Week 3 PowerPoint Slides

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Scientific Underpinnings of
Usability Engineering
February 5, 2004
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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Objectives
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After this class you will be able to (it is my
hope!):
•
•
•
•
•
Describe some eye physiology
Explain how the visual system works (somewhat)
Identify visual cues to depth
Explain some aspects of the psychology of reading
Explain how perceptual and cognitive psychology
influence HCI designs
• Have an excellent memory for “VAM”
• Discuss the importance of designing systems to match
the human.
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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Designing Stuff
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• In Week 1, I asked the question “What would a system
look like if we were designing it for dogs?”
– Wouldn’t be a lot of text.
– Wouldn’t require a lot of dexterity.
– Might code information in smells and tastes.
• But we’re designing systems for humans (usually!).
So it will behoove us to know something about how
human beings take in and process information.
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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Last week . . .
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• Why were those designs poor?
• At a high level, because they didn’t
match your understanding, your
organization of information. (Your
mental model.)
• The whole point: Let’s design systems
to fit people instead of the other way
around.
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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Human Information Processing
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• How do human beings take in and process
information?
– Sensory psychology – how humans transform physical
energy (e.g., light and sound waves) into sensory signals to
and in the brain.
– Perceptual psychology – how humans interpret these
sensory signals as perceptions.
– Cognitive psychology – how humans think about these
perceptions, and previous experiences, and their own mental
creations, and . . .
– Psycholinguistics – The psychology of language -- what
goes on between the time I have a thought and you have the
same (or similar!) thought, whether I say it or write it.
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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Eye Physiology
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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Eye Muscles
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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Visual Field
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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Retinal Physiology
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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Distribution of Rods and Cones
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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Visual Sensitivity
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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Visible Spectrum
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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Neural Pathways
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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Aftereffect
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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Ambiguous Figure
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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Sensation/Perception
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• POINT: Perceptions are made up of more
than just a collection of sensations!
• OTHER things influence our perceptions, e.g.,
–
–
–
–
–
Our experiences
Our biases
The context
Our current emotional state
Etc.
• So, what does that have to say about
designing human-computer interfaces???
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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Perceptual Psy – Color Vision
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• Color perception – 3 types of cones (RGB)
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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Perceptual Psy -- Depth
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• Different visual cues to depth
– Oculomotor vs. Visual
• Oculomotor – Lens accommodation and
extraocular muscle convergence are “read” by
the brain
– Visual: Binocular vs. Monocular
• Binocular – Stereopsis (retinal disparity)
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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More Depth Cues
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• Monocular
– Static
• Interposition
• Size
• Perspective
–
–
–
–
Linear perspective
Texture gradient
Aerial perspective
Shading
– Motion parallax
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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Monocular Cues -- Interposition
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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Monocular Cues -- Size
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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Monocular Cues – Linear
Perspective
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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Monocular Cues – Texture
Gradient
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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Sooooo . . .
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The grass really
IS
greener on the other side of the fence!!!
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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Monocular Cues – Aerial
Perspective
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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Monocular Cues -- Shading
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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Monocular Cues – Motion
Parallax
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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More visual perception
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• Illusions – and what they tell us about
vision
• Ponzo illusion
• Muller-Lyer illusion
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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Ponzo Illusion
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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Muller-Lyer Illusion
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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Psycholinguistics
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• The psychology of language.
• What goes on from the time I get an idea
until you have the same idea,
– Whether I speak my idea (speech
production, auditory science, speech
perception)
– Or write my idea (motor movements, visual
system, reading)
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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The Psychology of Reading
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• Except for fairly rare cases of “phonetic
symbolism” (onomatopoeia) words have
no inherent meaning.
– (And rarer cases of “orthographic
symbolism”!!)
• So, READING is the interpreting of
words, the acts that go on to impose
meaning, from within, on external visual
stimuli.
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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Some facts about reading
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• Eyes of the mature reader move rhythmically across the page
(from left to right).
• Eye movement consists of fixations, saccades, regressions, and
return sweeps.
• No information is taken in during saccades (10-25 msec),
regressions (same duration), or return sweeps (40 msec).
• During fixation (250 msec) a visual pattern is reflected onto the
retina.
• Span of perception = amount of print seen during a single fixation.
• Span of perception = 12 letter spaces for good readers, 6 for poor
readers.
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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More facts
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• Span of recognition – 1.21 words for senior high, 1.33 words for
college readers.
• So, 7 to 8 fixations per line of print.
• As content gets tougher, duration of fixations, not number,
changes (increases).
• Regressive movements aren’t systematic. Used when attention
is faltering.
• College readers have 1 regressive movement per 3 or 4 lines of
print. Immature readers have 3 or 4 regressions per line.
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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Iconic Memory
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• Remember in Week 1 I mentioned a two-stage memory process –
STM and LTM.
