Post on 05-Jun-2020
1
1
MSc Computer Science: Introduction to Human Computer Interaction
Bob Hendley
Room: 236, CS
MSc CS: Intro. to HCI 2016-17 2 2
Introduction to HCI
100% coursework Re-assessment by repeat
Classes: Monday 5:00
G29 Mech. Eng.
Thursday 10:00 G34 Mech. Eng.
Notes are at: http://www.cs.bham.ac.uk/~rjh/courses/IntroductionToHCI
MSc CS: Intro. to HCI 2016-17 3 3
First some motivation
……
MSc CS: Intro. to HCI 2016-17 4 4
The world is full of bad design …
Photo from Jacob Nielsen’s Alertbox June 7, 2004
MSc CS: Intro. to HCI 2016-17 5 5
…. And …
MSc CS: Intro. to HCI 2016-17 6 6
… and
2
MSc CS: Intro. to HCI 2016-17 7
What’s wrong with these?
Complex
Ugly
Non-intuitive & inconsistent
Fail to consider:
User
Usage
Non-ergonomic
MSc CS: Intro. to HCI 2016-17 8
What’s wrong with these?
Complex
Ugly
Non-intuitive
Fail to consider:
User
Usage
non-ergonomic
Good design must:
Consider capabilities of user
Goals of user & usage scenarios
Take a user focussed view
NOT system focussed!
MSc CS: Intro. to HCI 2016-17 9 9
See:
http://www.baddesigns.com/
http://www.webpagesthatsuck.com/
http://www.useit.com/alertbox/bad-design.html
… and many many more!
http://www.baddesigns.com/
http://www.webpagesthatsuck.com/
http://www.useit.com/alertbox/bad-design.html
… and many many more!
MSc CS: Intro. to HCI 2016-17 10 10
And sometimes good design …
MSc CS: Intro. to HCI 2016-17 11 11
And …
MSc CS: Intro. to HCI 2016-17 12
3
MSc CS: Intro. to HCI 2016-17 13
Why are these good?
User focussed Driven by:
Capabilities of people
What the user is doing
How they will be used
Context of use: For instance: safety critical, social, training/learning …
Aesthetics
Ergonomics
Evaluated ….. & modified
MSc CS: Intro. to HCI 2016-17 14 14
Many things look good – but aren’t!
http://www.zaha-hadid.com/
MSc CS: Intro. to HCI 2016-17 15 15
Does it matter?
It may just confuse you!
But:
You might get a ticket
Take longer to complete a task
Delete your work!
Crash your car!
Kill your patients!
…….
MSc CS: Intro. to HCI 2016-17 16 16
Or worse: The 2000 USA Presidential Ballot in Florida
MSc CS: Intro. to HCI 2016-17 17 17
So why look at HCI?
Pragmatically:
Typically, the largest part of a software project:
Cost
Time
The only bit the user sees!
MSc CS: Intro. to HCI 2016-17 18 18
So, what is it about?
Screen design?
Interaction?
People?
Experiments?
4
MSc CS: Intro. to HCI 2016-17 19 19
So, what is it about?
Screen design? Attractive
Functional
Interaction? Shallow
Deep
People? Capabilities
Constraints
Goals/tasks etc.
Experiments? To evaluate a
system
To learn about people’s capabilities
MSc CS: Intro. to HCI 2016-17 20 20
HCI is changing..
Physical things
GUI interfaces
Collaborative interfaces
Internet technologies
Social technologies
Ubiquitous technologies
?
MSc CS: Intro. to HCI 2016-17 21 21
What’s the problem?
Slide idea by Bill Buxton
transistors speed
discs cost
1950 1990 2030
Computer
abilities Features
Productivity
Ease of use
1950 1990 2030
Promised
Functionality
1950 2030 2000BC
human
abilities
Threshold of complexity
So:
•People can’t get
smarter
•Technology gets more complex
•Interfaces must fill the gap
MSc CS: Intro. to HCI 2016-17 22 22
Human Computer Interaction
Computer Science
Ergonomics
Psychology
Sociology
Design
…and more
MSc CS: Intro. to HCI 2016-17 23 23
To make better interactive technology …. We need to:
Know about how people interact with things
Know about what people can and can’t do
And when!
Know about the situations in which people
do things
Know about the basics of good design
Understand people’s goals
… and then check whether it works
MSc CS: Intro. to HCI 2016-17 24 24
Can we master CS + Psychology, sociology, business, linguistics ……?
No! … but we can all learn things about people
and design that will help us create better artefacts than we would otherwise have done…
Or
we can find out when we need to!
5
MSc CS: Intro. to HCI 2016-17 25 25
HCI is made up of…
Theories: learn and apply
Models: create and use
Methods: master and apply
Guidelines: learn and use
Principles: understand and apply
Techniques: master and use
So, elements of
Science
Computer Science
Psychology
…
Art
Engineering
Craft
….
MSc CS: Intro. to HCI 2016-17 26 26
… and these may concern:
People
Analysis
Design
Implementation
Evaluation
…..
MSc CS: Intro. to HCI 2016-17 27 27
So, a tentative outline:
Motivation
People. Their abilities & Limitations
Coursework
Techniques for design User centred design
Scenarios
Personas
Prototyping
Design Evaluation
Evaluation with users
So:
We’ll focus upon
methodologies for engineering good HCI
And not on theoretical or research in HCI
MSc CS: Intro. to HCI 2016-17 28
Human Computer Interaction, 3rd Edition Alan Dix, Janet Finlay, Gregory Abowd, Russell Beale Prentice Hall, 2004. ISBN 0-13-046109-1
http://www.youtube.com/watch_popup?v=ZfV4R4x2SK0
28
Text:
Human Computer Interaction, 3rd Edition Alan Dix, Janet Finlay, Gregory Abowd, Russell Beale Prentice Hall, 2004. ISBN 0-13-046109-1
http://www.youtube.com/watch_popup?v=ZfV4R4x2SK0
Human Computer Interaction, 3rd Edition Alan Dix, Janet Finlay, Gregory Abowd, Russell Beale Prentice Hall, 2004. ISBN 0-13-046109-1
http://www.youtube.com/watch_popup?v=ZfV4R4x2SK0
Human Computer Interaction, 3rd Edition Alan Dix, Janet Finlay, Gregory Abowd, Russell Beale Prentice Hall, 2004. ISBN 0-13-046109-1
http://www.youtube.com/watch_popup?v=ZfV4R4x2SK0
MSc CS: Intro. to HCI 2016-17 29 29
Lecture 2
It’s all about people: Perceptual systems
What & how
Examples
Vision
Memory
Levels of information processing
Lessons for HCI
MSc CS: Intro. to HCI 2016-17 30 30
What is a User? A dip into some examples from psychology
Is
Behaves
Feels
6
MSc CS: Intro. to HCI 2016-17 31 31
What makes up a person?
Body
Senses & perception
Memory
Behaviour
Thought
MSc CS: Intro. to HCI 2016-17 32 32
The Human as an Input Device
How we make ‘sense’ of the
world around us… inputs and
understanding
MSc CS: Intro. to HCI 2016-17 33 33
Each Sense has…
A sensor – e.g.. Eye, skin, ear etc
A process – nerves … brain etc.
Limitations – pitch, brightness, cycle time etc.
….. And there is the added complexity of
individual differences in sensory perception:
Between individuals
Over time
MSc CS: Intro. to HCI 2016-17 34
Perception & Senses
Vision
Hearing
Touch
Smell & taste
Motion/Balance
Kinethesis/ Proprioception
.. and others –
temperature, pain, pressure etc.
MSc CS: Intro. to HCI 2016-17 35
Vision
Primary sense
Most important for HCI
High bandwidth (10GB/sec ??????)
High resolution
Specialist processors/processing
Take advantage of this and especially pre-attentive processing
MSc CS: Intro. to HCI 2016-17 36
Pop outs & gestalts
No cognitive processing required
Very fast
Can be inhibited/confused
Examples: Colour
Size
Number
Motion
7
MSc CS: Intro. to HCI 2016-17 37
Some Examples
MSc CS: Intro. to HCI 2016-17 38
Connectedness
a b
c d
MSc CS: Intro. to HCI 2016-17 39
Symmetry
MSc CS: Intro. to HCI 2016-17 40
Closure
a
a b
MSc CS: Intro. to HCI 2016-17 41
Object interpretation
MSc CS: Intro. to HCI 2016-17 42
Foreground & Background
8
MSc CS: Intro. to HCI 2016-17 43
Contours
a
a
b
MSc CS: Intro. to HCI 2016-17 44
Transparency
a
MSc CS: Intro. to HCI 2016-17 45
Texture
a
ab
c d
MSc CS: Intro. to HCI 2016-17 46
85689726984689762689764358922659865986554897689269898
02462996874026557627986489045679232769285460986772098
90834579802790759047098279085790847729087590827908754
98709856749068975786259845690243790472190790709811450
85689726984689762689764458922659865986554897689269898
MSc CS: Intro. to HCI 2016-17 47
8568972698468976268976435892265986598655489768926989
0246299687402655762798648904567923276928546098677209
9083457980279075904709827908579084772908759082790875
9870985674906897578625984569024379047219079070981145
85689726984689762689764458922659865986554897689269898
MSc CS: Intro. to HCI 2016-17 48
Orientation
9
MSc CS: Intro. to HCI 2016-17 49
Motion
MSc CS: Intro. to HCI 2016-17 50
Shading
MSc CS: Intro. to HCI 2016-17 51
Faces/emotion …..
MSc CS: Intro. to HCI 2016-17 52
Length Width
Parallelism Curvature
Number Added marks Spatial grouping
Shape
Enclosure
MSc CS: Intro. to HCI 2016-17 53
An Example
MSc CS: Intro. to HCI 2016-17 54
Depth – seeing the 3D world
Many depth cues
Stereopsis
Occlusion
Sharpness
Accommodation
Contrast
Some will dominate others
In other cases, conflicts cause sickness
10
MSc CS: Intro. to HCI 2016-17 55
Problems
People differ:
Colour blindness
Stress levels
Stereopsis
etc.
There is not a complete understanding of human visual system
MSc CS: Intro. to HCI 2016-17 56 56
Interpreting images - context
The visual system compensates for: movement changes in luminance.
