1
Q
2 different metric types
A
observable + quantifiable
2
Q
3 common questions with metrics
A
- “Which metric shall I (we) use?”
- “How shall I (we) obtain the components needed to calculate it?”
- “Is this metric reliable enough to give a realistic picture of the degree to which my (our) system is usable (or not)?
3
Q
3 general metrics names
A
Performance Metrics
Issue-Based Metrics
Self-Reported Metrics
4
Q
9 performance metrics names
A
- Completion rate (task success, effectiveness)
- Task time
- Errors
- Efficiency (Page views/clicks)
- Lostness
- Conversion rate
- Learnability
- Eye-tracking
- Biometric data
5
Q
1 combined metric name
A
Single usability metric
6
Q
3 self-reported metric names
A
- Task-level satisfaction (self-report)
- Expectations
- Test-level satisfaction (self-report)
7
Q
1 issue-based metric name
A
Usability problems
8
Q
Performance metrics (there ae six of them)
A
- Task Success (Completion Rates)
- Binary Success
- Levels of Success - Time on Task
- Errors
- Effectiveness
- Efficiency
- Learnability
9
Q
Effectiveness formula explanation
A
- measure completion rate.
- fundamental usability metric/completion rate is calculated by assigning a binary value of ‘1’ if the test participant manages to complete a task and ‘0’ if he/she does not.
- average Task Completion Rate is 78%
10
Q
Effectiveness formula
A
(Number of tasks completed/Total number of tasks) X 100%
11
Q
Effectiveness example. 5 tasks and a user completes 3 of them.
A
3/5 X 100% = 60%
12
Q
3 Levels of success
A
Complete Success
Partial Success
Failure
13
Q
How to resolve a task when a user is not successful
A
Tell the users at the beginning of the session that they should continue to work on each task until they either complete it or reach the point at which, in the real world, they would give up or seek assistance (from technical support, a colleague, etc.).
14
Q
Time on task explanation
A
Time on task (sometimes referred to as task completion time or simply task time).
Caveat: Sometimes, slower is better
Ex: They are truly engaging with the website
15
Q
4 steps to make efficiency quantible
A
- Identify the action(s) to be measured
- Define the Start and end of an action
- Count the actions
- Actions must be meaningful
16
Q
Lostness formula
A
N: # of DIFFERENT webpages visited
S: total # of webpages (duplicate included)
R: minimum # of pages required to visit
L = sqrt(N/S-1)^2 +(R/N-1)^2
17
Q
2 types of rating scales
A
likert and semantic differential scales
18
Q
4 types of self-reported metrics
A
- Post-Task ratings
- Post session ratings
- using sus to compare designs
- online services
19
Q
Likert scale definition
A
5 point rating scale following:
1. Strongly disagree
2. Disagree
3. Neither agree nor disagree
4. Agree
5. Strongly agree
20
Q
Semantic Differential scales definition
A
Will have a scale with two values on each side. These two values will be opposites such as: weak and strong, ugly and beautiful, cool and warm. example below
weak o o o o o o o strong
21
Q
SUS meaning and definition
A
System Usability Scale - consists of a 10 item easy questionnaire with five response options for respondents; from Strongly agree to Strongly disagree
22
Q
10 questions used in SUS
A
- I think that I would like to use this system frequently.
- I found the system unnecessarily complex.
- I thought the system was easy to use.
- I think that I would need the support of a technical person to be able to use this system.
- I found the various functions in this system were well integrated.
- I thought there was too much inconsistency in this system.
- I would imagine that most people would learn to use this system very quickly.
- I found the system very cumbersome to use.
- I felt very confident using the system.
- I needed to learn a lot of things before I could get going with this system.
23
Q
CSUQ meaning and definition
A
Computer System Usability Questionnaire - has 19 questions about usability; from strongly disagree to strongly agree
24
Q
3 severity ratings
A
low, medium, high
25
low severity rating
Any issue that annoys or frustrates participants but does not play a role in task failure. These are the types Of issues that may lead someone of course, but he still recovers and completes the task. This issue may only reduce efficiency and/or satisfaction a small amount, if any.