• A third stage, Iconic Memory: The unidentified, “pre-categorical”
pattern of lines, curves and angles; formed in about 100 msec.
• Icon can hold up to 20 letter spaces.
• Pattern recognition routines are applied to the lines, curves.
• It takes about 10 – 20 msec to read each letter out of the iconic
memory.
• Neural signal takes about 30 msec to go from the retina to the
visual cortex.
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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Iconic Memory (cont’d.)
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• At some point, thanks to pattern recognition routines, letters are
read out.
• Letters are transformed into abstract phonemic representations.
• The abstract phonemes are used to search the mental lexicon.
• About 300 msec after the eye has fallen upon the page, the first
word is “understood,” i.e., placed in Primary Memory (STM,
Working Memory).
• Syntactic and semantic rules are applied to gain the meaning of
the sentence.
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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How do you know, Randolph?
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• Psycholinguists employ a variety of methods to
acquire this data about human behavior.
• One question: Why do we think readers routinely
transform the visual representation into a phonological
representation?
– Cognitive economy – all (healthy) new readers
come to the task as skilled hearers.
– “I thought you said something about data?”
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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Rubenstein et al. (1971)
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• Used a lexical decision task (word/nonword?).
• Two types of words – homophonous (with real words),
like burd and nonhomophonous like rolt. Equally
“wordlike.”
• Longer latencies for burd.
• Similarly, longer for real homophones like meat.
• Pointed to “false matches” in the mental lexicon.
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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More Data
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• McCusker et al. (1977) proofreading experiment
– Homophonous typos (e.g., furst) went undetected
more often than nonhomophonous typos (e.g.,
farst).
• Gough and Cosky (1977) used the Stroop task.
– Nonwords homophonous with color words (e.g,. bloo) led to
more interference than control words (e.g., blot) or nonwords
nonhomophonous with color words (e.g., blop).
• I found readers took longer to process words with
irregular “spelling-to-sound rules” (e.g., pint) than
words with regular rules (e.g., hint) (Bias, 1978).
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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The Point
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• The reasons for this somewhat esoteric
discourse on the psychology of reading
are:
– To communicate the complexity that is
human information processing
– The illustrate the ways scientists go about
answering questions about info processing
– To sensitize you to the sorts of things known
about human behavior
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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Last week, talking about
Perception and Cognition
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•What do we know about humans?
– In the physical realm: Anthropometry.
– These days we’re more interested in the
cognitive realm.
– Question: Can you remember a 30-digit
number?
– I say that you can, right now, without practice,
seeing it only once, for 1 second, with no time to
rehearse.
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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3333333333333333333333333333333
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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Experiment 1
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Instead of numbers, I’ll present CVC
(consonant-vowel-consonant) strings -- like
“NEH”.
10 CVCs, one at a time.
Presented visually.
Don’t have to remember them in order.
Pencils down.
Ready?
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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BOV
NAZ
TOL
RIJ
DIH
REN
WUK
CAQ
GOC
MEB
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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BOV
NAZ
TOL
RIJ
DIH
REN
WUK
CAQ
GOC
MEB
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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Experiment 2
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•Now, 10 new CVCs.
•Same task -- recall them.
•This time, after we read the 10th item,
we’ll all count backwards from 100 by 3s,
aloud, together.
•Then when I say “Go,” write down as
many of the 10 CVCs as you can.
•Pencils down.
•Ready?
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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VAM
LUN
XOP
REH
WIV
CIT
JEG
KUC
ZOB
YAD
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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VAM
LUN
XOP
REH
WIV
CIT
JEG
KUC
ZOB
YAD
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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Experiment 3
•
•
•
•
•
•
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Same as Experiment 2.
Yet 10 more CVCs.
Backwards counting.
Don’t have to recall them in order.
Pencils down.
Ready?
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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i
GEP
TIV
WOH
LUP
MAZ
SEX
KOL
RUC
NID
BIR
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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i
GEP
TIV
WOH
LUP
MAZ
SEX
KOL
RUC
NID
BIR
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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So?
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• So, the answer to “Can you remember a 30digit number?”, is . . . It depends. On what?
– Whether you hear or see the number.
– Whether the number is masked.
– Whether you have time to rehearse.
– Whether you can “chunk” the numbers.
– If there are any intervening tasks.
– How meaningful the number is.
– WHAT the number is.
So, what’s a usable interface?
It depends.
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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SO WHAT?
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• Given that we’re so all-fired complex,
what does this have to say about how we
design computer interfaces?
– Depth cues.
– Color perception.
– Effects of context on perception.
– What’s easy to read?
– Recognition vs. recall.
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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Last week’s homework
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• Good and bad web site designs
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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Coming Up
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• Next week: Guest Lecture by Dr. Phil
Kortum and Dr. Bob Bushey, from SBC
Labs.
• Make sure you’ve done the reading!
R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu
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