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HCI Test 3 > HCI Test 3 > Flashcards

HCI Test 3 Flashcards

1
Q

Arrange elements in one layer

A

(1) sequence if there is one
(2) functional groups (if there are)
(3) frequency then alphabetic order

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2
Q

Layout analysis

A

Arrangement of methods in one layer:

(1) group elements by their functions
(2) arrange functional groups according to their importance/sequence/frequency of usage

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3
Q

Pos and neg of layout analysis

A

+: easy to use, low cost

-: low reliability

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4
Q

Link analysis

A

Goal is to reduce the eye or motor movement distance on the interface

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5
Q

Pos and neg of link analysis

A

+: easy to use

-: ?

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6
Q

Types of UIs (3)

A

Command, graphic ui, multimodal (wearable)

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7
Q

Command interface advantages/disadvantages

A

+: lower demand on hardware

-: higher memory load on user, non-intuitive, poorer human performance

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8
Q

Graphic UI advantages/disadvantages

A

+: lower memory load on users, intuitive, better human performance
-: higher demand on hardware

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9
Q

Multimodal UIs (3)

A
  • Pen gesture recognition
  • Speech recognition
  • Multimedia (movies, animations…)
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10
Q

Multimodal UIs advantages/disadvantages

A

+: utilize human’s capacity

-: higher requirement on hardware

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11
Q

Multiple Resource Theory

A

Wickens…

(1) Responses: Verbal, Spacial, Manual, Vocal
(2) Modalities: Visual, Auditory
(3) Codes: Spacial Verbal
(4) Stages: Encoding, Central Processing, Responding

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12
Q

Input devices (4)

A

(1) hands
(2) voice
(3) eyes
(4) other (foot, brain?)

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13
Q

Hand input devices (2)

A

(1) keyboards (qwerty, dvorak)

(2) handwriting

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14
Q

qwerty keyboard

A

sacrifice human performance because of usage habits

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15
Q

problems with qwerty keyboards

A

(1) workload: lh>rh

(2) some frequently used letters (eg. e) are not on the same row, but some non-freq used ones are on home row

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16
Q

dvorak keyboard

A

(1) infrequent keys leave the home row

(2) workload: rh>lh

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17
Q

handwriting and voice recognition - how it works

A

match characteristics of the input stream with stored patterns, many for each possible word

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18
Q

Handwriting and voice recognition - technical difficulties (4)

A

(1) segmentations - separate into letters, recognize
(2) individual differences -> program training
(3) voice - noise
(4) voice - privacy

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19
Q

Handwriting and and voice recognition - spatial and temporal segmentation issues

A

temporal - optimal waiting time

  • spatial - optimal number and size of -windows
  • recognition accuracy
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20
Q

Recognition accuracy vs. task completion time

A

downward slope, horizonal asymptote

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21
Q

Eye-direct control usage

A

(1) people with disabilities

(2) hands are busy

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22
Q

Dr. Hawking

A
  • pneumonia
  • tracheotomy
  • machine that synthesized speech based on vibrations in trachea
  • Siemens recently made new eye-direct control UI
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23
Q

2 types of brain-computer interfaces

A

(1) non-intrusive - outside of scalp

(2) intrusive - implanted

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24
Q

3 types of output devices

A

(1) visual
(2) auditory
(3) tactile

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25
Q

2 types of visual output devices

A

(1) traditional (CRT, LCD)

2) non-traditional (VR - immersive, augmented - semi-immersive

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26
Q

Traditional visual display

A

wide screen to fit pictures

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27
Q

non-traditional visual display - adv/disadv

A

+: 3D depth perception, tracking head motion

-: motion sickness, ?

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28
Q

auditory display type

A

3D sound system - applicaiton - truck driver warning system

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29
Q

3D sound system - truck driver warning system

A

(1) modality

(2) beep - voice might take time to process

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30
Q

Tactile display examples

A

frozen wind, lane departure warning system

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31
Q

Benefits of auditory and tactile display

A

(1) when visual modality is occupied or very busy, auditory and tactile information will utilize the other modalities to convey information
(2) you may neglect to see it, but it is hard to neglect to hear it
(3) in some circumstances, it is more natural than visual display (e.g. the departure warning example)