26
medium severity rating
Any issue that contributes to significant task difficulty but does not cause task failure. Participants often develop workarounds to get to what they need. These issues have an impact on effectiveness and most likely efficiency and satisfaction.
27
high severity rating
Any issue that leads directly to task failure. Basically, there is no way to encounter this issue and still complete the task. This type of issue has a significant impact on effectiveness, efficiency, and satisfaction.
28
Self-reported metrics definition
Self-reported data give you the most important information about users’ perception of the system and their interaction with it. At an emotional level, the data may tell you something about how the users feel about the system
29
tasks that can be measured
Time on task, errors, efficiency, lostness, conversion rate, learnability, eye tracking, emotion, stress, phycological measures
30
3 usability statistics
1. effectiveness (can users successfully achieve their objectives)
2. efficiency (how much effort and resource is expended in achieving those objectives)
3. satisfaction (was the experience satisfactory)
31
what do sensor data streams test on?
a person, an environment, such as an office
and the home
32
questions in sensor data streaming
Where do people travel over the course of a day?
With whom do they normally communicate or collaborate?
What tools or information resources do they use at various points during the day? When, where, and with whom?
What routines help to define a “typical” or “atypical” day?
How healthy are a person’s daily behaviors? Is he or she making good health choices?
33
One advantage of using streams of data as a means of understanding people’s activities and behaviors is
that the technique can be used to answer research questions across a range of units of analysis
34
The 3 data streams are
egocentric, group-centric, and space-centric
35
Egocentric Sensor Data Streams
Sensors focused on monitoring the movements, activities, and interactions of a single individual can answer questions at an egocentric unit of analysis.
36
Egocentric data stream questions
How do people allocate their time or attention?
How is a person ’ s mental state or mood affected by real - world stimuli ?
How do electronic communications or mobile computing interactions affect daily routines?
How do people ’ s own understanding or interpretations of their activities , colleagues , or environment differ from what a ubiquitous computing application or tool is able to automatically sense ?
37
Group-Centric Sensor Data Streams
This group - centric approach can involve simply capturing the same signals as for a single person, but across a group over the same window of time, or it might involve deploying a broader set of environmental or infrastructural sensors in a shared/community space or collecting data about more interpersonal types of interactions
38
Group-centric data stream questions
How often do members of this group interact with one another ?
What do these interactions entail ?
How do power relations manifest in different kinds of work environments or work teams ?
39
Space-Centric Sensor Data Streams
Answer questions about how spaces are used, irrespective of their particular inhabitants, given appropriate instrumentation of a space.
High information density sensors
Low density sensors
40
Space-centric data stream questions
How are the occupants of a home spending their time throughout the day and night ?
Is a senior adult living by herself continuing to maintain healthy levels of physical activity ?
What is the impact of ambient feedback promoting environmental awareness on cooking , cleaning , and hygiene activities within different types of families ?
41
Sensor Data Streams and Context-Aware Computing
Context-aware computing is a form of interactive computing in which a user’s implicit behavior—that is, their location, their physical activity, or their interactions with other people—or the environment in which a system is being used can both serve as alternative or auxiliary inputs to the system.
42
limitations of sensor data streaming
1. poor job of why things have happened in the real world
2. The phenomena must be well understood
3. quality of data limited by sensors capabilities
4. select sensors to effectively capture quality data and minimize discomfort
5. large streams of data over moderate-length deployment.
6. sensors are technologically complex
43
7 things to report when using sensors
1. Hardware
2. Experimental setup
3. Participant knowledge
4. Experimental execution
5. Software infrastructure
6. Analysis
7. Why were these choices, and not others, made?
44
Eye tracking definition
Eye tracking is the process of measuring either the point of gaze (“where we are looking”) or the movement of the RETINA relative to the head.
45
What memory does eye tracking work in unison with?
working memory
46
Saccadic movements in eye tracking are
rapid, ballistic (pre-programmed) movements of the eyes that abruptly change the point of fixation. Effectively blind during these movements
47
Disadvantages of eye tracking?
