Scientific Underpinnings of Usability Engineering

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Scientific Underpinnings of Usability Engineering. February 5, 2004. Objectives. 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 - PowerPoint PPT Presentation

Transcript of Scientific Underpinnings of Usability Engineering

R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu 1

iScientific Underpinnings of

Usability Engineering

February 5, 2004

R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu 2

iObjectives

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 3

iDesigning Stuff

• 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 4

iLast week . . .

• 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 5

iHuman Information Processing

• 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 6

iEye Physiology

R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu 7

iEye Muscles

R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu 8

iVisual Field

R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu 9

iRetinal Physiology

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iDistribution of Rods and Cones

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iVisual Sensitivity

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iVisible Spectrum

R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu 13

iNeural Pathways

R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu 14

iAftereffect

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iAmbiguous Figure

R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu 16

iSensation/Perception

• 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 17

iPerceptual Psy – Color Vision

• Color perception – 3 types of cones (RGB)

R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu 18

iPerceptual Psy -- Depth

• 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 19

iMore Depth Cues

• 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 20

iMonocular Cues -- Interposition

R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu 21

iMonocular Cues -- Size

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R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu 23

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R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu 24

iMonocular Cues – Linear Perspective

R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu 25

iMonocular Cues – Texture Gradient

R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu 26

iSooooo . . .

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 27

iMonocular Cues – Aerial Perspective

R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu 28

iMonocular Cues -- Shading

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iMonocular Cues – Motion Parallax

R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu 30

iMore visual perception

• 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 31

iPonzo Illusion

R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu 32

iMuller-Lyer Illusion

R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu 33

iPsycholinguistics

• 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 34

iThe Psychology of Reading

• 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 35

iSome facts about reading

• 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 36

iMore facts

• 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 37

iIconic Memory

• 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 38

iIconic Memory (cont’d.)

• 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 39

iHow do you know, Randolph?

• 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 40

iRubenstein et al. (1971)

• 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 41

iMore Data

• 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 42

iThe Point

• 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 43

iLast week, talking about Perception and Cognition

•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 44

i

3333333333333333333333333333333

R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu 45

iExperiment 1

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 46

iBOVNAZTOLRIJDIHRENWUKCAQGOCMEB

R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu 47

iBOVNAZTOLRIJDIHRENWUKCAQGOCMEB

R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu 48

iExperiment 2

•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 49

iVAMLUNXOPREHWIVCITJEGKUCZOBYAD

R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu 50

iVAMLUNXOPREHWIVCITJEGKUCZOBYAD

R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu 51

iExperiment 3

• 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 52

iGEPTIV

WOHLUPMAZSEXKOLRUCNIDBIR

R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu 53

iGEPTIV

WOHLUPMAZSEXKOLRUCNIDBIR

R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu 54

iSo?

• So, the answer to “Can you remember a 30-digit 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 55

iSO WHAT?

• 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 56

iLast week’s homework

• Good and bad web site designs

R. G. Bias | School of Information | SZB 562BB | Phone: 512 471 7046 | rbias@ischool.utexas.edu 57

iComing Up

• Next week: Guest Lecture by Dr. Phil Kortum and Dr. Bob Bushey, from SBC Labs.

• Make sure you’ve done the reading!