Procedures

Training Start

slide-29
SLIDE 29

Procedures

Training Start Flow Chart task Quotes task Poster task Questionnaire

slide-30
SLIDE 30

Procedures

Training Start Flow Chart task Quotes task Poster task Questionnaire Done 4 conditions? Change Interface

slide-31
SLIDE 31

Procedures

Training Start Flow Chart task Quotes task Poster task Questionnaire Done 4 conditions? Change Interface Final Questionnaire End

slide-32
SLIDE 32

Results: Ranking

Users ranked the Split Interface the highest (p<0.001)

slide-33
SLIDE 33

Results: Ranking

Users ranked the Split Interface the highest (p<0.001)

slide-34
SLIDE 34

1 2 3 4 5 6 7

E a s e

  • f

U s e S a t i s f a c t i

  • n

Unchanging Split Moving Visual Popout

General Satisfaction

slide-35
SLIDE 35

1 2 3 4 5 6 7

E a s e

  • f

U s e S a t i s f a c t i

  • n

Unchanging Split Moving Visual Popout

1 2 3 4 5 6 7

E a s e

  • f

U s e S a t i s f a c t i

  • n

Unchanging Split Moving Visual Popout

General Satisfaction

slide-36
SLIDE 36

1 2 3 4 5 6 7

E a s e

  • f

U s e S a t i s f a c t i

  • n

Unchanging Split Moving Visual Popout

1 2 3 4 5 6 7

E a s e

  • f

U s e S a t i s f a c t i

  • n

Unchanging Split Moving Visual Popout

General Satisfaction

1 2 3 4 5 6 7

E a s e

  • f

U s e S a t i s f a c t i

  • n

Unchanging Split Moving Visual Popout

slide-37
SLIDE 37

1 2 3 4 5 6 7

E a s e

  • f

U s e S a t i s f a c t i

  • n

Unchanging Split Moving Visual Popout

1 2 3 4 5 6 7

E a s e

  • f

U s e S a t i s f a c t i

  • n

Unchanging Split Moving Visual Popout

General Satisfaction

1 2 3 4 5 6 7

E a s e

  • f

U s e S a t i s f a c t i

  • n

Unchanging Split Moving Visual Popout

1 2 3 4 5 6 7

E a s e

  • f

U s e S a t i s f a c t i

  • n

Unchanging Split Moving Visual Popout

slide-38
SLIDE 38

1 2 3 4 5 6 7

E a s e

  • f

U s e S a t i s f a c t i

  • n

Unchanging Split Moving Visual Popout

1 2 3 4 5 6 7

E a s e

  • f

U s e S a t i s f a c t i

  • n

Unchanging Split Moving Visual Popout

General Satisfaction

slide-39
SLIDE 39

Usability

1 2 3 4 5 6 7

D i s c

  • v

e r a b i l i t y S e n s e

  • f

C

  • n

t r

  • l

P r e d i c t a b i l i t y

  • f

a d a p t a t i

  • n

Unchanging Split Moving Visual Popout

1 2 3 4 5 6 7

D i s c

  • v

e r a b i l i t y S e n s e

  • f

C

  • n

t r

  • l

P r e d i c t a b i l i t y

  • f

a d a p t a t i

  • n

Unchanging Split Moving Visual Popout

slide-40
SLIDE 40

Usability

1 2 3 4 5 6 7

D i s c

  • v

e r a b i l i t y S e n s e

  • f

C

  • n

t r

  • l

P r e d i c t a b i l i t y

  • f

a d a p t a t i

  • n

Unchanging Split Moving Visual Popout

1 2 3 4 5 6 7

D i s c

  • v

e r a b i l i t y S e n s e

  • f

C

  • n

t r

  • l

P r e d i c t a b i l i t y

  • f

a d a p t a t i

  • n

Unchanging Split Moving Visual Popout

1 2 3 4 5 6 7

D i s c

  • v

e r a b i l i t y S e n s e

  • f

C

  • n

t r

  • l

P r e d i c t a b i l i t y

  • f

a d a p t a t i

  • n

Unchanging Split Moving Visual Popout

slide-41
SLIDE 41

Subjective Cost and Benefit

slide-42
SLIDE 42
  • Subjective cost

based on:

  • Mental demand
  • Physical Demand
  • Frustration
  • Confusion due to

adaptation

Subjective Cost and Benefit

slide-43
SLIDE 43
  • Subjective cost

based on:

  • Mental demand
  • Physical Demand
  • Frustration
  • Confusion due to

adaptation

  • Subjective benefit

based on:

  • Performance
  • Efficiency due to

adaptation

Subjective Cost and Benefit

slide-44
SLIDE 44
  • Subjective cost

based on:

  • Mental demand
  • Physical Demand
  • Frustration
  • Confusion due to

adaptation

  • Subjective benefit

based on:

  • Performance
  • Efficiency due to

adaptation

Subjective Cost and Benefit

Subjective cost Subjective benefit

Non-adaptive baseline Visual Popout Interface Split Interface Moving Interface

slide-45
SLIDE 45
  • Subjective cost

based on:

  • Mental demand
  • Physical Demand
  • Frustration
  • Confusion due to

adaptation

  • Subjective benefit

based on:

  • Performance
  • Efficiency due to

adaptation

Subjective Cost and Benefit

Subjective cost Subjective benefit

Non-adaptive baseline Visual Popout Interface Split Interface Moving Interface

slide-46
SLIDE 46

User Comments

Split Interface Moving Interface Visual Popout Interface

slide-47
SLIDE 47

User Comments

Split Interface Moving Interface Visual Popout Interface

  • stability
  • semantic

grouping

slide-48
SLIDE 48

User Comments

Split Interface Moving Interface Visual Popout Interface

  • stability
  • semantic

grouping

  • discoverability
slide-49
SLIDE 49

User Comments

Split Interface Moving Interface Visual Popout Interface

  • stability
  • semantic

grouping

  • discoverability
slide-50
SLIDE 50

User Comments

Split Interface Moving Interface Visual Popout Interface

  • stability
  • semantic

grouping

  • discoverability
  • poor

discoverability

slide-51
SLIDE 51

User Comments

Split Interface Moving Interface Visual Popout Interface

  • stability
  • semantic

grouping

  • discoverability
  • poor

discoverability

  • instability
slide-52
SLIDE 52

User Comments

Split Interface Moving Interface Visual Popout Interface

  • stability
  • semantic

grouping

  • discoverability
  • poor

discoverability

  • instability
  • anti-salience
slide-53
SLIDE 53

Road Map

Introduce and motivate the problem Video Experiment 1: qualitative results Experiment 2: quantitative results Synthesis Conclusions

slide-54
SLIDE 54

Experiment 2

Investigate how the accuracy of the adaptive algorithm affects how adaptation is used Collect accurate performance data Goals:

slide-55
SLIDE 55

Participants

  • 8 research colleagues (2 female)
  • aged 25 to 58 (mean=36)
  • high experience using computers
  • expert users of MS Office
  • participants received two meal vouchers as

gratuity

slide-56
SLIDE 56

Tasks

slide-57
SLIDE 57

Tasks

slide-58
SLIDE 58

Tasks

slide-59
SLIDE 59

Tasks

slide-60
SLIDE 60

Tasks

slide-61
SLIDE 61

Procedures

  • Introduction and a brief training on a non-

adaptive version of the interface

  • Each participant used each of the three

interfaces (Unchanging, Split and Moving) at two different accuracy levels (30% and 70%)

slide-62
SLIDE 62

Performance Vs. Adaptation Type

None Split Moving 70 75 80 85 90 95

Completion time (seconds)

slide-63
SLIDE 63

Performance Vs. Adaptation Type

None Split Moving 70 75 80 85 90 95

Completion time (seconds)

slide-64
SLIDE 64

Performance Vs. Adaptation Type

  • Participants were

significantly faster using Split Interface than Non- adaptive baseline (p<0.003)

None Split Moving 70 75 80 85 90 95

Completion time (seconds)

slide-65
SLIDE 65

Performance Vs. Adaptation Type

  • Participants were

significantly faster using Split Interface than Non- adaptive baseline (p<0.003)