Context is used to resolve ambiguity
Optical illusions sometimes occur due to over compensation
MSc CS: Intro. to HCI 2016-17 57 57
Interpreting images - context
The visual system compensates for: movement changes in luminance.
Context is used to resolve ambiguity
Optical illusions sometimes occur due to over compensation
MSc CS: Intro. to HCI 2016-17 58 58
Interpreting images - context
The visual system compensates for: movement changes in luminance.
Context is used to resolve ambiguity
Optical illusions sometimes occur due to over compensation
MSc CS: Intro. to HCI 2016-17 59 59
Interpreting images - context
The visual system compensates for: movement changes in luminance.
Context is used to resolve ambiguity
Optical illusions sometimes occur due to over compensation
MSc CS: Intro. to HCI 2016-17 60
Interference
Try naming the ink colour in first column
Then try the second!
The point is:
•when two cues work together,
then we process quickly
•When they conflict, then we are
slow and error rates increase
….and this applies across all
levels
11
MSc CS: Intro. to HCI 2016-17 61 MSc CS: Intro. to HCI 2016-17 62 62
Touch
Provides important feedback about environment.
May be key sense for someone who is visually impaired.
Some areas more sensitive than others e.g. fingers.
Also consider:
Stimulus received via receptors in the skin: thermoreceptors – heat and cold nociceptors – pain mechanoreceptors – pressure
Kinethesis - awareness of body position affects comfort and performance.
MSc CS: Intro. to HCI 2016-17 63 63
Impact on HCI
Understanding the limitations and capabilities of humans is essential as guidance for good design. E.g.
Grouping
Consistent cueing
STM limitations
…….
But there is much more to this than we have described here!
But these models are not enough: There are
competing/inconsistent theories
They are incomplete
We are complex!
Large individual differences Vision
Motor skills
Cognitive skills
There are model based tools that aim to predict performance
But they have limited scope For now!
MSc CS: Intro. to HCI 2016-17 64 64
Impact on HCI (2)
The examples we have looked at:
Are chosen because they are easily accessible
They are surprising and show the complexity of people and their processing and behaviour
But, these examples are mostly at a ‘surface’
level
There are big gains from using this knowledge:
Selection rather than specifying (I.e. recognition rather than recall)
Visual grouping and layout
Etc
Even more important is understanding the deeper and longer term factors
E.g. goals, motivations, affective states, usage scenarios and so on
MSc CS: Intro. to HCI 2016-17 65
Take a look at this example!
If you don’t believe me:
The door study
If you don’t believe me:
The door study
MSc CS: Intro. to HCI 2016-17 66
Lecture 3
Let’s look at people more deeply:
Memory & processing
Maslow’s Triangle
Case studies: Teaching
Behaviour change
Interruptions
Alarm clock
Lessons
12
MSc CS: Intro. to HCI 2016-17 67 67
The Human as a Store
Humans have the capacity to remember and retrieve information…
this affects the way they use technology
How does it work?
MSc CS: Intro. to HCI 2016-17 68 68
Three Different ‘Stores’
Sensory buffers: momentary stores for stimuli received by the senses. This information, unless encoded in the short-term memory, is quickly lost.
Short-term memory (or working memory): short-term memory acts as a store for
information required fleetingly.
Long-term memory: this forms the main
resource for memory.
MSc CS: Intro. to HCI 2016-17 69 69
Short Term Memory
An example of this would be recalling a telephone number long enough to write it down. Short-term memory degrades quickly, and has a limited capacity.
Quick access time – 70ms Short term storage – ~20 second decay time
Limited capacity Length of sequence remembered of order = 7 ± 2 (Miller, 1956) Chunking
Often referred to as ‘Working memory’
MSc CS: Intro. to HCI 2016-17 70 70
Chunking and STM
Short-term memory holds information that is actively being used (thought about, reasoned with).
A chunk can be thought of as a single object that conveys a larger amount of information (e.g. 0121 414 xxxx).
Examples of these include words, shapes and colours. However, the information decays in seconds as items are displaced by new items coming in.
MSc CS: Intro. to HCI 2016-17 71 71
LTM – Networked chunks
Here we store everything we ‘know’. Long-term memory is characterised by huge capacity, slow access time and relative accuracy over time.
It is organised in an Episodic way events and experiences in sequential order …….. and a Semantic way
facts, concepts and skills that we have acquired
Storage Structure, familiarity and concreteness Decay, interference, forgetting
Retrieval Recall - reproduced Recognition – clue given – faster, more accurate ….
MSc CS: Intro. to HCI 2016-17 72 72
Different types of human processing
Norman introduced the idea that product design should address three different levels of cognitive and emotional processing:
Visceral
Behavioral
Reflective.
13
MSc CS: Intro. to HCI 2016-17 73 73
Visceral Processing
The most immediate level of processing, in which we react to visual and other sensory aspects of a product that we can perceive before significant interaction occurs. Visceral processing helps us make rapid decisions about what is good, bad, safe, or dangerous.
MSc CS: Intro. to HCI 2016-17 74 74
Behavioral Processing
The middle level of processing that lets us manage simple, everyday behaviors, which, according to Norman, constitute the majority of human activity.
Norman states:
historically, interaction design and usability practices have primarily addressed this level of cognitive processing.
MSc CS: Intro. to HCI 2016-17 75 75
Reflective Processing
The least immediate level of processing, which involves conscious consideration and reflection on past experiences.
Reflective processing can enhance or inhibit behavioral processing, but has no direct access to visceral reactions.
This level of cognitive processing is accessible only via memory, not through direct interaction or perception.
MSc CS: Intro. to HCI 2016-17 76
Maslow’s Hierarchy of needs
MSc CS: Intro. to HCI 2016-17 77
Maslow’s Triangle
MSc CS: Intro. to HCI 2016-17 78
Some Case Studies
Teaching
Behaviour change
Interruptions
Alarm clocks
Lessons?
14
MSc CS: Intro. to HCI 2016-17 79
What must we do?
If we want to build systems that help people in complex tasks:
Understand the tasks & the cognitive processes Build on research & practice
(these are often incomplete or conflicting!)
Build systems with a knowledge of these things
Test whether they work
MSc CS: Intro. to HCI 2016-17 80
(1) Systems that teach
How do people learn?
What is the best way to ‘teach’ people
Can we adapt the behaviour of a system to the abilities/traits & knowledge of an individual?
Does it work?
MSc CS: Intro. to HCI 2016-17 81
Models of Learning Style
The Felder/Silverman model classifies learners in 4 dimensions:
MSc CS: Intro. to HCI 2016-17 82
So:
Can we build a system which:
Builds a model of a students learning style?
Maintains a model of a students existing ‘knowledge’?
Adapts its teaching to an individual?
Does it work?
MSc CS: Intro. to HCI 2016-17 83
Results: Adapting teaching
based on a student
model (learning style
& knowledge):
•Improves
learning
•Short term
•Long term
•Increases
learner
satisfaction
LS+K > K
LS+K > LS
[Short & long term learning &
user satisfaction] MSc CS: Intro. to HCI 2016-17 84
(2) Behaviour change
Problem:
Many people would like to change their bad behaviours:
Addictions, health, fitness, mental health …….
Technology provides a potential route
How can we help:
There are many apps, websites …. But do they work?
What do we need to do to enable change?
What are the problems?
15
MSc CS: Intro. to HCI 2016-17 85
Draw upon research to build models to support change
Models (to draw upon) System1/System2
How do we change behaviour?
Habits How are they formed?
Changed? Removed?
Reactance Why? What causes it? How can
it be reduced? What influences it?
Priming How do we use/avoid it?
Triggers
Affective state
Activity
Etc.
Build technology that: Senses
Mobile ‘phone
Interprets raw data to information
Acts appropriately for: that user,
in that context,
at that time …
MSc CS: Intro. to HCI 2016-17 86
(3) Interruptions
Problem:
Our systems interrupt us:
Typically, people receive many hundreds of notifications on their ‘phone each day
This is disruptive!
Can we improve this?
Find appropriate: Time
Medium
Device
for each notification
Understand the value and cost of an interruption in different contexts adapt
MSc CS: Intro. to HCI 2016-17 87
What do we need?
Models of behaviour:
Interruptability
When should we interrupt?
Tasks
What is the user doing?
Goals
Etc.
Sense user state
Interpret interruption
Predict future states
Predict cost & value of interruption in current & future contexts
Determine best time, place, method to issue notification
MSc CS: Intro. to HCI 2016-17 88
(4) Smart Alarm apps
Problem: How can you build a better alarm?
Build an understanding of sleep patterns
When is the best time to awaken a person?
Build an app which:
Monitors users sleep pattern:
e.g. accelerometer, mic
Uses a window to define alarm time
Wakes user at best time in their sleep cycle
MSc CS: Intro. to HCI 2016-17 89
Summary
Sometimes we don’t need to be too clever, but:
We may need to understand: Models of perception, cognition,
behaviour: To guide good design
Understanding of User goals, tasks, capabilities etc.
Models of behaviour: Of different types
And what drives it
Drawing upon theories and models: possibly, across several
disciplines
We may need to build systems which:
Sense
Interpret, reason, infer, learn
Act appropriately
We always need to understand user
Check whether they work:
And possibly fix them
underlying knowledge
MSc CS: Intro. to HCI 2016-17 90 90
Lecture 4
Coursework:
Motivation: ATM
Groups
Coursework Specification
Assessment
16
MSc CS: Intro. to HCI 2016-17 91
ATM/Cash Machine
Surely, this is a trivial interface to get right!
User Goals? Cash before card!
Ergonomics
Data entry <enter>
Buttons/touch screen
Consistency
Requirements
Etc.
MSc CS: Intro. to HCI 2016-17 92
A B C D E
Success Rate 90.9 90.9 95.0 92.3 80.0
No. of Clicks 29.1 25.8 24.6 27.4 30.9
Time 63.9 59.2 56.3 57.9 72.0
Satisfaction 4.29 4.16 4.44 4.14 3.97
Difference 22.1 8.81 14.8 11.7 27.4
ATM: Empirical studies This study compared
performance with 5 banks’ ATMs:
Large variation in performance:
Error rate
Time taken
Satisfaction
And also, large variation between users!
MSc CS: Intro. to HCI 2016-17 93
Lectures 5, 6 & 7
Design Alternative models
Where is the focus?
