User Interface Design

1. May 18, 2010 IAT 334 1
IAT 334
Interface Design
Chris Shaw
______________________________________________________________________________________
SCHOOL OF INTERACTIVE ARTS + TECHNOLOGY [SIAT] | WWW.SIAT.SFU.CA

2. May 18, 2010 IAT 334 2
Exam Materials
 Slides
 Shneiderman & Plaisant Chapters 1-8
 Programming materials
– Supplemantary: Glassner Book
• Chapters 1-5,
• Chapters 10.2, 13.1-13.6
– On Sakai: Password: GlassnerIAT334

3. May 18, 2010 IAT 334 3
Why We Are Here
 Look at human factors that affect
software design and development
 Central Topic: User interface design

4. May 18, 2010 IAT 334 4
HCI
 What happens when a human and a computer
get together to perform a task
– Task
• Write a document
• Plan a budget
• Design a presentation
• Play a video game
– Not a task..
• Goof off (obviously)

5. May 18, 2010 IAT 334 5
Why is this important?
 Computers (in one way or another) affect
every person in society
– Increasing % use computers in work, at
home in the road…
 Product success depends on ease of use

6. May 18, 2010 IAT 334 6
Course Aims
 Consciousness raising for you
– Eg. Don Norman
• “The Design of Everyday Things”
– Doors
• Handles afford various opening method
 Design critic

7. May 18, 2010 IAT 334 7
Goals of HCI
(Shneiderman & Plaisant Chap1)
 Allow users to carry out tasks
– Safely
– Effectively
– Efficiently
– Enjoyably

8. May 18, 2010 IAT 334
Goals of System Engineering
Functionality
• Tasks and sub-tasks to be carried out
Reliability
• Maintaining trust in the system
Standardization, integration, consistency and
portability
Schedules and budgets
• Adhering to timelines and expense
• Human factors principles and testing reduces costs

9. May 18, 2010 IAT 334 9
Usability
 Five Measurable Goals of UI Design
 Combination of
– Ease of learning
– High speed of user task performance
– Low user error rate
– Subjective user satisfaction
– User retention over time

10. May 18, 2010 IAT 334
Life-critical systems: air traffic control, emergency, power utilities
etc.
• high reliability, error-free performance, lengthy training for
systems, subjective satisfaction less of an issue
Industrial and commercial uses: banking, inventory management,
airline and hotel reservations, etc.
• low costs is critical over reliability, ease of learning, errors
calculated against costs, subjective satisfaction of modest
importance
Interests in Human Factors
in Design

11. Sept14, 2009 IAT 334
Office, home, entertainment: productivity and entertainment
applications
• ease of learning, low error rates, subjective satisfaction are
paramount since use is discretionary and competition is fierce.
Range of types of users from novice to expert.
Exploratory, creative, and cooperative: web-based, decision-
making, design-support, collaborative work, etc.
• users knowledgeable in domain but vary in computer skills, direct-
manipulation using familiar routines and gestures work best,
difficult systems to design and evaluate.
Interests in Human Factors
in Design

12. May 18, 2010 IAT 334
Accommodating
Human Diversity
Physical
Abilities and
Workplaces
Cognitive
and Perceptual
Abilities
Personality
Differences
Cultural
and International
Diversity
Users with
Disabilities
Elderly
Users

13. May 18, 2010 IAT 334 13
Key Historical Event
 Design of the first Mac 1983-1984
 “The computer for the rest of us”

14. May 18, 2010 IAT 334 14
Improving Interfaces
 Know the User!
– Physical abilities
– Cognitive abilities
– Personality differences
– Skill differences
– Cultural diversity
– Motivation
– Special needs

15. May 18, 2010 IAT 334 15
Two Crucial Errors
 Assume all users are alike
 Assume all users are like the designer

16. Another Crucial Error
 Have the user design it!
 Users bring vital knowledge to design:
– They know a lot about the problem
– They know a lot about the current tools
– They typically know very little about design
May 18, 2010 IAT 334 16

17. May 18, 2010 IAT 334 17
UI Design/Develop Process
 Analyze user’s goals
 Create design alternatives
 Analyze designs
 Implement prototype
 Test
 Refine
Design
Evaluate Implement

18. May 18, 2010 IAT 334 18
Evaluation
 Things we can measure
– Time to learn
– Speed of performance
– Rate of errors by user
– Retention over time
– Subjective satisfaction

19. May 18, 2010 IAT 334 19
Interfaces in the World
 VCR
 Mouse
 Phone
 Copier
 Car
 Airline reservation
 Air traffic control

20. May 18, 2010 IAT 334 20
History of HCI
______________________________________________________________________________________
SCHOOL OF INTERACTIVE ARTS + TECHNOLOGY [SIAT] | WWW.SIAT.SFU.CA

21. May 18, 2010 IAT 334 21
Ivan Sutherland
 SketchPad - ‘63 PhD thesis at MIT
– Hierarchy - pictures & subpictures
– Master picture with instances
– Constraints
– Icons
– Copying
– Light pen as input device
– Recursive operations