None Split Moving 70 75 80 85 90 95

Completion time (seconds)

slide-66
SLIDE 66

Performance Vs. Adaptation Type

  • Participants were

significantly faster using Split Interface than Non- adaptive baseline (p<0.003)

  • Participants were

marginally faster using Moving Interface than Non-adaptive baseline (p<0.073)

None Split Moving 70 75 80 85 90 95

Completion time (seconds)

slide-67
SLIDE 67

Performance Vs. Adaptation Type

  • Participants were

significantly faster using Split Interface than Non- adaptive baseline (p<0.003)

  • Participants were

marginally faster using Moving Interface than Non-adaptive baseline (p<0.073)

None Split Moving 70 75 80 85 90 95

Completion time (seconds)

slide-68
SLIDE 68

Performance Vs. Accuracy

  • Both adaptive

interfaces resulted in faster performance at the higher (70%) accuracy level than at the lower (30%) level (p<0.001)

70 75 80 85 90 95 Split Moving 30% 70% 30% 70%

slide-69
SLIDE 69

Frequency of Use

  • Vs. Accuracy
slide-70
SLIDE 70

Frequency of Use

  • Vs. Accuracy
slide-71
SLIDE 71

Frequency of Use

  • Vs. Accuracy

?

slide-72
SLIDE 72

Frequency of Use

  • Vs. Accuracy

19% 81% 30% accuracy

slide-73
SLIDE 73

Frequency of Use

  • Vs. Accuracy

7% 93% 70% accuracy 19% 81% 30% accuracy

slide-74
SLIDE 74

User Comments

Split Interface Moving Interface

slide-75
SLIDE 75

User Comments

Split Interface Moving Interface

  • discoverability
slide-76
SLIDE 76

User Comments

Split Interface Moving Interface

  • discoverability
  • poor discoverability
slide-77
SLIDE 77

User Comments

Split Interface Moving Interface

  • discoverability
  • poor discoverability
  • instability
slide-78
SLIDE 78

Exploring the Design Space for Adaptive Graphical User Interfaces

slide-79
SLIDE 79

Exploring the Design Space for Adaptive Graphical User Interfaces

slide-80
SLIDE 80

Putting It All Together

slide-81
SLIDE 81

Putting It All Together

Interaction Mechanics stability locality

slide-82
SLIDE 82

Putting It All Together

Algorithm Behavior frequency of adaptation accuracy predictability Interaction Mechanics stability locality

slide-83
SLIDE 83

Putting It All Together

Context interaction frequency task complexity Algorithm Behavior frequency of adaptation accuracy predictability Interaction Mechanics stability locality

slide-84
SLIDE 84

Context interaction frequency task complexity Algorithm Behavior frequency of adaptation accuracy predictability Interaction Mechanics stability locality

Stability

Split Interfaces Moving Interface High stability Low stability User satisfaction

slide-85
SLIDE 85

Context interaction frequency task complexity Algorithm Behavior frequency of adaptation accuracy predictability Interaction Mechanics stability locality

Stability

Split Interfaces Moving Interface MS Smart Menus High stability Low stability User satisfaction

slide-86
SLIDE 86

Context interaction frequency task complexity Algorithm Behavior frequency of adaptation accuracy predictability Interaction Mechanics stability locality

Stability

Split Interfaces Moving Interface MS Smart Menus Visual Popout High stability Low stability User satisfaction

slide-87
SLIDE 87

Locality

  • User comments indicate that, especially for

manual tasks, high locality improves discoverability of adaptation.

Context interaction frequency task complexity Algorithm Behavior frequency of adaptation accuracy predictability Interaction Mechanics stability locality

slide-88
SLIDE 88

Context interaction frequency task complexity Algorithm Behavior frequency of adaptation accuracy predictability Interaction Mechanics stability locality

Adaptation Frequency

↑ Sears and Shneiderman [1994] ↓ Findlater and McGrenere [2004]

Two studies of Split Menus:

slide-89
SLIDE 89

Context interaction frequency task complexity Algorithm Behavior frequency of adaptation accuracy predictability Interaction Mechanics stability locality