UCSD (User Centred System Design)
Personas
Scenarios
93 MSc CS: Intro. to HCI 2016-17 94 94
Understanding the Design Process
What is the design process?
…. And what should it be?
…. Remember, we want:
To produce good designs
To produce them efficiently
Where are good/bad decisions made?
Why are good/bad decisions made?
MSc CS: Intro. to HCI 2016-17 95 95
Developing Interactive Products
Stage 1 – build time 1. Designers: understand
requirements and explore, design, evaluate and refine solutions
2. Implementers: construct, test and refine system
Stage 2 – use time ‘Stakeholders’ use the
system and because their needs, contexts and objectives can only be anticipated – some changes are generally made to the product at this stage
The more time spent in the early stages: The lower the
overall cost
The better the solution
So: Focus on
understanding users & design
Focus on ‘stakeholders’ – end users ++
MSc CS: Intro. to HCI 2016-17 96 96
RE responsible in the failure of 90% of
larger projects (Davis et al., 2006)
Poor requirements management can be attributed to
71% of software projects that fail; greater than bad
technology, missed deadlines, and change
management issues (Lindquist, 2005)
Fixing mistakes made at the requirements
elicitation stage accounts for 75% of all error
removal costs (Davey & Cope, 2008)
Poor execution of elicitation will almost
guarantee that the final project is a complete
failure (Hickey & Davis, 2003)
17
MSc CS: Intro. to HCI 2016-17 97 97
Efficient Development..
Relies on the system’s developer having a GOOD understanding of the ‘stakeholders’ –
(users?)
Needs
Capabilities
Objectives, goals, tasks, plans …..
Context
Etc.
... And knowing what the technology can do!
MSc CS: Intro. to HCI 2016-17 98 98
The Focus of the development
… can vary..
•Context
•System
•User
MSc CS: Intro. to HCI 2016-17 99 99
System Centred Design
MSc CS: Intro. to HCI 2016-17 100 100
System Centred Design
MSc CS: Intro. to HCI 2016-17 101 101
System Centred Design
What can I easily build on this platform?
What can I create from the available tools?
What do I, as a programmer [or administrator, manager …], find interesting?
How do I (the developer) see the system?
This is
what you get!
System centred: not just
technology centred
MSc CS: Intro. to HCI 2016-17 102 102
User Centred …
Design is focused upon the users:
Abilities and real needs
Not just what you hope or imagine they are
Context
Work
Tasks
Values
….
18
MSc CS: Intro. to HCI 2016-17 103 103
Methodologies
Depending on the focus we can label our methodology as:
Abilities and needs: User Centred Design
Context: Contextual Design
Work: Goal Directed Design
Tasks: Task Centred Design
Values: Value / Worth Centred Design
MSc CS: Intro. to HCI 2016-17 104 104
User Centred [System] Design
Focus on: the people who will use the system
their requirements
their preferences
Building models of: Users
Tasks
Systems
This is usually:
An iterative process
That involves:
Prototyping and Evaluation with (and without) users
Descriptive models that
build an understanding
MSc CS: Intro. to HCI 2016-17 105 105
UCD
MSc CS: Intro. to HCI 2016-17 106 106
Core Concepts in UCD
Early stages User models
Task models
Context
But also on Goals
Values
Prototyping, evaluation, refinement ….
Later stages?
Inclusive Design
Design for all
Universal Access
MSc CS: Intro. to HCI 2016-17 107 107
Who are Users in UCD?
They should represent the actual users: Not one user but all
different classes
All types of user e.g. Learning: students,
teachers, parents, administrators …
eCommerce: customer, marketing, sales, managers …
Consider:
Yourself
Your peers
Your granny
Your nephew
….
A system designed to teach 7 year olds remedial
arithmetic:
•Required a reading age of 14
•Sophisticated cognitive & social skills
•Used green text on a blue background
MSc CS: Intro. to HCI 2016-17 108 108
Who are Users in UCD?
They should represent the actual users: Not one user but all
different classes
All types of user e.g. Learning: students,
teachers, parents, administrators …
eCommerce: customer, marketing, sales, managers …
Consider:
Yourself
Your peers
Your granny
Your nephew
….
A system designed to teach 7 year olds remedial
arithmetic:
•Required a reading age of 14
•Sophisticated cognitive & social skills
•Used green text on a blue background
19
MSc CS: Intro. to HCI 2016-17 109 109
Video here….
http://www.computing.dundee.ac.uk/projects/UTOPIA/
MSc CS: Intro. to HCI 2016-17 110 110
Tasks (and Goals)
Tasks
What is the user trying to do with the system?
Not all systems are task based (eg. Games, SNS)
Not all tasks can be easily specified
Goals Irrespective of the user
tasks, there can be conflicting or complementary goals Interruptions
To have fun?
Do something else
So, these may constrain time, engagement, motivation ….
MSc CS: Intro. to HCI 2016-17 111 111
Context
Where will the system be used?
Quiet office, busy train, outside ….
What sort of technology will be deployed?
Desktop, tablet, kiosk ..
Will the users be able to get any help?
Will they receive training?
All these constrain the space of designs
MSc CS: Intro. to HCI 2016-17 112 112
Values
What matters to the user?
Motivation, accuracy, speed, satisfaction…
What is important in the context?
What are the business concerns?
MSc CS: Intro. to HCI 2016-17 113 113
Lecture 6
Models of Users
… It’s all about empathy… Personas
Scenarios
The point is: It’s all too easy to forget:
Who the user is
What motivates them
What they are trying to do
MSc CS: Intro. to HCI 2016-17 114
Warning!!!
This section might seem very …..
But it works!
(if you engage with it)
20
MSc CS: Intro. to HCI 2016-17 115
Personas & Scenarios
Purpose:
To build an understanding/to construct ‘models’: Of users of the system
Of the way they will use it
And use these to:
To guide the design process
To guide the evaluation of designs
Methods:
Aim for good coverage of usage: Balance cost/value
(Ideally) Informed by real (potential) users Interviews, observations
etc.: This is hard to do
properly
Who are they? What are their constraints? What are their goals? etc
MSc CS: Intro. to HCI 2016-17 116 116
Modelling Users using Personas
Widely promoted by Alan Cooper as an integral component of Goal-Centred (Directed) design Refer to: www.interactionbydesign.com/presentations/olsen_persona_toolkit.pdf
Personas are user archetypes that we construct from behavioral data: gathered during user interviews and field
observations.
… but also from insight
MSc CS: Intro. to HCI 2016-17 117 117
The Power of Personas
The personas are given realistic:
Names
Faces
Personalities
to foster user empathy within a design team.
As well as driving design:
Personas & their scenarios can be used later to:
evaluate prototypes
and the final product
A critical element of personas:
beyond capturing typical user attitudes & behavior patterns
and roles
is capturing user motivations in
the form of specific goals.
MSc CS: Intro. to HCI 2016-17 118 118
Note:
In programming we design and program test cases for software sometimes before even writing the program itself.
HCI approaches this in a similar fashion by creating scenarios which they expect users to encounter or run through. One major distinction is that scenarios cover the
most likely of cases and only sometimes include the edge cases.
They will never, ever, cover every possible scenario.
MSc CS: Intro. to HCI 2016-17 119
An example Persona template
MSc CS: Intro. to HCI 2016-17 120
An example Persona The point is to build a
‘picture’ of the user:
•So that you can put
yourself in their place
21
MSc CS: Intro. to HCI 2016-17 121
And another
MSc CS: Intro. to HCI 2016-17 122 122
Creating Scenarios
“A scenario is a concise description of a persona using a product to achieve a goal” (Cooper).
concise : short but complete; breadth instead of depth
product : assume the product (software or physical device) exists, even if it doesn’t
goal : the reason why we perform a task
There must be enough detail to drive design & evaluation
We are interested in:
The users’ behaviour
What they want to achieve
Not the details of how they achieve it (I.e. not keystrokes, menu selections etc.)
MSc CS: Intro. to HCI 2016-17 123 123
Why Use Scenarios?
They build an understanding of the users
They drive requirements analysis and design
Scenarios help us to validate our design
Scenarios help us check our assumptions
Successful Scenarios help us transfer theoretical/conceptual design to “wire frame” design
Like Personas, Scenarios create a shared understanding of the end users for the entire design team.
MSc CS: Intro. to HCI 2016-17 124 124
Scenario: example
Steve texts using predictive text
He is sending a message to a number he doesn’t have in his contacts It is a girl he met on the train and he
wants to meet up with her
He has the number on a scrap of paper
He is walking down towards New Street Station
It is getting quite dark
He is texting without checking the screen
MSc CS: Intro. to HCI 2016-17 125
Another Example: Booking train tickets
Steve Jones: 1. Steve has a meeting in London at 10:00 on Tuesday. He wants to find a train
that will arrive by 9:30 and return after 7:00. When he has selected the train he needs to tell purchasing to buy it. He needs the details in his diary. He needs his wife to have the details so that she knows what he is doing and, maybe, can ferry him to/from the station.
2. Steve lives in Stratford and wants to compare the options for tickets for his commute to Birmingham. He usually travels 4 days and either travels away or works from home the other day. He wants to keep costs down but needs flexibility.
3. On Sunday, Steve wants to take his family for a day out. He wants to choose the most interesting, quickest and cheapest option. He does not want to use a replacement bus service. His total for 2+2 is £120.
4. Steve needs to attend a meeting at 9:30 in central Paris on Monday. He would like to spend some time exploring the city. He wants to minimise his CO2 footprint but he also has a tight budget. He does not want to be away more than one night
MSc CS: Intro. to HCI 2016-17 126 126
Writing Good Scenarios
Brainstorm, within the context of our problem domain, the goals our Personas will have
Write the Scenarios for a specific Persona
Go for breadth rather than depth:
it is more important to describe things from start to finish rather than in exhaustive detail
Remember, this is about what the user wants to achieve not how they do it.
22
MSc CS: Intro. to HCI 2016-17 127 MSc CS: Intro. to HCI 2016-17 128
An example – open diary
system
Who are the users?
What are they trying to do?
MSc CS: Intro. to HCI 2016-17 129
An example – open diary
system
Who are the users?
What are they trying to do?
For instance, consider:
Students, lecturers, salesman, retired person ….
Privacy & security
Devices & synching
Anniversaries
Regular appointments
Types of appointments hard soft
Movable/fixed
Location
etc. etc.