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32
Q

3 types of I/O types

A

(1) traditional
(2) VR
(3) Auditory and tactile

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33
Q

Motivations to model

A

(1) predict and generate human behavior
(2) evaluate and improve interface design efficiently (save time and expense of experiment)
(3) unify many experimental studies
(4) model can be integrated into intelligent system design

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34
Q

KLM

A

Keystroke level model by Card, prediction of user performance time by adding each step’s time up

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35
Q

Elements of KLM

A 
K - key
P - point mouse
H - home on keyboard
M - mentally prepare
R - system response time
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36
Q

assumption of KLM

A

single task and there is no overlap

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37
Q

KLM’s pos/neg

A

+: easy to learn, quick to use

-: no practice effect, no overlap among steps, no hierarchical structure, no fatigue effect

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38
Q

GOMS

A

Goals, Operators/Methods, and Selection Rules by Card, Moran Newell, a hierarchical analysis of task steps and estimation of performance time

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39
Q

founders of AI and cognitive science

A

Newell and Simon

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40
Q

Variation of GOMS

A

NGOMSL - natural GOMS language - Kieras

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41
Q

NGOMSL

A

Method for goal - followed by steps (procedure)
Selection rules for goal - followed by if/then statements (if text is word, then accomplish goal: Highlight arbitrary text.)
Major improvement - add if…then, and return

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42
Q

GOMS/NGOMSL pos/neg

A

+: hierarchical analysis, more flexible (e.g. if-then rule)

-: single task, affected by different user strategies

43
Q

CPM-GOMS

A

Critical Path Method-GOMS

44
Q

GOMS setup

A 
Goal:...
[select: Goal:...
               - ....
               - ...]
Goal:...
45
Q

CPM-GOMS setup

A

Visual Perception
Cognitive Operators
Eye Movement

46
Q

CPM-GOMS pos/neg

A

+: Multiple Tasks

-: Only at the time domain, time consuming

47
Q

Classifications of Modeling

A

(1) KLM/GOMS - procedure modeling
(2) Simulation - production systems modeling
(3) Math Modeling - Deterministic, Stochastic

48
Q

Production Systems Theory guy

A

Herbert Simon

49
Q

HAM/ACT-R founder

A

John Anderson

50
Q

SOAR founder

A

Allen Newell

51
Q

EPIC and GOMS founder

A

David Kieras

52
Q

Discrete x Serial Stages models

A

Subtractive, Additive, General Gamma

53
Q

Discrete x Network Configurations models

A

Critical Path Network

54
Q

Continuous x Serial Stages models

A

Cascade, Queue series

55
Q

Continuous x Network Configurations models

A

Queuing network

56
Q

Discrete x Procedure Models and Methods

A

CPM-GOMS

57
Q

Continuous x Procedure Models and Methods

A

QN-MHP

58
Q

Discrete x Production Systems

A

SOAR

59
Q

Continuous x Production Systems

A

CAPS

60
Q

4 types of simulation models

A

(1) EPIC
(2) ACT-R
(3) CAPS
(4) QN-MHP

61
Q

EPIC

A

Executive Process-Interactive Control

  • Simulation Model
  • Core Assumption: No processing limit in the cognition part, limit is in the motor part
  • Certain parameters come from MHP
62
Q

ACT-R

A

Adaptive Control of Thought - Rational

  • Simulation Model
  • Core Assumption: Cognitive System works in serial manner
  • Perceptual/Motor from EPIC
63
Q

ACT-R progression

A

HAM -> ACT-R 1.0 (no motor/perceptual) -> ACT-R/PM (Motor Perceptual from EPIC)

64
Q

SOAR

A

An architecture for general intelligence

  • Simulation model
  • Core Assumption: AI model - no processing limit
  • Used in many systems as AI rather than cognitive model of human (e.g. missiles system)
65
Q

QN-MHP

A

Queuing network Model Human Processor

- Human behavior emerges naturally as entities are presented in the different routes in the network

66
Q

AI versus cognitive modeling

A

AI: Realize the function as human, but don’t care how human actually does it
Cog model: focus on how human actual performs
Ex: dish washer

67
Q

2 types of math models

A

SEEV, model verification

68
Q

SEEV

A
  • Salience (bottom-up processing)
  • Effort
  • Expectancy (top-down factor calibrated to bandwidth of events that occur at location)
  • Value (importance and relevance)
69
Q

SEEV formula

A

P(A) = S + Ex + V - Ef

70
Q

How to verify model’s prediction

A

trajectory of eye movement

71
Q

2 indices to judge a model

A

R squared, RMS

72
Q

R squared

A

square of correlation coefficients (trend/pattern)

73
Q

RMS

A

Root Mean Square

sqrt(sum of xi^2/n) where xi is Model value - Data value and n = number of conditions

74
Q

SATO

A

T = a + blog2(D/W)

75
Q

Why evaluate and test?