22. May 18, 2010 IAT 334 22
Douglas Engelbart
 Invented the mouse
 Landmark system/demo:
– hierarchical hypertext, multimedia, mouse,
high-res display, windows, shared files,
electronic messaging, CSCW,
teleconferencing, …
 http://www.youtube.com/watch?v=JfIgzSoTMOs

23. May 18, 2010 IAT 334
The Mouse
source: resonancepub.com & brittanica.com
Doug Engelbart’s mouse - 1963-64

24. May 18, 2010 IAT 334 24
Alan Kay
 Dynabook - Notebook sized computer
loaded with multimedia and can store
everything
 Personal Computing
 Desktop Interface

25. May 18, 2010 IAT 334 25
PCs with GUIs
 Xerox PARC - mid 1970’s
– Alto
– Local processor, Bitmap display, Mouse
– Precursor to modern GUI
– LAN - Ethernet

26. May 18, 2010 IAT 334
Menus
source: folklore.org
Bill Atkinson’s Polaroids of the first pull-down menu prototype - circa 1979

27. May 18, 2010 IAT 334 27
Xerox Star - ‘81
 First commercial PC designed for
“business professionals”
– Desktop metaphor, pointing, WYSIWYG
 First system based on usability
engineering

28. Windows 95
May 18, 2010 IAT 334 28

29. Handhelds
 Portable computing + phone
 Newton, Palm, Blackberry, iPhone
May 18, 2010 IAT 334 29

30. May 18, 2010 IAT 334 30
Human Capabilities
 Want to improve user performance
 Know the user!
– Senses
– Information processing systems

31. May 18, 2010 IAT 334 31
Senses
 Sight, hearing, touch important for
current HCI
– smell, taste ???

32. May 18, 2010 IAT 334 32
Sight
 Visual System workings
 Color - color blindness: 8% males,
1% females
 Much done by context & grouping
(words, optical illusions, …)

33. May 18, 2010 IAT 334 33
Hearing
 Often taken for granted how good it is
– Pitch - frequency
– Loudness - amplitude
– Timbre - type of sound (instrument)
 Sensitive to range 20Hz - 22000Hz
 Limited spatially, good temporal
performance

34. May 18, 2010 IAT 334 34
Touch
 Three main sensations handled by
different types of receptors:
– Pressure (normal)
– Intense pressure (heat/pain)
– Temperature (hot/cold)
 Where important?

35. May 18, 2010 IAT 334 35
Models of Human Performance
 Predictive
 Quantitative
– Time to perform
– Time to learn
– Number and type of errors
– Time to recover from errors
 Approximations

36. May 18, 2010 IAT 334 36
Basic HCI
 Model Human Processor
– A simple model of human cognition
– Card, Moran, Newell 1983
 Components:
– Senses
– Sensory store
– Short-term memory
– Long-term memory
– Cognition

37. May 18, 2010 IAT 334 37
Information Processing
 Usually serial action
– Respond to buzzer by pressing button
 Usually parallel recognition
• Driving, reading signs, listening to radio

38. May 18, 2010 IAT 334 38
Model Human Processor
Basics
 Parameters
– Processors cycle time of 50-200ms
– Memories have type, capacity, decay time
 Types
– Visual
– Auditory
– Tactile
– Taste, smell, proprioception, etc

39. May 18, 2010 IAT 334 39
Model Picture Closeup

40. May 18, 2010 IAT 334 40
Perceptual Processor
 Continually “grabs data” from the sensory
system
 Cycle time: 100ms [50 - 200] ms
 Passes data to Image Store in
unrecognized form
– “Array of Pixels” (or whatever it is) from eyes
– “Sound Intensities” from ears

41. May 18, 2010 IAT 334 41
Sensory Store
 The “input buffer” of the senses
 Stores most recent input unrecognized
 Storage time and capacity varies by type
– Visual: NominalRange
• Capacity: 17letters of text [7 - 17] letters
• Decay Time: 200ms [70 - 1000] ms
– Audio:
• Capacity: 5 letters of text [4.4-6.6] letters
• Decay Time: 1500 ms [900 - 3500] ms

42. May 18, 2010 IAT 334 42
Memory
 Three “types”
– Short-term memory
Conscious thought, calculations
– Intermediate
Storing intermediate results, future plans
– Long-term
Permanent, remember everything ever
happened to us

43. May 18, 2010 IAT 334 43
Memory: Sort Term
 Short Term (Working) Memory (WM)
– Gets basic recognition from Sensory Store
• “Stop sign” vs. “red octagon w/white marks”
– 7 +/- 2 “chunks”
• 4048946328 vs. 404-894-6328
– WM: NominalRange
• Capacity: 7 chunks [5 - 9] chunks
• Decay Time: 7 seconds [5 - 226] seconds
• Access Time: 70ms [25 - 170] ms