When to notify: Anniversary, meetings (travel,
prepare ..)
You only identify these
issues by:
•Analysing existing systems
•Considering concrete
usage by concrete people
MSc CS: Intro. to HCI 2016-17 130
Some Examples
Here are some examples of personas. See
www.fluidproject.org
Here are some examples of personas. See
www.fluidproject.org
MSc CS: Intro. to HCI 2016-17 131 131
Further Work
Investigate the use of personas by searching for toolkits and case studies
MSc CS: Intro. to HCI 2016-17 132
Summary
Personas & scenarios are excellent ways to:
Focus on the users
Their context, motivations, goals, tasks, constraints etc.
Share & validate understanding of users
Undertake early stage testing
It’s really important
(and effective) to capture a lot of ‘soft’
information
Focus on the user’s
goals & tasks
Not on how they might use the system
Identify, archetypal users
23
MSc CS: Intro. to HCI 2016-17 133
Lecture 8
Tutorial
Review problem specifications
Tutorial with groups
MSc CS: Intro. to HCI 2016-17 134 134
Lecture 9&10
Prototyping What is a prototype & why do it
LoFi prototyping Screen mockups
Storyboards
Card-based prototypes
HiFi prototyping Tools
MSc CS: Intro. to HCI 2016-17 135 135
Prototyping and Construction
What is a prototype?
Why prototype?
Different kinds of prototyping low fidelity
high fidelity
Compromises in prototyping
vertical
horizontal
Construction
MSc CS: Intro. to HCI 2016-17 136 136
What is a Prototype
In many design fields a prototype is a model:
Cars
Buildings
Appliances
Etc.
MSc CS: Intro. to HCI 2016-17 137
Prototypes may serve different purposes
MSc CS: Intro. to HCI 2016-17 138
Aims of prototyping
To evaluate alternative solutions:
Quickly
Cheaply
Focus:
Broad but shallow
Deep but narrow
Prototypes may be:
Disposable
Evolving
Purpose: To understand requirements
To understand potential designs
To understand technology
…..
Make mistakes early and cheaply!
24
MSc CS: Intro. to HCI 2016-17 139
Methodology for prototyping
Iterative
Usually several stages of prototyping
Parallel
Consider alternative solutions
May have several orthogonal strands of prototyping
E.g. Cars: body, interior, drivetrain ….
Software: UI, DB, Logic ….
Evaluate each prototype
Be clear about the purpose
Minimise cost
Time
Effort
Only do what is necessary to meet goals
MSc CS: Intro. to HCI 2016-17 140 140
What do we mean by a HCI Prototype?
It can be (among other things):
a paper-based screen design
a storyboard, i.e. a cartoon-like series of scenes
An animated slide show
With interaction
a piece of software with limited functionality – built quickly using tools/scripting languages etc
a video simulating the use of a system
.....
Or even ....
a physical mockup (e.g. a ‘phone)
There may be parallel prototypes
to test different aspects
The aim is to understand the space of designs:
Test alternative solutions
Understand how they might be built
Evaluate them with users
MSc CS: Intro. to HCI 2016-17 141 141
Why Prototype?
Evaluation and feedback are central to interaction design
Stakeholders (ie. Users) can see/hold/interact with a prototype more easily than a document or a drawing
Team members can communicate effectively
You can test out ideas for yourself
It encourages reflection A very important aspect of design
Prototypes answer questions
support designers in choosing between alternatives
MSc CS: Intro. to HCI 2016-17 142 142
What to Prototype
Technical issues
Work flow, task design
Screen layouts and information display
Interaction models and modes
Difficult/controversial/critical areas
Rather than the routine
….
MSc CS: Intro. to HCI 2016-17 143 143
Lo-Fi Prototyping
Uses a medium which may be unlike the final medium
e.g. paper, cardboard, photoshop …
It is quick, cheap and easily changed/binned
Examples:
sketches of screens, task sequences,‘Post-it’ notes
Storyboards
‘Wizard-of-Oz’
MSc CS: Intro. to HCI 2016-17 144 144
Why Use Low-Fi Prototypes
Traditional methods take too long: Sketches prototype evaluate iterate
Can simulate the prototype: Sketches act as prototype:
Designer “plays computer”
Other design team members observe & record
Might sound silly:
….. but it is very effective
No implementation skills Allows non-programmers to participate
Widely used in industry
25
Paper-based prototypes
MSc CS: Intro. to HCI 2016-17 146
Later we can produce a more hifi version
It may be MUCH easier to draw
MSc CS: Intro. to HCI 2016-17 148 148
Card-based prototypes
• Combine screen mock-ups and storyboard • Use (e.g.) index cards (3 X 5 inches) • Each card represents one screen or part of
screen • Designer drives interaction • Often used in website development
Interaction
Interaction
MSc CS: Intro. to HCI 2016-17 149 149
Storyboards
Often used with scenarios, bringing more detail, and a chance to role play
It is a series of sketches showing how a user might progress through a task using the device
Used early in design
Evaluate
against Persona
& scenarios
MSc CS: Intro. to HCI 2016-17 150 150
Generating Storyboards
26
MSc CS: Intro. to HCI 2016-17 151 151
Storyboard used to generate prototype
MSc CS: Intro. to HCI 2016-17 152 152
Hi-Fi Prototyping
Uses materials that you would expect to be in the final product.
Prototype looks more like the final system than a low-fidelity version.
For a high-fidelity software prototype common environments include: Director, Flash, Visual Basic, Powerpoint, ….
Danger that users think they have a full system……. see compromises
MSc CS: Intro. to HCI 2016-17 153 153
Wizard of Oz
The user thinks they are interacting with a computer, but a developer is responding to generate the output rather than the system.
Usually done early in design to understand users’ expectations
What is ‘wrong’ with this approach?
MSc CS: Intro. to HCI 2016-17 154
Inte
rface
Pro
toty
pe
Experim
ente
r In
terfa
ce
Follo
ws S
cript
Wizard of Oz
Can be used with Cards or
Hi-Fi prototype
MSc CS: Intro. to HCI 2016-17 155 155
Compromises
All prototypes involve compromises That’s the point!
For software-based prototyping maybe there is a slow response? sketchy icons? limited functionality?
Two common types of compromise ‘horizontal’:
provide a wide range of functions, but with little detail
‘vertical’:
provide a lot of detail for only a few functions
Focus prototype where there is value
Compromises in prototypes mustn’t be ignored.
Final product still needs engineering
MSc CS: Intro. to HCI 2016-17 156 156
Hi-Fi Disadvantages
Distort perceptions of the tester:
Formal representation indicates “finished” nature
E.g People comment on colour, fonts, and alignment
Discourages major changes:
Testers don’t want to change a “finished” design
Designers don’t want to lose effort put into
creating the hi-fi design
27
MSc CS: Intro. to HCI 2016-17 157 157
Down-sides to informal design
Clients
Often see the fidelity of the interface as an indication of development effort
Often hard to involve them as subjects
Talk to them early and often!
Explain the process and set expectations up front!
MSc CS: Intro. to HCI 2016-17 158 158
Summary
Different kinds of prototyping are used for different purposes and at different stages Prototypes answer questions so prototype appropriately and be clear why you are
building it
Construction: the final product must be engineered appropriately Conceptual design (the first step of design) Consider interaction types and interface types to prompt creativity
Storyboards can be generated from scenarios Card-based prototypes can be generated from use cases
MSc CS: Intro. to HCI 2016-17 159
Some quick techniques!
‘Steal’ some screenshots
Use a paint/draw package to customize
Use tools like powerpoint to ‘glue’ it
together
Screens
Sequences
159 MSc CS: Intro. to HCI 2016-17 160 160
Start with a Blank Page
MSc CS: Intro. to HCI 2016-17 161 161
Use a drawing program to insert items you want
Be experimental ... But don’t get too carried away by bad taste!
Remember that you will evaluate this later
MSc CS: Intro. to HCI 2016-17 162 162
Useful Tricks
Print Screen and then cut out elements you like Windows: Alt-PrntScrn captures the active window into
the clipboard Mac OSX Grab Utility Android
Use a simple graphics editor like Paint to stitch the images together Copy & Paste many elements for different looks/feels
28
MSc CS: Intro. to HCI 2016-17 163 163
PowerPoint/Web-Based
Provides the illusion of interactivity
Can employ screenshots to show parts of your webpage
Can be used as just a “click-through” of
screenshots
MSc CS: Intro. to HCI 2016-17 164 164
Resources
http://www.krisjordan.com/2008/09/07/10-minute-mock-prototyping-tips-for-powerpoint/
http://www.istartedsomething.com/20071018/ Demo Program
Balsamiq: http://www.youtube.com/watch?v=zLysy3IPfFI
http://www.krisjordan.com/2008/09/07/10-minute-mock-prototyping-tips-for-powerpoint/
http://www.istartedsomething.com/20071018/ Demo Program
Balsamiq: http://www.youtube.com/watch?v=zLysy3IPfFI
MSc CS: Intro. to HCI 2016-17 165
Remember: Aims of prototyping
To evaluate alternative solutions:
Quickly
Cheaply
Focus:
Broad but shallow
Deep but narrow
Prototypes may be:
Disposable
Evolving
Purpose: To understand requirements
To understand design
To understand technology
Make mistakes early and cheaply!
MSc CS: Intro. to HCI 2016-17 166 166
Lecture 11&12
User Interface evaluations:
What are they and why do them?
When: Throughout the design phase
At the end
How: By inspection
By experiment
MSc CS: Intro. to HCI 2016-17 167 167
Why Evaluate?
Evaluation is important:
To compare design choices:
to assist us in making decisions
To determine how usable the system is (possibly, for different user groups):
So it can be improved
To identify good and bad features:
to inform future design
To understand what makes a good interface
To understand principles, science, behaviour …
MSc CS: Intro. to HCI 2016-17 168
Compare this with software testing
Evaluate & test as you build: Including prototypes
Test the completed product: Does it work?
Reflect on what is produced and how: Do it better next
time
There are always multiple dimensions: Correctness, efficiency,
reliability …
Cannot be exhaustive: Focus where return is
greatest
Compare: ‘synthetic’ test
‘real world’ test
Methods may differ but aim is the same!