A

to get a mental model of the user

76
Q

Where to evaluate and test?

A
  • usability testing room (easy to control variables, subjects may change their real behavior)
  • natural task setting
77
Q

How to evaluate and test?

A

usability evaluation methods, usability testing methods

78
Q

usability evaluation methods

A

(1) cognitive walkthrough
(2) think aloud method
(3) cooperative evaluation
(4) checklist

79
Q

4 questions for cognitive walkthrough

A

(1) do users have a goal in mind
(2) do users notice that there are cues to complete their goals?
(3) can users link the correct cue with their goal?
(4) if users perform a correct/wrong action, do they get feedback?

80
Q

4 notes for cognitive walkthrough

A

(1) take the perspective from users
(2) consistent with design principles
(3) very easy to use and no subjects needed
(4) can only find 40% of usability problems

81
Q

3 notes for think aloud method

A

(1) one of the most effective ways to explore users’ real-time thoughts
(2) only use small amount of subjects
(3) subjects “say while doing”

82
Q

pos/neg for think aloud

A

+: discover what’s going on in users’ minds

-: intrusive, difficult to conduct for large number of subjects

83
Q

3 notes for cooperative evaluation

A

(1) need a small number of subjects/users
(2) an experimenter and subject/user cooperatively explore the UI and complete several tasks
(3) subject/user think aloud during the process

84
Q

cooperative evaluation pos/neg

A

+: very natural way to find usability problems

-: users’ verbal response and behavior might be affected by experimenter, only a few subjects

85
Q

QUIS

A
  • questionnaire for user interface satisfaction
  • developed by Chin et al.
  • can be used either by designers or users
  • a detailed implementation of design principles
  • categorized evaluation
  • not only usability, but some perception of hardware issues
86
Q

QUIS pos/neg

A

+: quick and easy

-: sometimes not able to provide specific design suggestions

87
Q

SUMI

A
  • Software Usability Measurement Inventory
  • developed by Kirakowski
  • mainly for software
88
Q

SUMI pos/neg

A

+ easy and relatively quick, free

-: for software only, has only 3 choices, no room for open-ended comments

89
Q

Usability testing - two major ways

A

(1) test UI prototypes without formal experimental design (identify usability problems, improve the interface design quickly
(2) Test UI prototypes with formal experiment design (find optimal design, benchmark/products, comparisons, etc

90
Q

Steps to testing UI prototypes without formal experimental design

A

(1) build prototypes
(2) design tasks
(3) invite a few potential or target users
(4) ask users to carry out these tasks (either with or without thinking aloud)
(5) recording all actions and verbal activities
(6) simple analysis of the results

91
Q

Without experimental design - pos/neg

A

+: quick and natural
-: do not know the exact causal relationship among variables with enough data support, cannot formally use results in publications, test reports, etc.

92
Q

With experimental design - pos/neg

A

+: relatively clean causal relationship, formal usage of the data
-: designing and running experiment is time consuming

93
Q

Independent variables

A

variables manipulated by the researcher or usability experts

94
Q

Dependent variables

A

variables observed by the researcher or usability experts

95
Q

One of the keys of a successful design

A

Controlling confounding variables

96
Q

Within subjects design

A

levels of a certain variable experienced by each subject

97
Q

between-subjects design

A

levels of certain variables only experienced by some of subjects/users

98
Q

Why number of subjects is an important issue

A

determines validity and how strong your conclusion is

99
Q

Equation for number of subjects

A

NX where N is a natural number and X is combinations of all between subjects variables
OR can be calculated by estimated variability of data

100
Q

OC Curves

A

Operating Characteristic Curve

101
Q

x axis of OC curve

A

d = abs(mu - mu0)/sigma where mu is the average of the data, mu0 is the standard

102
Q

Statistical power

A

beta; should be greater than or equal to .6

103
Q

standard deviation

A

sqrt(sum of (xi-avg(x))^2/(n-1))

104
Q

Power

A

1- beta; should be greater than or equal to 7

HCI Test 3 (2 decks)

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