Adaptation Frequency

↑ Sears and Shneiderman [1994] ↓ Findlater and McGrenere [2004]

adaptation once per user/session adaptation once per interaction Two studies of Split Menus:

slide-90
SLIDE 90

Context interaction frequency task complexity Algorithm Behavior frequency of adaptation accuracy predictability Interaction Mechanics stability locality

Accuracy

slide-91
SLIDE 91

Context interaction frequency task complexity Algorithm Behavior frequency of adaptation accuracy predictability Interaction Mechanics stability locality

Accuracy

  • Participants performed faster at higher accuracy

levels

(also in [ Tsandilas and schraefel CHI’05])

slide-92
SLIDE 92

Context interaction frequency task complexity Algorithm Behavior frequency of adaptation accuracy predictability Interaction Mechanics stability locality

Accuracy

  • Participants performed faster at higher accuracy

levels

(also in [ Tsandilas and schraefel CHI’05])

  • Participants were more likely to take advantage
  • f adaptation at higher accuracy levels
slide-93
SLIDE 93

Context interaction frequency task complexity Algorithm Behavior frequency of adaptation accuracy predictability Interaction Mechanics stability locality

Accuracy

  • Participants performed faster at higher accuracy

levels

(also in [ Tsandilas and schraefel CHI’05])

  • Participants were more likely to take advantage
  • f adaptation at higher accuracy levels
  • More disorienting interfaces affected more by

reduced accuracy

[ Tsandilas and schraefel CHI’05]

slide-94
SLIDE 94

Predictability

A study in progress!

Context interaction frequency task complexity Algorithm Behavior frequency of adaptation accuracy predictability Interaction Mechanics stability locality

slide-95
SLIDE 95

Context interaction frequency task complexity Algorithm Behavior frequency of adaptation accuracy predictability Interaction Mechanics stability locality

Interaction Frequency

↑ Greenberg and Witten [1985] ↕ Trevellyan and Browne [1987]

Two studies of adaptive deep hierarchical menus:

slide-96
SLIDE 96

Context interaction frequency task complexity Algorithm Behavior frequency of adaptation accuracy predictability Interaction Mechanics stability locality

Interaction Frequency

↑ Greenberg and Witten [1985] ↕ Trevellyan and Browne [1987]

30 interactions per trial 100 interactions per trial:

  • - first 30 positive
  • - last 30 neutral or negative

Two studies of adaptive deep hierarchical menus:

slide-97
SLIDE 97

Task Complexity

Split Interface Moving Interface

  • stability
  • semantic

grouping

  • discoverability
  • poor

discoverability

  • instability

Split Interface Moving Interface

  • discoverability
  • poor

discoverability

  • instability

Experiment 1 Experiment 2

Context interaction frequency task complexity Algorithm Behavior frequency of adaptation accuracy predictability Interaction Mechanics stability locality

slide-98
SLIDE 98

Task Complexity

Split Interface Moving Interface

  • stability
  • semantic

grouping

  • discoverability
  • poor

discoverability

  • instability

Split Interface Moving Interface

  • discoverability
  • poor

discoverability

  • instability

Experiment 1 Experiment 2

Context interaction frequency task complexity Algorithm Behavior frequency of adaptation accuracy predictability Interaction Mechanics stability locality

slide-99
SLIDE 99

Conclusions

slide-100
SLIDE 100

Conclusions

Moving Interface Split Interface Visual Popout

slide-101
SLIDE 101

Conclusions

Moving Interface Split Interface Visual Popout Preferred Disliked [Experiment 1]

slide-102
SLIDE 102

Conclusions

Moving Interface Split Interface Visual Popout Preferred Disliked Faster [Experiment 2]

slide-103
SLIDE 103

Conclusions

Context interaction frequency task complexity Algorithm Behavior frequency of adaptation accuracy predictability Interaction Mechanics stability locality

slide-104
SLIDE 104

Acknowledgments

  • Andrea Bunt, Leah Findlater and Joanna

McGrenere at UBC

  • Members of the

VIBE Group at MSR

slide-105
SLIDE 105

Contact Information

  • Krzysztof Gajos:

kgajos@cs.washington.edu

  • Mary Czerwinski:

marycz@microsoft.com

  • Desney Tan:

desney@microsoft.com

  • Daniel Weld:

weld@cs.washington.edu