29
MSc CS: Intro. to HCI 2016-17 169
Unit testing Integration
testing
Alpha testing
Prototype1 prototypen Product
Development process
So, we have an iterative process:
•Identify purpose
•Design prototype
•Build
•Evaluate
•Learn lessons
MSc CS: Intro. to HCI 2016-17 170
How to organise your evaluations
Evaluation is expensive: Focus where it is
most: Valuable
Easily/cheaply undertaken
Real users are expensive & elusive: Use wisely &
economically
Evaluate at all stages:
Analysis
Design
Implementation
Delivery
Catch mistakes early:
Especially the big ones!
So: Think & plan
MSc CS: Intro. to HCI 2016-17 171
What are we interested in?
Five aspects of usability:
Learnability: ease of learning especially for novice users.
Efficiency: steady-state performance – particularly of expert users. How efficiently can they do their job.
Memorability: ease of using system intermittently for casual users.
Errors: error rate for both
minor and serious errors.
Subjective Satisfaction:
Do they like it?
This may not be
comprehensive, but:
all of these are important
The balance between them
will vary!
MSc CS: Intro. to HCI 2016-17 172
Requirements for evaluation
Be clear what you want to learn: Focus on important
parts of design
Focus on important aspects of design
Devote appropriate resources
Make lessons explicit
For instance:
Aircraft display: Low error rates, efficient
Learnability, memorability & satisfaction are less important
Ecommerce site: Learnability, satisfaction,
memorability are crucial
Error rates, efficiency are less critical
MSc CS: Intro. to HCI 2016-17 173 173
Evaluation Methods
There are very many techniques for evaluating interfaces
Broadly, they can be divided into: Inspection Methods
Testing/experimental methods But, this division is not a
hard one.
Degree of rigour can be varied
Inspection methods:
No users needed! May be informed by
Personas & scenarios
Heuristic evaluations
Walkthroughs
Others
User Testing/experiment:
Users needed
Usability tests
Empirical: Observe
Measure
Analyse
Hard & expensive
MSc CS: Intro. to HCI 2016-17 174
Planning evaluations
It’s critical to decide,
upfront:
What attributes are important:
Their relative importance
E.g. learnability > efficiency > error rates
For instance, compare a flight booking system:
For travel agents
For end-users
30
MSc CS: Intro. to HCI 2016-17 175
Cost of evaluations
In early stages, evaluations must be:
Fast
Cheap
And they don’t need to be perfect
[We’re evaluating prototypes!]
For the final product:
Effectiveness, reliability, completeness are more important
So, we’re prepared to spend more time and effort
MSc CS: Intro. to HCI 2016-17 176
Inspection Methods
Inspection methods
Heuristic Evaluation:
Nielsen’s Heuristics
How to do it
Effectiveness of inspection methods
MSc CS: Intro. to HCI 2016-17 177 177
Inspection Methods
Methods that are based on inspections:
Heuristic evaluation
Heuristic estimation
Cognitive walkthrough
Feature inspection
Standards inspection
Pluralistic walkthrough
Consistency inspection
Formal usability inspection
MSc CS: Intro. to HCI 2016-17 178 178
Heuristic evaluation (what is it?)
Method for finding usability problems
Popularized by Jakob Nielsen
“Discount” usability engineering:
Use with working interface or prototypes
Convenient
Fast (cheap!)
Easy to use
MSc CS: Intro. to HCI 2016-17 179
Systematic inspection to see if interface complies to guidelines Driven by Heuristics (Rules of thumb)
Method: Typically, 3-5 inspectors
usability engineers, end users, double experts…
Inspect interface independently (~1–2 hours for simple interfaces) Compare notes afterwards
single evaluator only catches ~35% of usability problems
5 evaluators catch ~75%
Works for paper, prototypes, and working systems
179
Heuristic evaluation
Eval: 1 2 3 5 10
Teledata 51% 71% 81% 90% 97%
Mantel 38% 52% 60% 70% 83%
Savings 26% 41% 50% 63% 78%
Transport 20% 33% 42% 55% 71%
MSc CS: Intro. to HCI 2016-17 180
# Evaluators 1 2 3 5 10
Teledata 51% 71% 81% 90% 97%
Mantel 38% 52% 60% 70% 83%
Savings 26% 41% 50% 63% 78%
Transport 20% 33% 42% 55% 72%
31
MSc CS: Intro. to HCI 2016-17 181
Why do this?
We need to understand the performance of our prototypes:
To fix them
To guide decisions
However:
A full experimental evaluation would be too expensive & take too long
The system is, in any case, incomplete & ‘rough’
So, use methods that are good enough & quick enough: This applies even when the
system is finished: catch ‘obvious’ errors
fix
Then test rigourously
MSc CS: Intro. to HCI 2016-17 182 182
Points of Variation
Evaluators
Heuristics used
Method employed during inspection
MSc CS: Intro. to HCI 2016-17 183 183
Evaluators
These people can be novices or experts
“novice evaluators”: Often domain experts
“regular specialists”: Usability experts
“double specialists”: Domain & usability experts
Each evaluator finds different problems
The best evaluators find both hard and easy problems
MSc CS: Intro. to HCI 2016-17 184 184
Heuristics
Heuristics are rules of thumb that are used to inform/guide the inspection…
There are many alternative heuristic sets:
Nielsen’s
MSc CS: Intro. to HCI 2016-17 185 185
Nielsen's Heuristics
1. Visibility of system status
2. Match between system & real world
3. User control and freedom
4. Consistency & standards
5. Error prevention
6. Recognition rather than recall
7. Flexibility & efficiency of use
8. Minimalist design
9. Help error recovery
10.Help & documentation
MSc CS: Intro. to HCI 2016-17 186 186
1. Visibility of system status
Show what the system is doing:
How long it will take
What mode it is in
Make it clear when the system is waiting for user action
…..
searching database for matches
32
MSc CS: Intro. to HCI 2016-17 187 187
Aside: What is “reasonable time”?
0.1 sec: Feels immediate to the user. No additional feedback
needed. But not for some things!
1.0 sec: Tolerable, but doesn’t feel immediate. Some feedback
needed.
10 sec: Maximum duration for keeping user’s focus on the action.
For longer delays, use (for instance) %-done progress bars.
MSc CS: Intro. to HCI 2016-17 188 188
2. Match between the system and the real world
Make sure the system’s model matches the user’s – or make the system’s clear
Socrates: Please select command mode
Student: Please find an author named Octavia Butler.
Socrates: Invalid Folio command: please
For instance, don’t use
language that you
cannot accept as input:
•Mirroring
MSc CS: Intro. to HCI 2016-17 189 189
3. User control and freedom
Guidance is useful, but don’t over constrain:
Allow flexibility
Don’t force users to take a particular path:
e.g. Provide (useful) exits for mistaken choices Don’t force abort & restart
Enable:
undo
redo
MSc CS: Intro. to HCI 2016-17 190 190
4. Consistency and standards
MSc CS: Intro. to HCI 2016-17 191 191
5. Error prevention
People will make errors.
Design to prevent/reduce them:
How might you go about trying to prevent errors?
MSc CS: Intro. to HCI 2016-17 192 192
5. Error prevention
People will make errors.
Design to prevent/reduce them:
How might you go about trying to prevent errors?
Menus
Grey out invalid choices
Radio buttons
Calendar popups
E.g flights to Birmingham, Lagos …..
33
MSc CS: Intro. to HCI 2016-17 193 193
6. Recognition rather than recall
Minimise load on user’s memory:
Menus vs Commands E.g select country code rather than type it
Display format/options next to text box
Carry over/display information from different parts of dialogue
MSc CS: Intro. to HCI 2016-17 194 194
7. Flexibility and efficiency of use
Is usage as efficient as possible?
Consider:
Keyboard accelerators
Macros & keyboard macros
Recently used file list
…..
MSc CS: Intro. to HCI 2016-17 195 195
8. Aesthetic and minimalist design
Keep it simple!
MSc CS: Intro. to HCI 2016-17 196 196
9. Help users recognize, diagnose, and recover from errors
SEGMENTATION VIOLATION! Error #13
ATTEMPT TO WRITE INTO
READ-ONLY MEMORY!
Error #4: NOT A TYPEWRITER
MSc CS: Intro. to HCI 2016-17 197 197
10. Help and documentation
MSc CS: Intro. to HCI 2016-17 198
Remember ….
Not all heuristics will be, necessarily, relevant
Different applications will have different priorities
Some of these dimensions will conflict
So, we need to be clear about:
Who the users are
Their context
Their motivation
….
… and drive
evaluation accordingly
34
MSc CS: Intro. to HCI 2016-17 199 199
We should wonder…..
Is this a sensible heuristic set?: Coverage
Uniqueness
Ease of use
There are others: Some focused on a domain
but this set is widely used!
MSc CS: Intro. to HCI 2016-17 200 200
Phases of a heuristic evaluation
Pre-evaluation training - give evaluators needed domain knowledge and information on the scenario
Evaluate interface independently
Rate each problem for severity
Aggregate results
Debrief: Report the results to the interface designers
MSc CS: Intro. to HCI 2016-17 201 201
Severity ratings
Each evaluator rates individually: 0 - don’t agree that this is a usability problem
1 - cosmetic problem
2 - minor usability problem
3 - major usability problem important to fix
4 - usability catastrophe imperative to fix
Consider:
Impact
Frequency
MSc CS: Intro. to HCI 2016-17 202 202
Styles of Heuristic evaluation
Problems found by a single inspector
Problems found by multiple inspectors
Individuals vs. teams
Goal or task?
Structured or free exploration?
MSc CS: Intro. to HCI 2016-17 203 203
Empirical studies of effectiveness of heuristics
Problems found by a single inspector:
Averaged over six case studies:
35% of all usability problems
42% of the major problems
32% of the minor problems
Whilst not perfect:
Finding some problems with one evaluator is
much better than finding no problems with no evaluators!
MSc CS: Intro. to HCI 2016-17 204 204
Problems found by a single inspector
Varies according to difficulty of the interface being evaluated the expertise of the inspectors
Average problems found by: novice evaluators - no usability expertise - 22% regular specialists - expertise in usability - 41% double specialists - experience in both usability and the particular
kind of interface being evaluated - 60%: also find domain-related problems
Tradeoff: novices less good:
but cheaper!