Expensive
48
eye tracking is represented in:
scanpaths, saccades, fixations, and heatmaps
49
4 most important eye tracking methodologies
Accuracy
Reliability
Robustness
Non-intrusiveness
50
What are gestures?
A form of non-verbal communication.
A movement of part of the body, especially a hand or the head, to express an idea or meaning.
51
Implicit gestures
Non verbal
Used in place of or to augment speech
52
Gesture recognition
Interpreting human gestures via mathematical algorithms.
Gestures as input to control devices or applications.
53
Motivations for using gestures
Gesturing is a natural form of communication. Can be done while talking. Babies learn gestures before talking. Very innate in humans.
54
3 types of human gestures
1. Hand and arm gestures
2. Head and face gestures
3. Body gestures
55
4 considerations for using gestures
1. Environment
2. Real-time
3. Cost
4. Usability
56
2 types of computer recognized gestures
Offline gestures
Online gestures
57
Offline gesture and example
Processed after the user’s interaction with the object
Ex:- gesture to activate a menu.
58
Online gestures
Direct manipulations like scaling and rotating
59
Most important gesture usage and why?
Sign Language Recognition - Just as speech recognition can transcribe speech to text, certain types of gesture recognition software can transcribe the symbols represented through sign language into text.
60
General uses for gestures
sign language recognition, VR, aid to disabled
61
Challenges with gestures
1. Limited options
2. gestures aren't universal Ex: Peace sign here is a middle finger in England
3. Robustness - gestures are read wrong due to low lightning, background noise, etc
62
Gestures are heavily used in phones. What are some examples?
double tap, pinch, scroll, swipe, long press, etc
63
UIs in the Pervasive Computing Era
Future computing devices won’t have the same UI as current PCs. Alexas, VRs, no screens, etc
64
Motivations for using speech UI
1. Unlimited commands
2. Natural
3. Freedom for the rest of the body
4. people talk fast
5. small devices
65
4 scenarios when speech UI should be used?
1. Mobile
2. Hands-busy
3. Eyes-busy
4. Assistive Technologies
66
Limitations to speech UI
1. Not perfect -> 5-10% error rate
2. No visible state (no visible log of whats been done)
3. Can’t see effect of commands
4. Hard to learn
5. Can’t easily explore interface
6. spelling (male vs mail)
7. isolated words or segmentation
67
2 things speech UI require
speech recognition, and speech production
68
what to consider when designing speech UI
- give feedback
- simple hierarchies
- simple, quick feedback
- speech takes working memory
- create real conversation (interruptions are okay)
- include confirming commands
- give short errors at first
69
10 design guidelines for voice UI
1. show system status
2. real world concepts
3. user control and freedom
4. consistent standards
5. prevent errors
6. let users recognize not recall
7. flexible but efficient
8. minimal design
9. error recovery
10. help is given
70
Common voice activated triggers
voice, tactile, motion, device self-trigger
71
7 main parts to a leading cue (speech UI)
1. immediate
2. brief and transitory
3. clear beginning
4. consistent
5. distinct
6. supplementary cues
7. initial prompt
72
3 main parts to an ending cue (speech UI)
1. adequate time
2. adaptive time
3. reasonable pause
73
5 disadvantages of speech UIs
1. Disruptive
2. Privacy Concerns
3. Recognition Errors
4. Multiple Verbal Tasks (Interference)
5. Context Errors
74
7 Advantages of haptic UI
1. Users have a lot of sensitive skin.
2. Skin can map 2d display of environment continuously
3. visual representations can be recognized tactilely
4. inputs are simple and easy
5. another input modality. useful for the blind and the sighted
7. immersion
75
Uses for haptic UIs
video games, personal computers, mobiles, VR, simulators, robotics, training doctors, art, aviation, cars,
76
User studies inputs used in crowdsourcing
1. Surveys
2. rapid prototyping
3. usability tests
4. cognitive walkthroughs
5. performance measures
6. quantitative ratings
77
What is crowd sourcing and why is it used?
Makes tasks available for anyone online to complete and can quickly access a large user pool, collect data, and compensate users.
78
What is Amazon's Mechanical Turk and how is it used?