44. May 18, 2010 IAT 334 44
Memory: Long Term
 Long Term Memory (LTM)
– “Unlimited” size
– Slower access time (100ms)
– Little decay
– Episodic & Semantic
 Why learn about memory?
– Know what’s behind many HCI techniques
– Predict what users will understand

45. May 18, 2010 IAT 334 45
LT Memory Structure
 Episodic memory
– Events & experiences in serial form
 Semantic memory
– Structured record of facts, concepts & skills

46. May 18, 2010 IAT 334 46
Read the colors of the words
Black Red
Orange Yellow
Blue

47. May 18, 2010 IAT 334 47
MHP Operation
 Recognize-Act Cycle
– On each cycle, contents in WM initiate actions
associatively linked to them in LTM
– Actions modify contents of WM
 Discrimination Principle
– Retrieval is determined by candidates that
exist in memory relative to retrieval cues
– Interference by strongly activated chunks

48. May 18, 2010 IAT 334 48
Perception
Stimuli that occur within one PP cycle fuse into a
single concept
– movies (frame rate)
• Frame rate > 1 / Tp = 1/(100 msec/frame) = 10 f/sec
– morse code listening rate
Perceptual causality
– two distinct stimuli can fuse if the first event appears
to cause the other
– events must occur in the same cycle

49. May 18, 2010 IAT 334 49
Operation
 Variable Cognitive Processor Rate
– Cognitive Processor cycle time Tc is shorter
with greater effort
– Induced by increased task
demands/information
– Decreases with practice

50. May 18, 2010 IAT 334 50
Operation: Target finding
 Task: Move hand to target area
 Fitts Law
– A series of microcorrections
• Correction takes Tp + Tc + Tm
– Time Tpos to move hand to target width W
which is distance D:
• Tpos = a + b log2 (d/w + 1.0)
– Movement time depends on relative precision

51. Jan 13, 2011 IAT 334 51
IAT 334
Interface Design
Task Analysis
______________________________________________________________________________________
SCHOOL OF INTERACTIVE ARTS + TECHNOLOGY [SIAT] | WWW.SIAT.SFU.CA

52. Jan 13, 2011 IAT 334 52
Task Conformance
 Task coverage
– Can system do all tasks of interest?
 Task adequacy
– Can user do tasks?
– Does system match real-world tasks?

53. Jan 13, 2011 IAT 334 53
Task Analysis
 Analyzing how people do their jobs
– Go to their environment
– Learn about, analyze and describe their tasks
 Examine users’ tasks to better understand
what they need from interface and how
they will use it

54. Task Analysis
 Gather data about what users need to do
or accomplish
…then…
 Represent data for interpretation and use
in design decisions
Jan 13, 2011 IAT 334 54

55. Information to be Gathered
 Information about users
 Description of environment
– where the tasks will be performed
 Major goals of the job
– what will result in a successful end state?
 User preferences & needs
– before they even start: coffee, pen,
notebook, log sheets…
Jan 13, 2011 IAT 334 55

56. Jan 13, 2011 IAT 334 56
Task Analysis
 Broad Focus
 Observe users of current system(s)
 Generate requirements
– Hierarchical task analysis
– Knowledge-based task analysis
– Entity-Relationship model

57. Data Gathering Techniques
1. Observation
2. Interviews & Contextual Inquiry
3. Ethnography
also…
4. Surveys & Questionnaires
5. Focus Groups & Expert Debriefing
6. Competitive Product Review
7. Documentation mining
8. Data logging
Jan 13, 2011 IAT 334 57

58. Information to be Gathered
 Tasks & Subtasks:
– Physical
– Cognitive
– Communication
 Conditions under which these tasks are done
 Results/outcomes of tasks
 Requirements to perform task:
– Information
– Communication with others
– Equipment
Jan 13, 2011 IAT 334 58

59. 1. Observation
 Watch users do what they do
– Typically from a distance
 Record with videotape
– May require coding video later
 Take lots of notes, sketches
 Focus on specific task-relevant behaviors
in notes, but later convert to abstract
subtasks
Jan 13, 2011 IAT 334 59

60. 2. Interviews
 Engage the user more than just watching
 Structured interviews
– Efficient, but requires training
 Unstructured
– Inefficient, but requires no training
 Semi-structured
– Good balance
– Often appropriate
Jan 13, 2011 IAT 334 60

61. 3. Ethnography
 Deeply contextual inquiry
– “Wallow in the data”
 “Live among” the users
 Understanding the full complexity of
behavior, in its complete social context
 Note: Techniques based in sociology and
anthropology--the study of humans
Jan 13, 2011 IAT 334 61

62. 4. Surveys & Questionnaires
 Subjective answers in a quantitative format
– What does this mean?
 Questions:
– Exploratory vs. confirmatory
– Open-ended vs. categorical (exhaustive)
– NB: If you ask it, use it. If you won’t/can’t use it,
don’t ask it.
Jan 13, 2011 IAT 334 62