35
MSc CS: Intro. to HCI 2016-17 205 205
Problems found by a single inspector
Evaluators miss both easy and hard problems: ‘best’ evaluators can miss easy problems ‘worst’ evaluators can still uncover hard problems
MSc CS: Intro. to HCI 2016-17 206 206
MSc CS: Intro. to HCI 2016-17 207 207
Problems found by multiple evaluators
3-5 evaluators find 66-75% of usability problems:
different people find different usability problems
only modest overlap between the sets of problems found
MSc CS: Intro. to HCI 2016-17 208 208
Problems found by multiple evaluators
Where is the best cost/benefit?
Obviously, this
is case
dependent!
MSc CS: Intro. to HCI 2016-17 209 209
Individuals vs. teams
Nielsen:
recommends individual evaluators inspect the interface independently
Why?
evaluation is not influenced by others
independent and unbiased
greater variability in the kinds of errors found
no overhead required to organize group meetings
MSc CS: Intro. to HCI 2016-17 210 210
Self Guided vs. Scenario Exploration
Self-guided: open-ended exploration Not necessarily task-directed
good for exploring diverse aspects of the interface, and to follow
potential pitfalls
Scenario driven: step through the interface using representative end user tasks ensures problems identified in relevant portions of the interface ensures that specific features of interest are evaluated
but limits the scope of the evaluation - problems can be missed
36
MSc CS: Intro. to HCI 2016-17 211 211
How useful are they?
Inspection methods are discount methods for practitioners. They are not rigorous scientific methods.
All inspection methods are subjective.
No inspection method can compensate for inexperience or poor judgment. They’re as good as the evaluators
Using multiple analysts results in an inter-subjective synthesis. However, this also
a) raises the false alarm rate, unless (e.g.) a voting system is applied
b) reduces the hit rate if a voting system is applied!
Group synthesis of a prioritized problem list seems to be the most effective current practical approach.
MSc CS: Intro. to HCI 2016-17 212
A recipe …..
Use several independent evaluators
Ensure evaluators understand purpose & scope
Ie. Plan, focus and direct!
Use personas & scenarios to drive evaluation
Collate and analyse results
Generate recommendations!
Remember: Finding problems with
systems is inevitable and acceptable: (maybe if they don’t exist
you are not trying hard enough!)
But not spotting them is NOT acceptable!
MSc CS: Intro. to HCI 2016-17 213
Remember
Problems can arise because of:
Mistakes:
You just got it wrong or it
works for you but not for the actual users
You are trying to be creative:
sometimes it doesn’t quite
work!
A good design for one user class may be bad for other classes
Compromise:
A good design from one
perspective may be bad from another
The aim of the evaluation is to be explicit about issues and what to do about them.
You can present results as a table:
Aspect Issue Severity Recommendation
System status
The ….
The …
0
5
Not an issue
Modify …
Match with real world
Also see:
•http://comminfo.rutgers.edu/~aspoerri/Teaching/InfoVisOnline/HEte
mplate.doc
•http://www.uxforthemasses.com/blog/wp-content/uploads/2011/02/Usability-review-template.xls
MSc CS: Intro. to HCI 2016-17 214
Summary
Inspection methods:
Can be very effective: They will catch many
problems
They are ‘cheap’ Quick, easy to undertake
They don’t require end-users
Find, say, 80% of problems quickly and cheaply Then devote other
methods to the harder problems
Using multiple evaluators improves coverage
Using personas & scenarios helps to focus on end-user needs
Works with early stage prototypes
Inform design decisions
MSc CS: Intro. to HCI 2016-17 215 215
Lecture 15
Usability Testing:
Motivation
To find problems
Methodologies
Data collection
Data analysis
Controlled experiments:
Experimental design
Participants
Variables
Data collection
Data analysis
interpretation
MSc CS: Intro. to HCI 2016-17 216
Usability Testing
Remember:
Inspection methods can identify problems:
Quickly
Cheaply
But they won’t find
everything!
Usability testing is:
Empirical testing
With users
To find usability problems
So they can be fixed
Compare with Software testing (e.g. alpha, beta …. testing)
37
MSc CS: Intro. to HCI 2016-17 217
Why do this?
The ultimate test!
Designers believe that they understand users
Designers understand what they have designed:
They find it easy, intuitive, reliable …. to use:
They are often wrong!
Conduct the test, collect the data, look at the results …
Sometimes you are very surprised (disappointed!)
MSc CS: Intro. to HCI 2016-17 218
So, how do we do this?
There are many approaches: Informal
Sit user down with system
Tell them to use it
Ask them what they think
Formal Controlled sets of users
Defined task
Video, record keystrokes, measure time, error rate etc.
Statistical analysis of data
And every stage between!
MSc CS: Intro. to HCI 2016-17 219
Problems with informal testing
Informal/subjective tests: May not be very reliable
(Typically) Short term – whereas usage may be long term
Users may be: Atypical
Too few
Subjective assessment is unreliable: Why?
Task & environment is artificial
But: Cheap(er)
Will uncover many problems
MSc CS: Intro. to HCI 2016-17 220
Problems with formal (controlled) testing
Very, very expensive: Time of:
Users (numbers required & duration)
Experimenters
Analysis
Often answer ‘small’ questions: Because of need to control experiment
But …. Can be very useful (or even essential) Safety critical applications
To establish principles!
MSc CS: Intro. to HCI 2016-17 221
So, where does this leave us?
As always, it’s a matter of balance: How important is
usability? What aspects are
important?
What resources can we devote? Costs
Timescales
User availability
There is a balance to be drawn between: Analysis
Validation of: Requirements
Design
Product
Use limited access to users most appropriately
Produce a plan!
MSc CS: Intro. to HCI 2016-17 222
Usability testing
Remember the purpose is to find problems:
So they can be fixed
Issues:
Who are the users?
Where & how is the testing done?
What data do we collect?
What do we do with the results?
38
MSc CS: Intro. to HCI 2016-17 223
Who are the users?
In early stages we will use atypical users: Students
Volunteers
Colleagues
And so on …
[But we still want them as typical, balanced etc. as possible]
And in artificial circumstances
Later:
Typical users
In realistic settings
MSc CS: Intro. to HCI 2016-17 224
Where and how?
In early stages:
In a (probably) non realistic setting
Use a script to define the context:
From user scenarios
Typically, short term use
Later:
Seek realistic usage
Move to a realistic environment
User takes initiative from environmental cues
Longer time scales
‘in the wild’ studies
MSc CS: Intro. to HCI 2016-17 225
Data
What is important?
Objective data:
Time taken, error rates, usage patterns and so on
Subjective data:
Is the user happy?
What were they thinking:
Mental model
Problems
The system can:
Log data:
Key strokes, mouse events, timings data
Video
Possibly with detailed analysis & annotation
Debrief/interviews
Questionnaires
MSc CS: Intro. to HCI 2016-17 226
Think Aloud
Often what the user is thinking is critical:
What is their ‘mental model’
Why did they do that?
What are they looking for
Some methods used:
Ask user to explain what they are doing as they do it:
Changes behaviour
Debrief/interview them afterwards
Using video of their usage
[Erikson & Simon 1985]
MSc CS: Intro. to HCI 2016-17 227
Eye tracking
Where is the user looking and when?
Screen design
Movement around screen:
Searching, reading etc
MSc CS: Intro. to HCI 2016-17 228
Questionnaires – a quick way
to collect useful data
Personal/demographic data Domain expert?
Technical expertise & experience
Age, sex, impairments etc
Subjective assessment Easy to use?
Attractive?
Things I liked
Things I disliked
Changes I would make
For each task:
Was the task completed?
How long?
Any errors?
If it was not completed:
Why?
Try to use an existing
questionnaire!
• Why?
39
MSc CS: Intro. to HCI 2016-17 229
Why use an existing Questionnaire
It’s easy to create a
questionnaire
Paper
On-line e.g. survey monkey
It’s hard to create a
useful one
Existing questionnaires are:
Trialled and validated
The interpretation of the results is understood
You can augment an existing tool by adding to it:
At the end.
MSc CS: Intro. to HCI 2016-17 230
System Usability Score (SUS)
To calculate the SUS score
first sum the score contributions from each item. Each item's score contribution will range from 0 to 4.
For items 1,3,5,7,and 9 the score contribution is the scale position minus 1.
For items 2,4,6,8 and 10, the contribution is 5 minus the scale position.
Multiply the sum of the scores by 2.5 to obtain the overall value of SU.
SUS scores have a range of 0 to 100.
http://www.usabilitynet.org/trump/documents/Suschapt.doc
MSc CS: Intro. to HCI 2016-17 231
Computer System Usability Questionnaire
http://oldwww.acm.org/perlman/question.cgi?form=CSUQ
MSc CS: Intro. to HCI 2016-17 232
How to conduct usability testing
Produce a plan: Objectives:
What are you trying to evaluate?
Identify focus
Method: How will you conduct
it?
How will you collect data?
How will they be analysed?
Always pilot
Make it clear to user:
Purpose
Tasks
Make conclusions/lessons
explicit
MSc CS: Intro. to HCI 2016-17 233
A recipe
Load user resources up front: UI requirements
Development of personas & scenarios
Use personas to drive: Analysis
Design
Testing
Use heuristic evaluations
Use personas to drive testing with usability ‘experts’
Use non-domain users to test general usability
Use typical users when confident
Assessment:
Collect data
Identify lessons!!!!
MSc CS: Intro. to HCI 2016-17 234
Overall lessons
Think, define objectives, plan, analyse
Load effort towards early stages Inspection methods
Atypical users
Real usage
Catch errors as early & cheaply as possible Only use more expensive methods when you are
confident
Be honest & learn lessons Remember, you are doing this to find problems!
40
MSc CS: Intro. to HCI 2016-17 235
Lecture 16
Controlled Experiments
MSc CS: Intro. to HCI 2016-17 236
Controlled experiments
This is concerned with empirical evaluation of system use by users.
A more scientific study with controlled conditions:
Users
Variables
Statistical analysis
Interpretation of results
Define objectives
Define hypotheses? What are we trying to do?
Uncover problems?
Reliably compare conditions?
Etc.
Define scope, focus, objective of evaluation
Design experiment
Conduct experiment: Collect data
Analyse data
Draw conclusions
MSc CS: Intro. to HCI 2016-17 237
Experiment Design
Determine design: What you need to test:
What is the research question?