Used for human intelligent tasks such as finding an image, webpage, or relevance on search results. Pays the testers pennies on each task.
79
What is the best way to get amazon's mechanical turk to work?
Add simple, verifiable questions so you can tell if someone just put all 5s or if they were actually engaged and reading. You want cognitive presence.
80
Differences between traditional user studies and mechanical turk?
Traditional: complex, long, subjective opinions, targeted demographics, high interactivity
Turk: simple, short, object verifiable, unknown demographic, limited interactivity
81
Considerations for crowd sourcing?
1. Are the tasks suitable?
* Tradeoffs between online vs laboratory?
* Wages?
* How to ensure good results?
82
3 items to consider if crowdsourcing is appropriate:
1. Task complexity, subjectivity, and information to be collected
2. questions you want answered
3. data needed
83
Tradeoffs in crowdsourcing
1. no supervision = cheating
2. not much data collection
3. low cost
4. demogrpahics
5. quality work considerations
84
3 challenges of crowdsourcing
1. cost - not free
2. quality - cheating
3. latency - not real-time
85
Main factors in team performance
Teamwork, behavior, skills, attitudes, knowledge, leadership, performance monitoring, and adaptability/flexibility
86
Factor of team performance definition - # of members on a team
Team size
87
Factor of team performance definition - unique qualities possessed by a team
team competencies
88
Factor of team performance definition - way members of a team are organized
team structure and composition
89
Factor of team performance definition - distance between goals and motivations of any two team members
social distance
90
Factor of team performance definition - geophysical distance between any two team members (time-zone)
spatial distance
91
Factor of team performance definition - mechanism to maintain norms and coherence by minimizing expression of diverse characteristics of team members
Mutual support and surveillance
92
Factor of team performance definition - perception of one's leader and their authority
presence or absence of legitimate authority figures
93
Factor of team performance definition - measurement of leader's goals with team's motivations
task attractiveness
94
Factor of team performance definition - relationship between teams and tasks to be performed
team processes and tasks
95
what is microsofts hololens and how does it work?
Microsoft HoloLens is a smart glass which is the first cordless, self-contained holographic computer running on Windows 10.
Microsoft HoloLens is made up of specialized components that together enable Holographic Computing.
96
Virtual and augmented reality; what are they?
Virtual: Tricks eyes into being somewhere else
Augmented: changes the current scene to be changed by a dimensional layover
97
6 features of hololens?
1. camera
2. cpu
3. lenses
4. cooling vents
5. sensors
6. buttons
98
Hololens vs google glass
Google glass was design to perform the function of Smartphone. Google glass is VR not augmented reality
99
Other augmented reality technologies
Taste+, pre-touch, paperID, skintrack, inForm, Materiable, HoloFlex, WatchMI, etc
100
What is taste+?
changes the way things taste but using electrical charges in spoons or waterbottles
101
What is skintrack?
ring that puts a smartphone onto your whole arm and can sense actions based on touching the skin
102
5 stages of the gartner hype cycle
1. innovation trigger
2. peak of inflated expectations
3. trough of disillusionment
4. slope of elightenment
5. plateau of productivity
103
where is the HoloLens on gartner hype cycle?
I would say it is in the slope of enlightenment. Hololens 1.0 released and was a let down. But now HoloLens rumors have begun and how it will be improved to be productive.
104
What are some keywords for the future of HCI?
Sensing and Mobility
Augmented Human
Advanced AI and Analytics
Hyperautomation
Multiexperience
Transparency and traceability
The distributed cloud
Practical Blockchain
AI security
Autonomous things
105
What are some examples of the augmented human?
Neurolink that uses electric brain waves to use technology.
Exo skeletons - think cyberpunk
106
What are some examples of hyperautomation?
technology to automate tasks that once required humans.
Robotic process automation (RPA), intelligent business management software (iBPMS) and AI
107
what are some examples of multiexperience?
includes multisensory and multitouchpoint interfaces like wearables and advanced computer sensors (VR AND AR)
Domino’s Pizza created an experience beyond app-based ordering that includes autonomous vehicles, a pizza tracker and smart speaker communications
Human Computer Interaction
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