63. 5. Focus Groups
 Structured Interview with groups of individuals
– 3 to 10 persons
– Use several different groups with different roles or
perspectives
– Manage the interaction
• Avoid few people dominating the discussion
 Focus on preferences and views, not
performance
 Relatively low cost, quick way to learn a lot
 Audio or video record, with permission
Jan 13, 2011 IAT 334 63

64. 6. Competitive Products
 Looking for both good and bad ideas
– Functionality
– UI style
 Why are they successful or unsuccessful?
 What does successful really mean?
– (Note: Successful does not equal usable)
Jan 13, 2011 IAT 334 64

65. 7. Document Mining
 Documentation
– Often contains description of how the tasks
should be done
– Standards docs
– Manuals
– Histories
– Best Practices
Jan 13, 2011 IAT 334 65

66. 8. Data Logging
 Automatically tracking:
– Keystroke/mouse clicks
– Timers
– Logs of transactions
– Physical location/movement trackers
• Cell phones
• GPS
Jan 13, 2011 IAT 334 66

67. Now that you have observed…
 You have piles of notes, hours of video,
surveys up to here…
 How can you digest and represent the
data, to turn it into information?
Jan 13, 2011 IAT 334 67

68. Describe Tasks
1. Task Outlines
2. Narratives
3. Hierarchies & Network Diagrams
– Hierarchical Task Analysis (HTA)
– Entity-Relationship Diagrams
4. Flow Charts
5. Card Sorting
Jan 13, 2011 IAT 334 68

69. 1. Task Outline
Using a lawnmower to cut grass
Step 1. Examine lawn
a. Make sure grass is dry
b. Look for objects laying in the grass
Step 2. Inspect lawnmower
a. Check components for tightness
1) Check that grass bag handle is securely fastened to the grass bag support
2) Make sure grass bag connector is securely fastened to bag adaptor
3) Make sure that deck cover is in place
4) Check for any loose parts (such as oil caps)
5) Check to make sure blade is attached securely
b. Check engine oil level
1) Remove oil fill cap and dipstick
2) Wipe dipstick
3) Replace dipstick completely in lawnmower
4) Remove dipstick
5) Check that oil is past the level line on dipstick
Jan 13, 2011 IAT 334 69

70. 2. Narratives
 Describe tasks in sentences
 Often expanded version of task outline
 More effective for communicating general
idea of task
 Not effective for details
 Not effective for branching tasks
 Not effective for parallel tasks
Jan 13, 2011 IAT 334 70

71. 3. Hierarchies & Networks
 Hierarchical Task Analysis (HTA)
– Graphical notation & decomposition of tasks
– Tasks as sets of actions
– Tasks organized into plans (describes sequence)
 Network / Entity-Relationship Diagrams
– Objects/people with links to related objects
– Links described functionally and in terms of strength
Jan 13, 2011 IAT 334 71

72. 4. Flow Charts
 Flow Chart of Task Steps
– Combines Entity-relationship (network) with
sequential flow, branching, parallel tasks.
– Includes actions, decisions, logic, by all
elements of the system
– Abstracted
– Mature, well-known, good tools
Jan 13, 2011 IAT 334 72

73. Jan 13, 2011 IAT 334 73
5. Knowledge-based
Analysis
 List all objects and actions involved in a
task, then build a taxonomy of them
 Often times, work with domain expert to
get help

74. Summary:
Data Gathering Techniques
1. Observation
2. Interviews & Contextual Inquiry
3. Ethnography
also…
4. Surveys & Questionnaires
5. Focus Groups & Expert Debriefing
6. Competitive Product Review
7. Documentation mining
8. Data logging
Jan 13, 2011 IAT 334 74

75. Summary:
Describe Tasks
1. Task Outlines
2. Narratives
3. Hierarchies & Network Diagrams
– Hierarchical Task Analysis (HTA)
– Entity-Relationship Diagrams
4. Flow Charts
5. Card Sorting
Jan 13, 2011 IAT 334 75

76. Jan 20, 2011 IAT 334 76
UI Design Principles
 Categories
– Learnability
• support for learning for users of all levels
– Flexibility
• support for multiple ways of doing tasks
– Robustness
• support for recovery
 Always think about exceptions, suitability

77. Jan 20, 2011 IAT 334 77
Learnability Principles
 Predictability
 Synthesizability
 Familiarity
 Generalizability
 Consistency

78. Jan 20, 2011 IAT 334 78
Predictability
 I think that this action will do…
 Operation visibility - can see avail actions
– e.g. menus vs. command shell
– grayed menu items

79. Jan 20, 2011 IAT 334 79
Synthesizability
 From the resulting system state, My
previous action did…
– compare in command prompt vs UI
– same feedback needed for all users, all apps?

80. Jan 20, 2011 IAT 334 80
Familiarity
 Does UI task relate real-world task or
domain knowledge?
– to anything user is familiar with?
– Use of metaphors
• pitfalls
– Are there limitations on familiarity?