Performance/ satisfaction etc
This leads to a set of hypotheses
How you will measure it: Data collection
Pilot experiments
Conduct experiments
The problem is:
Short term vs long term
Actual performance vs subjective views
Control of experiment
Etc etc.
Pre-study data collection
In-study data collection:
Observe
Think-aloud
Track
Post-study data collection
After each condition
At the very end
MSc CS: Intro. to HCI 2016-17 238
Hypotheses
You cannot really draw conclusions unless you are clear, in advance, what you are trying to
test.
Define hypothese e.g.
H1: in condition 1 users will complete their task faster than condition 2
H2: in condition 1 users will be more satisfied with the system than in condition 2
H3: in condition 1 the user will learn more than in condition 2
MSc CS: Intro. to HCI 2016-17 239
Experimental Conditions
Typically we want to establish: 2 or more experimental
conditions This defines the
independent (or controlled) variables
E.g. interface 1 or interface 2
As far as possible, the two conditions should be identical Except for the defined
point of variation
The dependent (or measured) variables are the things that we expect to measure (the effects). E.g. Speed
Effectiveness
Error rate
And so on
MSc CS: Intro. to HCI 2016-17 240
Users
Users are a major point of variation
Because they vary!
Subjects:
Between subjects
Each user experiences only one condition
Within subjects
Each user experiences each (or several) conditions
41
MSc CS: Intro. to HCI 2016-17 241
Within Subjects
This reduces variation:
Because the user is the same between conditions
But there could be
ordering and other confounding effects
Counterbalancing helps to reduce this effect:
User 1: C1 C2
User 2: C2 C1
MSc CS: Intro. to HCI 2016-17 242
Between subjects
Each user only experiences one condition:
No carry over effects
Cannot directly compare C1/C2 for an individual
Large individual variation
Balance users in each condition:
Age, sex etc
Pre-test scores
To try to have comparable populations in each condition
MSc CS: Intro. to HCI 2016-17 243
Other things to watch out for
Experiments with people are very difficult:
Individual variations
Biases
e.g.
Blind, double blind, triple blind studies
Why must all clinical trials be registered beforehand?
Hawthorn effect
Placebo effects
………
MSc CS: Intro. to HCI 2016-17 244
Data
As with usability testing:
Time to complete task
Error rate
Questionnaires Satisfaction
Others
Etc.
What can we do:
Observe But in an objective way
Measure errors
Measure time to complete task
Measure achievement What is the objective of
system? Change behaviour? Change
attitudes? Learn something?
Debrief users: Discussion
Questionnaires
……….
MSc CS: Intro. to HCI 2016-17 245
Data analysis
We have to undertake a (sensible!) statistical analysis of the data:
Driven by the hypotheses
Then we can (possibly):
Conclude that the hypotheses are true
At a certain confidence level
Of course, the important thing is:
The interpretation that you put on the results:
Assumptions
Limitations
MSc CS: Intro. to HCI 2016-17 246
Summary
Usability testing aims to find problems
Controlled experiments aim to answer a question: This may be a scientific
question or just a comparison between two interfaces.
They are hard (and expensive) to design and undertake.
They, typically, answer small, detailed questions
There are many pitfalls in designing, undertaking and interpreting these experiments.
See: www.nejm.org/doi/ful
l/10.1056/NEJM1991
04043241418
42
MSc CS: Intro. to HCI 2016-17 247 247
Lecture 17 & 18
User Interface Design Designing Systems that work for People
Important ideas in design: Metaphor
Interaction model
Affordances
What is important to guide your design: Principles
Guidelines
Standards
MSc CS: Intro. to HCI 2016-17 248 248
So how do I design?
MSc CS: Intro. to HCI 2016-17 249
Remember: criteria
Learnability
Efficiency
Memorability
Error rates/reliability
Satisfaction
We want to:
Maximise all of these
They often conflict
So:
Balance is problem specific
MSc CS: Intro. to HCI 2016-17 250
Designing for usability
Most of this is easy to dismiss as ‘common sense’
….. But many designers do not do this!
There is a ‘craft skill’ here
But look at examples, guidelines etc. To learn how to do it:
Compare to good software design!
MSc CS: Intro. to HCI 2016-17 251
Some important ideas
Interface metaphors
Where does the dialogue initiative lie?
Affordances
MSc CS: Intro. to HCI 2016-17 252 252
Interface Metaphors
Interface metaphors combine familiar knowledge with new knowledge in a way that will help the user understand & use the system:
Build a consistent mental model of system.
Three steps:
understand functionality
identify potential problem areas
generate metaphors
Evaluate metaphors:
How much structure does it provide?
How much is relevant to the problem?
Is it easy to represent?
Will the audience understand it?
How extensible is it?
So, we have obvious examples like:
Desktop
Video controls
Filing systems
Touch controls
These build on our existing knowledge to allow us to predict how the interface will work
Without having to explicitly
learn
43
MSc CS: Intro. to HCI 2016-17 253
Examples
MSc CS: Intro. to HCI 2016-17 254
UI Metaphor
Aim to build on existing knowledge
Easy to learn & predict behaviour
Compare:
Metaphor
Skeuomorphism
Analogy
Metonymy
Consider a slider for volume control:
MSc CS: Intro. to HCI 2016-17 255
Metaphors: summary
Using a metaphor is a good idea:
Improves learnability & memorability
Can improve performance
Can build on known good design
Dangers:
Metaphor is incomplete/breaks down:
Trash can
Conflicting cues
Bad slider!
May not work for all users
Can maintain inefficient use:
VR, search …
MSc CS: Intro. to HCI 2016-17 256 256
Interaction Models
Which interaction type?
How the user invokes actions
Instructing, conversing, manipulating or exploring
Do different interface types provide insight?
WIMP, shareable, augmented reality, etc
Initiative: System/User/Mixed
Think about what model is right:
Should the system always structure the dialogue?
Should the user have complete freedom to do what they want?
MSc CS: Intro. to HCI 2016-17 257
Affordances
A common principle across all design disciplines
Make it obvious what to do and what is possible:
No need to learn
Architects (e.g.) apply this:
Door handle vs door plate
Buttons, knobs, sliders …
MSc CS: Intro. to HCI 2016-17 258
44
MSc CS: Intro. to HCI 2016-17 259
Affordances
Like with metaphors, this builds upon people’s intuitions:
They show what is possible
They cue behaviour
Can improve learnability & performance
Conflicting affordances & unfilled affordances have a negative effect
MSc CS: Intro. to HCI 2016-17 260
Summary
All these can improve performance
If used properly
They can also be used to feedback the result of actions
Metaphors & affordances can be:
At various levels of abstraction
MSc CS: Intro. to HCI 2016-17 261 261
Construction
Taking the prototypes (or learning from them) and creating a whole
Quality must be attended to:
usability, reliability, robustness, maintainability, integrity, portability, efficiency, etc.
Product must be engineered:
Evolutionary prototyping
‘Throw-away’ prototyping
MSc CS: Intro. to HCI 2016-17 262
How can we do this?
Principles
Guidelines
Standards
Examples:
Nielson
Shneiderman
Norman
MSc CS: Intro. to HCI 2016-17 263 263
Design rules
Designing for maximum usability – the goal of interaction design
Principles of usability general understanding
Standards and guidelines direction for design
MSc CS: Intro. to HCI 2016-17 264 264
types of design rules
principles abstract design rules
low authority
high generality
guidelines lower authority
more general application
standards specific design rules
high authority
limited application increasing authority
inc
reas
ing
gen
era
lity
Standards
Guide lines
increasing authority
incre
asin
g g
en
era
lity
45
MSc CS: Intro. to HCI 2016-17 265 265
Principles to support usability
Learnability the ease with which new users can begin effective interaction and achieve maximal performance
Flexibility the multiplicity of ways the user and system exchange information
Robustness the level of support provided to the user in determining successful achievement and assessment of goal-directed behaviour
MSc CS: Intro. to HCI 2016-17 266 266
Principles of learnability (1)
Predictability
determining effect of future actions based on past interaction history and design metaphors & affordances
operation visibility
You can see what you might do (e.g. menu options with inappropriate options ‘greyed out’)
MSc CS: Intro. to HCI 2016-17 267 267
Principles of learnability (2)
Familiarity how prior knowledge applies to new system Guess-ability; affordance
Generalize-ability
extending specific interaction knowledge to new situations E.g. carry across from parts of this or other systems
Consistency
likeness in input/output behaviour arising from similar situations or task objectives
MSc CS: Intro. to HCI 2016-17 268 268
Principles of flexibility (1)
Dialogue initiative freedom from system imposed constraints on input dialogue
system vs. user initiative
Multi-threading ability of system to support user interaction for more than one
task at a time
concurrent vs. interleaving; multimodality
Task migrate-ability passing responsibility for task execution between user and
system E.g. delegate task to system (spell check?)
MSc CS: Intro. to HCI 2016-17 269 269
Principles of flexibility (2)
Substitutivity
allowing equivalent values of input and output to be substituted for each other
E.g. different (but equivalent) input/output formats
Different ways to perform the same task
Customizability
modifiability of the user interface by user (adaptability) or system (adaptivity)
MSc CS: Intro. to HCI 2016-17 270 270
Principles of robustness (1)
Observability ability of user to evaluate the internal state of the
system from its perceivable representation Browse-ability; defaults; reach-ability; persistence;
operation visibility I.e. see what is going on without changing anything
Recoverability
ability of user to take corrective action once an error has been recognized
forward/backward recovery
46
MSc CS: Intro. to HCI 2016-17 271 271
Principles of robustness (2)
Responsiveness
how the user perceives the rate of communication with the system
Stability
Task conformance
degree to which system services support all of the user's tasks
task completeness; task adequacy
MSc CS: Intro. to HCI 2016-17 272 272
Standards
Set by national, international bodies or manufacturers to ensure compliance by a large community of designers. Standards require sound underlying theory and slowly changing technology
Hardware standards more common than software high authority and low level of detail
ISO 9241 defines usability as effectiveness, efficiency and satisfaction with which users accomplish tasks
MSc CS: Intro. to HCI 2016-17 273 273
Guidelines
more suggestive and general
many textbooks and reports full of guidelines
abstract guidelines (principles) applicable during early life cycle activities
detailed guidelines (style guides) applicable during later life cycle activities
understanding justification for guidelines aids in resolving conflicts
MSc CS: Intro. to HCI 2016-17 274 274
Golden rules and heuristics
“Broad brush” design rules
Useful check list for good design
Better design using these than using nothing!