81. Jan 20, 2011 IAT 334 81
Generalizability
 Does knowledge of one UI apply to
others?
– Cut and paste in many apps
 Does knowledge of one aspect of a UI
apply to rest of the UI?
– File browsers in MacOS/ Windows
 Aid: UI Developers guidelines

82. Jan 20, 2011 IAT 334 82
Consistency
 Similar ways of doing tasks
– interacting
– output
– screen layout
 Is this always desirable for all systems, all
users?

83. Jan 20, 2011 IAT 334 83
Flexibility Principles
 Dialog Initiative
 Multithreading
 Task migratibility
 Substitutivity
 Customizability

84. Jan 20, 2011 IAT 334 84
Dialog Initiative
 System pre-emptive
– system does all prompts, user responds
• sometimes necessary
• Eg. Bank machine
 User pre-emptive
– user initiates actions
• more flexible

85. Jan 20, 2011 IAT 334 85
Multithreading
 Two types
– Concurrent
• input to multiple tasks simultaneously
– Interleaved
• many tasks, but input to one task at a time

86. Jan 20, 2011 IAT 334 86
Task migratability
 Ability to move performance of task to
entity (machine or person) that can do it
better
– Eg. Autopilot
– Spellchecking
– When is this good? Bad?

87. Jan 20, 2011 IAT 334 87
Substitutivity
 Flexibility in details of operations
– Allow user to choose suitable interaction
methods
– Allow different ways to
• perform actions
• specify data
• configure
– Allow different ways of presenting output
• to suit task, user

88. Jan 20, 2011 IAT 334 88
Customizability
 Ability to modify interface
– By user - adaptability
– By system - adaptivity

89. Jan 20, 2011 IAT 334 89
Robustness Principles
 Observability
 Recoverability
 Responsiveness
 Task Conformance

90. Jan 20, 2011 IAT 334 90
Observability
 Can user determine internal state of
system from observable state?
– Browsability
• explore current state (without changing it)
– Reachability
• navigate through observable states
– Persistence
• how long does observable state persist?

91. Jan 20, 2011 IAT 334 91
Recoverability
 Ability to continue to a goal after
recognizing error
• Difficulty of Recovery procedure should relate to
difficulty of original task
– Forward Recoverability
• ability to fix when we can’t undo?
– Backward Recoverability
• undo previous error(s)

92. Jan 20, 2011 IAT 334 92
Responsiveness
 Rate of communication between user and
system
– Response time
• time for system to respond in some way to user
action(s)
– Stability principle
• response time, rate should be consistent
– As computers have gotten better, required
computer response has gotten shorter

93. Jan 20, 2011 IAT 334 93
Task Conformance
 Task coverage
– can system do all tasks of interest?
 Task adequacy
– Can user do tasks?
– Does system match real-world tasks?

94. Feb 3, 2011 IAT 334 94
IAT 334
Interface Design
User Centered Design
Metaphor
Models
Practice
______________________________________________________________________________________
SCHOOL OF INTERACTIVE ARTS + TECHNOLOGY [SIAT] | WWW.SIAT.SFU.CA

95. Feb 3, 2011 IAT 334 95
Agenda
 User Centered Design -- Overall Process
 Design
– Metaphors
– Mental Models
– Idea generation
 Design principles
 Displaying your designs
– Storyboards
– Lo-Fi
– Wizard of Oz
– Visual Basic, Flash, etc

96. Feb 3, 2011 IAT 334 96
User-Centered Design
 User-centered design process
– Analysis of user needs
– Prototype
– Informal feedback
– Iterate on design
– Final application
– Formal feedback

97. Feb 3, 2011 IAT 334 97
Analysis of User Needs
 Techniques:
– Surveys
– Card-sorting tasks
– Interviews
– Focus groups
• Look at competing products
– Ethnography
• Participant observation

98. Feb 3, 2011 IAT 334 98
Prototyping
 Storyboards
 Paper simulations of application
 Wizard of Oz experiment
 Prototyping tools
 Cheap!

99. Feb 3, 2011 IAT 334 99
Informal Feedback
 Present prototype to users
 Do a quick questionnaire
 Observe the user struggle with your lousy
design

100. Feb 3, 2011 IAT 334 100
Iterate on Design
 Redesign system
– in light of initial user impressions
– pay attention to common complaints
 Be prepared to abandon bad ideas!!
 It’s just an idea, not a measure of your
worth!

101. Feb 3, 2011 IAT 334 101
Idea Creation
 Ideas come from
– Imagination
– Analogy
– Observation of current
practice
– Observation of current
systems
 Borrow from other
fields
– Animation
– Theatre
– Information displays
– Architecture
– ...
How do we create and develop new interface
ideas and designs?

102. Feb 3, 2011 IAT 334 102
Interface Metaphors
 Metaphor - Application of name or
descriptive term to another object which
is not literally applicable
– Use: Natural transfer - apply existing
knowledge to new, abstract tasks
– Problem: May introduce incorrect mental
model

103. Feb 3, 2011 IAT 334 103
Mental Models
 What models of the world are the users
using?
 Two Classes:
 Functional model
– “Press the accelerator once, then turn the
key”
 Structural model
– OK, why do we do that?

104. Feb 3, 2011 IAT 334 104
Another example...
 Functional model
– “Go north on King George, Cross the Pattullo, Turn
left at 10th Ave, Turn right at Kingsway, go 4.5km”
 Structural model
– What location??

105. Feb 3, 2011 IAT 334 105
Idea Creation
 Methods for creating and developing
interface ideas
– Turn off your natural critique mechanism!
– ?

106. Feb 3, 2011 IAT 334 106
Idea Creation Methods
 1. Consider new use for object
 2. Adapt object to be like something else
 3. Modify object for a new purpose

107. Feb 3, 2011 IAT 334 107
Idea Creation Methods
 4. Magnify - add to object
 5. Minimize - subtract from object
 6. Substitute something similar

108. Feb 3, 2011 IAT 334 108
Idea Creation Methods
 7. Rearrange aspects of object
 8. Change the point of view
 9. Combine data into an ensemble

109. Feb 3, 2011 IAT 334 109
Guidelines for Design
 1. Provide a good conceptual model
– User has mental model of how things work
– Build design that allows user to predict
effects of actions
 2. Make things visible
– Visible affordances, mappings, constraints
– Remind person of what can be done and how
to do it

110. Feb 3, 2011 IAT 334 110
Design Principles
 1. Use simple and natural dialog in user’s
language
– Match user’s task in a natural way
– Avoid jargon, techno-speak
– Present exactly info that user needs
• Less is more!

111. Feb 3, 2011 IAT 334 111
Design Principles
 Here are 10 more detailed principles to
follow about what to design and why

112. Feb 3, 2011 IAT 334 112
Design Principles
 2. Strive for consistency
– Sequences, actions, commands, layout,
terminology
– Makes more predictable
– Dialog boxes all having same “closure”
options

113. Feb 3, 2011 IAT 334 113
Design Principles
 3. Provide informative feedback
– Continuously inform user about what is
occurring
– Most important on frequent, substantive
actions
• % in file
– How to deal with delays?
• Special cursors
• % Done graphs

114. Feb 3, 2011 IAT 334 114
Design Principles
 4. Minimize user’s memory load
– Recognition is better than recall
• Make visible!
– Describe required input format, include
example and default
• Date: _ _ - _ _ - _ _ (DD-MM-YY)
– Use small # of generally applicable cmds

115. Feb 3, 2011 IAT 334 115
Design Principles
 5. Permit easy reversal of actions
– Undo!
– Reduces anxiety, encourages experimentation

116. Feb 3, 2011 IAT 334 116
Design Principles
 6. Provide clearly marked exits
– Don’t want the user to feel trapped
– Examples
• Cancel button on dialogs
• Quit any time
• Interrupt/resume on lengthy operations

117. Feb 3, 2011 IAT 334 117
Design Principles
 7. Provide shortcuts
– Enable frequent users to perform often-used
operations quickly
• Keyboard & mouse
– Abbreviations
– Menu shortcuts
– Function keys
– Command completion
– Double click vs. menu selection
• Navigation between windows/forms
• Reuse
– Provide a history system

118. Feb 3, 2011 IAT 334 118
Design Principles
 8. Support internal locus of control
– Put user in charge, not computer
– Can be major source of anxiety

119. Feb 3, 2011 IAT 334 119
Design Principles
 9. Handle errors smoothly and positively
– “That Filename already exists”
vs.
– “Rename failed”
 10. Provide useful help and
documentation

120. Dialog Design
Categories of Dialogs

121. Feb 10, 2011 IAT 334 121
Agenda
 Dialog design
– Command Language
– WIMP - Window, Icon, Menu, Pointer
– Direct manipulation
– Speech/Natural language
– Gesture, pen, multi-touch, VR…

122. Feb 10, 2011 IAT 334 122
Command Languages
 Earliest UI interaction paradigms
 Examples
– MS-DOS shell
– UNIX shell

123. Feb 10, 2011 IAT 334 123
CL Attributes
 Work primarily by recall, not recognition
 Heavy memory load
 Little or nothing is visible
so…
 Poor choice for novices
but...

124. Feb 10, 2011 IAT 334 124
CL Attributes
 Specify commands to operate on current
data collection
 User only controls initiation
 Single thread of control
 Some other display area needed

125. Feb 10, 2011 IAT 334 125
CL Design Goals
 Consistency
– Syntax, order
 Good naming and abbreviations
 Doing your homework in design can help
alleviate some of the negatives

126. Feb 10, 2011 IAT 334 126
Consistency
 Provide a consistent syntax
– In general: Have options and arguments
expressed the same way everywhere
– UNIX fails here because commands were
developed by lots of different people at
different organizations
• No guidelines provided

127. Feb 10, 2011 IAT 334 127
Dialog Order
 English: SVO subject verb object
 CL: S assumed (you)
Is VO or OV better? % rm file
% file rm
 V dO iO vs. V iO dO
% print file thePrinter
% lpr -PthePrinter file