Different collections e.g.
Nielsen’s 10 Heuristics
Shneiderman’s 8 Golden Rules
Norman’s 7 Principles
MSc CS: Intro. to HCI 2016-17 275 275
Nielsen's Heuristics
1. Visibility of system status
2. Match between system & real world
3. User control and freedom
4. Consistency & standards
5. Error prevention
6. Recognition rather than recall
7. Flexibility & efficiency of use
8. Minimalist design
9. Help error recovery
10.Help & documentation
MSc CS: Intro. to HCI 2016-17 276 276
Shneiderman’s 8 Golden Rules
1. Strive for consistency:
• Make sure that menu structures, terminology, actions etc. are consistent
2. Design for all users:
1. Support novice users: • E.g. tool tips
2. Enable frequent users to use shortcuts:
• Allow expert users to work more quickly: keyboard accelerators, macros etc.
3. Offer informative feedback:
• Make sure state is clear and provide feedback on actions
4. Design dialogs to yield closure:
• Organise actions with a clear structure and signal completion
5. Offer error prevention and simple
error handling:
• Aim to prevent errors, if they
happen then detect & signal and
offer a way forward
6. Permit easy reversal of actions:
• Undo, redo etc
7. Support internal locus of control:
• Give control & flexibility to user –
let them think they are in control!
8. Reduce short-term memory load:
• Keep it simple: reduce context
switching, display as much as you
can …
47
MSc CS: Intro. to HCI 2016-17 277 277
Norman’s 7 Principles
1. Use both knowledge in the world and knowledge in the head.
• Understand the user’s conceptual model and build to match that
2. Simplify the structure of tasks.
• Make it obvious what is going on, give feedback …
3. Make things visible: • Make functions, options,
state etc. visible to user
4. Get the mappings right: • For instance build on a
metaphor
5. Exploit the power of constraints, both natural and artificial:
• Make it easy to do it right and hard to do it wrong
6. Design for error: • Try to reduce the chances of
errors – but if they happen help recovery (e.g. undo)
7. When all else fails, standardize.
• At the very least, design consistently and follow guidelines or standards.
MSc CS: Intro. to HCI 2016-17 278
Summary
These heuristics are useful: To guide design
To evaluate designs
They have different origins: Analysis of usability
problems – Nielsen
Experience – Shneiderman
Human behaviour - Norman
If you use these (in some way) you will produce better designs
Remember, these are often conflicting:
So, explicitly think about where the balance should lie
Draw upon these rules, as appropriate
MSc CS: Intro. to HCI 2016-17 279
Lecture 19
Guest Lecture
Paul Englefield
[Slides]
Paul is a consultant usability engineer. Most recently at IBM providing consultancy services to corporate clients.
Paul will present some case studies of the work they have undertaken and will relate this back to methodologies, tools and techniques and also the challenges and obstacles that are faced.
MSc CS: Intro. to HCI 2016-17 280
Lecture 20
Guest Lecture
Charlie Pinder
[Slides]
MSc CS: Intro. to HCI 2016-17 281
Lecture 21
Guest Lecture
Andrew Howes
[Slides]
MSc CS: Intro. to HCI 2016-17 282
Lecture 22
Special cases
Disabilities
‘special’ users
Special Environments
Novel & emerging interaction methods
48
MSc CS: Intro. to HCI 2016-17 283
Special cases
Disabilities: Physical
Perceptual
Cognitive
Mental state Tiredness, anxiety etc.
Cultural Differences Language, culture
Age Groups: Children vs Adults vs
Elderly
These are not really special cases:
They can also inform design for ‘typical’
users
MSc CS: Intro. to HCI 2016-17 284 284
Users with disabilities
These represent extreme cases – but can inform design for normal users visual impairment screen readers, ALT tags, braille output
etc.
hearing impairment text communication, gesture, captions
physical impairment speech I/O, eyegaze, gesture, predictive
systems https://www.youtube.com/watch?v=0d6yIquOKQ0
speech impairment speech synthesis, text communication
dyslexia speech input, output
autism communication, education
Goal: Allow all users to have
access to software, information, tools
Consider: Users with no/slow data
connections/small screens/driving …
Noisy environments
Hands free situations – surgeons/lab. Workers ….
The clarity of language
….
MSc CS: Intro. to HCI 2016-17 285 285
… plus …
age groups older people e.g. disability aids, memory aids,
communication tools to prevent social isolation children e.g. appropriate input/output devices, involvement
in design process
cultural differences influence of nationality, generation, gender, race, sexuality,
class, religion, political persuasion etc. on interpretation of interface features
e.g. interpretation and acceptability of language, cultural symbols, gesture and colour
MSc CS: Intro. to HCI 2016-17 286
Potential Applications
There are many ways in which technology can help users: Directly overcoming
obstacles
Enabling communication, participation etc.
Sensing & inferring
Applications: Assistive technology
Overcome physical, sensory & cognitive limitations
Medical Sense biometric
features & infer state Physical and other
Social Enable interaction
MSc CS: Intro. to HCI 2016-17 287
Some examples
Sensing & prediction
Gesture input
Brain Computer Interfaces
MSc CS: Intro. to HCI 2016-17 288
Sensing
We collect data:
Directly through computer mediated communication, typing
Wearables Including ‘phones
Cameras, microphones
Special devices
These can be used to infer:
Physical state
Affective states: Moods, emotions etc.
[Build models of user]
And predict: Behaviour
Goals, desires
… and therefore build better systems
Adapt the system ….Or to design
interventions To change behaviour
49
MSc CS: Intro. to HCI 2016-17 289
Handsfree use
There are many cases where users cannot use convention interaction devices:
Sterile environments
Operating theatres
Food preparation
Remote operation:
Vehicles
Construction equipment
Gesture control is one way in which this can be addressed:
https://www.youtube.com/watch?v=f5Ep3oqicVU
MSc CS: Intro. to HCI 2016-17 290
Brain Computer Interfaces
What if a user is profoundly disabled?
What if gesture is impractical?
BCI can be used as:
An input device:
External
Implants
As an output device:
To stimulate parts of the brain
Visual
Aural
others
MSc CS: Intro. to HCI 2016-17 291
Brain Computer Interfaces: Control
Uses a headset to measure brain activity
Interprets data into commands
Controls external device (robot)
Or wheelchair, assistive robot ….
https://www.youtube.com/watch?v=0d6yIquOKQ0?v=xhrmjsjK0pU
MSc CS: Intro. to HCI 2016-17 292
Brain Compter Interfaces: Evaluation
This can be done at different levels:
Motor
Cognitive
Affective
Could allow control of:
Wheelchairs
Aircraft
etc
Reliability is an issue Training &
inaccuracy
Distractions
Safety critical situations
Cognitive load High levels of
concentration are needed
MSc CS: Intro. to HCI 2016-17 293
Lecture 21
Summary
Understand (some of) the way people work
Process of design
Understand user
Create (potential) solutions
Evaluate
Future
Conventional systems are still important
Ubiquitous computing On people’s terms
MSc CS: Intro. to HCI 2016-17 294
HCI Design
In this course we have introduced some of the issues of HCI & usability design (and, especially, a process for designing good systems) It’s all about people!
People in general
The potential users of the system Attributes
Goals & tasks
Constraints
[and many other things]
50
MSc CS: Intro. to HCI 2016-17 295
The user
The first step is to understand our users: What they can do
What they want
Their tasks, constraints, motivations etc
Once this is done you can have some confidence in what you produce Prototype, check …. Catch mistakes and iterate
The last step is to check whether you have done this right!
MSc CS: Intro. to HCI 2016-17 296
So ….. ?
Work with users upfront
Identify requirements
Build personas & scenarios To help define
requirements
To guide design
To drive some evaluations
Build prototypes
Alternatives
Multiple stages
Evaluate: Ideally with real users
End users
Non-typical users
Against metrics
Using personas to guide
Iterate, refine and go deeper
Evaluate at all stages:
As best you can
It will always teach you something
Evaluate the final product:
Analytically
Experimentally
MSc CS: Intro. to HCI 2016-17 297
Usability engineering
This methodology is typical of all engineering disciplines
It is a matter of maximising benefits and minimising costs:
Work within the constraints:
Create an explicit plan
Evaluation & testing is a central part of this:
Be clear about goal, method, data & analysis
Feedback on requirements/ designs/products
Lessons!
MSc CS: Intro. to HCI 2016-17 298
Is that it?
The point of having this type of methodology is:
Work efficiently & cost effectively
Provide space to be:
Creative
Imaginative
Innovative
Radical
HCI has several faces:
Engineering
Creating new solutions as technologies and societies evolve:
This provides a framework where you can do that
MSc CS: Intro. to HCI 2016-17 299
Note
We have looked at some techniques: For the overall
process
For understanding users
For designing & building systems
For evaluating systems
There are many other techniques that can be used:
For different purposes
In different contexts
With different objectives
[and some we haven’t
looked at e.g. cognitive modelling]
MSc CS: Intro. to HCI 2016-17 300
Looking Ahead
HCI started as a discipline to facilitate people using computers:
This is still important
It has always been multidisciplinary
Now we have systems which are becoming:
Ubiquitous
Invisible
So the interaction is on people’s terms
… and these systems
can provide insights into how people work
51
MSc CS: Intro. to HCI 2016-17 301
Looking Ahead (2)
Systems have increasing amounts of data about users (think Google!): These can be used
to build models of the user
The system can adapt based on these models
So we can:
Have new applications:
Behaviour change, care, environment, entertainment …
Change the way we perform existing tasks
http://www.youtube.com/watch_popup?v=AklKy2NDpqs#t=12
http://www.youtube.com/watch_popup?v=Mgy1S8qymx0#t=73s
So we can:
Have new applications:
Behaviour change, care, environment, entertainment …
Change the way we perform existing tasks
http://www.youtube.com/watch_popup?v=AklKy2NDpqs#t=12
http://www.youtube.com/watch_popup?v=Mgy1S8qymx0#t=73s
MSc CS: Intro. to HCI 2016-17 302
The End.