128. Dialog Order
 Technical issues dictate the choice:
 V iO dO
% lpr -PthePrinter file
 The command must parse the arguments
– So the command comes first
 Flags control how to act on the file
– Want to parse all flags before checking files
– e.g. -o outputFile
Feb 10, 2011 IAT 334 128

129. Feb 10, 2011 IAT 334 129
Syntax
 Pick a consistent syntax strategy
– Simple command list
• eg., vi minimize keystrokes
– Commands plus arguments
• realistic, can provide keyword parameters
• % cp from=foo to=bar
– Commands plus options plus arguments
• what you usually see

130. Feb 10, 2011 IAT 334 130
Terminology
 Keep terminology consistent
– Same concept expressed with same options
– Useful to provide symmetric (congruent)
pairings
• forward/backward
• next/prev
• control/meta

131. Feb 10, 2011 IAT 334 131
WIMP
 Focus: Menus, Buttons, Forms
 Predominant interface paradigm now
(with some direct manipulation added)
 Advantages:
– ?

132. Recognition
 Recognition is easier than recall!
– Recall has one cue
– Recognition has the recall cue + the presence
of the prompting word/icon
Feb 10, 2011 IAT 334 132

133. Feb 10, 2011 IAT 334 133
Menus
 Key advantages:
– 1 keystroke or mouse operation vs. many
– No memorization of commands
– Limited input set

134. Feb 10, 2011 IAT 334 134
Menus
 Many different types
– pop-up
– pull-down
– radio buttons
– pie buttons
– hierarchies

135. Feb 10, 2011 IAT 334 135
Menu Items
 Organization strategies
– Create groups of logically similar items
– Cover all possibilities
– Ensure that items are non-overlapping
– Keep wording concise, understandable

136. Feb 10, 2011 IAT 334 136
Presentation Sequence
 Use natural if available
– Time
• e.g. Breakfast, Lunch, Dinner
– Numeric ordering
• e.g. Point sizes for font
– Size
• Canada-> BC -> Surrey

137. Feb 10, 2011 IAT 334 137
Presentation Sequence
 Choices
– Alphabetical
– Group related items
– Frequently used first
– Most important first
– Conventional order (MTWRF)
 Don’t change the order on the fly!

138. Feb 10, 2011 IAT 334 138
Direct Manipulation
 Continuous visibility of the objects and actions
of interest
 Rapid, incremental actions
 Reversibility of all actions to encourage
experimentation
 Syntactic correctness of all actions—every action
is syntactically legal
 Replacement of command language syntax by
direct manipulation of object of interest

139. Feb 10, 2011 IAT 334 139
Direct Manipulation
 Examples
– WYSIWYG editors and word processors
– VISICALC - 1st electronic spreadsheet
– CAD
– Desktop metaphor
– Video games

140. DM Syntax
 Typical DM syntax is postfix
 DirectObjects first, Verb second
– In this case, the command completes the
utterance
 Enables separate selection syntax
 Indirect objects typically specified before
direct objects
– e.g. brush size before painting in Photoshop
Feb 10, 2011 IAT 334 140

141. Feb 10, 2011 IAT 334 141
DM Essence
 Representation of reality that can be
manipulated
 The user is able to apply intellect directly to
the task
 Don’t have to name things, just touch them
 The tool itself seems to disappear

142. Direct Manipulation is
Locality
 DM Relies on a primary geometric organization
 Items located nearby are frequently edited
together
– The words in a sentence
– A column of numbers in a spreadsheet
 Less related -> Less local -> Less DM!
Feb 10, 2011 IAT 334 142

143. User Modeling
Predicting thoughts and actions
GOMS

144. Feb 24, 2011 IAT 334 144
Agenda
 User modeling
– Fitt’s Law
– GOMS

145. Feb 24, 2011 IAT 334 145
User Modeling
 Idea: If we can build a model of how a
user works, then we can predict how s/he
will interact with the interface
– Predictive modeling
 Many different modeling techniques exist

146. User Modeling – 2 types
 Stimulus-Response
– Hick’s law
– Practice law
– Fitt’s law
 Cognitive – human as interperter/predictor –
based on Model Human Processor (MHP)
– Key-stroke Level Model
• Low-level, simple
– GOMS (and similar) Models
• Higher-level (Goals, Operations, Methods, Selections)
• Not discussed here
Feb 24, 2011 IAT 334 146

147. Power Law of Practice
 Tn = T1n-a
– Tn to complete the nth trial is T1 on the first trial
times n to the power -a; a is about .4, between .2
and .6
– Skilled behavior - Stimulus-Response and routine
cognitive actions
• Typing speed improvement
• Learning to use mouse
• Pushing buttons in response to stimuli
• NOT learning
Feb 24, 2011 IAT 334 147

148. Hick’s Law
 Decision time to choose among n equally
likely alternatives
– T = Ic log2(n+1)
– Ic ~ 150 msec
Feb 24, 2011 IAT 334 148

149. Fitts’ Law
 Models movement times for selection
(reaching) tasks in one dimension
 Basic idea: Movement time for a selection
task
– Increases as distance to target increases
– Decreases as size of target increases
Feb 24, 2011 IAT 334 149

150. Fitts: Index of Difficulty
 ID - Index of difficulty
 ID is an information theoretic quantity
– Based on work of Shannon – larger target => more
information (less uncertainty)
Feb 24, 2011 IAT 334 150
ID = log2 (d/w + 1.0)
bits
result
width (tolerance)
of target
distance
to move

151. Design implications
 Menu item size
 Icon size
 Put frequenlty used icons together
 Scroll bar target size and placement
– Up / down scroll arrows together or at top
and bottom of scroll bar
Feb 24, 2011 IAT 334 151

152. Feb 24, 2011 IAT 334 152
GOMS
 One of the most widely known
 Assumptions
– Know sequence of operations for a task
– Expert will be carrying them out
 Goals, Operators, Methods, Selection
Rules

153. Feb 24, 2011 IAT 334 153
GOMS Procedure
 Walk through sequence of steps
 Assign each an approximate time duration
-> Know overall performance time
 (Can be tedious)

154. Feb 24, 2011 IAT 334 154
Limitations
 GOMS is not for
– Tasks where steps are not well understood
– Inexperienced users
 Why?
 Good example: Move a sentence in a
document to previous paragraph

155. Feb 24, 2011 IAT 334 155
Goal
 End state trying to achieve
 Then decompose into subgoals
Moved sentence
Select sentence
Cut sentence
Paste sentence
Move to new spot
Place it

156. Feb 24, 2011 IAT 334 156
Operators
 Basic actions available for performing a
task (lowest level actions)
 Examples: move mouse pointer, drag,
press key, read dialog box, …

157. Feb 24, 2011 IAT 334 157
Methods
 Sequence of operators (procedures) for
accomplishing a goal (may be multiple)
 Example: Select sentence
– Move mouse pointer to first word
– Depress button
– Drag to last word
– Release

158. Feb 24, 2011 IAT 334 158
Selection Rules
 Invoked when there is a choice of a
method
 Example: Could cut sentence either by
menu pulldown or by ctrl-x

159. Feb 24, 2011 IAT 334 159
Further Analysis
 GOMS is often combined with a keystroke
level analysis
– Assigns times to different operators
– Plus: Rules for adding M’s (mental
preparations) in certain spots

160. Feb 24, 2011 IAT 334 160
Example
1. Select sentence
Reach for mouse H 0.40
Point to first word P 1.10
Click button down K 0.60
Drag to last word P 1.20
Release K 0.60
3.90 secs
2. Cut sentence
Press, hold ^ Point to menu
Press and release ‘x’ or Press and hold mouse
Release ^ Move to “cut”
Release
3. ...
Move Sentence

161. Keystroke-Level Model
 Simplified GOMS
 KSLM - developed by Card, Moran & Newell, see
their book
– The Psychology of Human-Computer Interaction,
Card, Moran and Newell, Erlbaum, 1983
 Skilled users performing routine tasks
 Assigns times to basic human operations -
experimentally verified
 Based on MHP - Model Human Processor
Feb 24, 2011 IAT 334 161

162. Feb 24, 2011 IAT 334 162
User Profiles
 Attributes:
– attitude, motivation, reading level, typing
skill, education, system experience, task
experience, computer literacy, frequency of
use, training, color-blindness, handedness,
gender,…
 Novice, intermediate, expert

163. Feb 24, 2011 IAT 334 163
Motivation
 User
– Low motivation,
discretionary use
– Low motivation,
mandatory
– High motivation, due
to fear
– High motivation, due
to interest
 Design goal
– Ease of learning
– Control, power
– Ease of learning,
robustness, control
– Power, ease of use

164. Feb 24, 2011 IAT 334 164
Knowledge & Experience
 Experience
 task system
– low low
– high high
– low high
– high low
 Design goals
– Many syntactic and
semantic prompts
– Efficient commands,
concise syntax
– Semantic help facilities
– Lots of syntactic
prompting

165. Feb 24, 2011 IAT 334 165
Job & Task Implications
 Frequency of use
– High - Ease of use
– Low - Ease of learning & remembering
 Task implications
– High - Ease of use
– Low - Ease of learning
 System use
– Mandatory - Ease of using
– Discretionary - Ease of learning

166. Feb 24, 2011 IAT 334 166
Modeling Problems
 1. Terminology - example
– High frequency use experts - cmd language
– Infrequent novices - menus
 What’s “frequent”, “novice”?

167. Feb 24, 2011 IAT 334 167
Modeling Problems (contd.)
 2. Dependent on “grain of analysis”
employed
– Can break down getting a cup of coffee into
7, 20, or 50 tasks
– That affects number of rules and their types

168. Feb 24, 2011 IAT 334 168
Modeling Problems (contd.)
 3. Does not involve user per se
– Don’t inform designer of what user wants
 4. Time-consuming and lengthy