Behavioral: Basic Psychology of the Senses of the User
IST 331 – Organization and Design of Information Systems: User and System Principles
Instructor: Mithu Bhattacharya
Revised by FER 17 feb 2011
Spring 2011
Class Agenda• TA Online Evaluation• 402 fall 2011• Discussion
– Today’s Reading– Chapter 5: Behavioral: Basic Psychology of the Senses
of the User• What’s Up Next?• In Class Exercise• Minute Paper
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Class Objectives
• Users’ Behavioral Characteristics• In Class Exercise• Minute Paper
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Introduction to B of ABCS• Why is it important to understand user’s behavioral
characteristics?– Optimizing system functionalities to match user requirements– Understanding user characteristics and limitations -> Better
allocate functions between user and system for maximum effect– Understanding user’s limitations
• How well a user can perceive displayed information• How much information can user use• What type of information is required by user• How easy it is for user to learn to perform tasks using system
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Sensation vs. Perception• SensationSensation
– The experience of sensory information The experience of sensory information – Determined by stimulus quality and sensory organDetermined by stimulus quality and sensory organ– Objective processObjective process
• PerceptionPerception– The process of creating meaningful patterns from raw The process of creating meaningful patterns from raw
sensory informationsensory information– Influenced by past experiences, expectations, and Influenced by past experiences, expectations, and
feelingsfeelings– Subjective processSubjective process
• Presenting stimuli -> Received accurately -> Does not Presenting stimuli -> Received accurately -> Does not mean perceived accuratelymean perceived accurately
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Validity
• Validity: How well a concept represents another concept• Internal validity: Is your experiment measuring what it thinks it is
measuring?– Not measuring noise or incidental factors– Controlling known effects that influence results can avoid problems
• Construct validity: If your measure measures what you think it measures
– Example: You want to measure size of people and end up measuring their feet
• External validity: What you measure will apply to other situations and populations
– Wider range of users increase external validity• Surface Validity
– Does it look like it measures what it is trying to measure?
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Perceptual Thresholds
• Vision: A candle flame seen from 30 miles on a clear, dark Vision: A candle flame seen from 30 miles on a clear, dark nightnight
• Hearing: The tick of a watch from 20 feet in very quiet Hearing: The tick of a watch from 20 feet in very quiet conditionsconditions
• Smell: 1 drop of perfume diffused throughout a three-Smell: 1 drop of perfume diffused throughout a three-room apartmentroom apartment
• Taste: .0356 ounce of table salt in 529 quarts of waterTaste: .0356 ounce of table salt in 529 quarts of water• Touch: A bee wing falling on your cheek from a height of 1 Touch: A bee wing falling on your cheek from a height of 1
centimetercentimeter
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Just Noticeable Differences (JND)• How small a change can be detected• Measures sensitivity of perception• Subjective measures and vary across users• Interface elements that use differences in stimuli that are
less than a JND are difficult for users to differentiate• Important differences should be differentiated by several
JNDs• Example: Yellow and slightly darker yellow will be difficult
to differentiate
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Habituation• Habituation occurs when percept occurs repeatedly
without importance• Over time stimuli seems less important and perceptible• Holds for all kinds of perception• Implications for system design
– Actions that are routinely requested are performed with less care– Example: Reading installation notes– Too many warnings generated are ignored because users
habituate– Reserve warnings to avoid users’ false habituation
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H – A Measure of Information
• How to define information (Claude Shannon)
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• Measure of information is negative sum of probabilities times the log of probabilities of each possible object or event
• If probability of event is 1, then there is no information (log 1 = 0)• If probabilities are each less than 1, then logs are negative, and the
negative sign make the same positive• Useful way to describe complexity of inputs
Signal Detection Theory
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• SDT measures how accurate is performance• Gives a way to analyze complex situations
Signal Present
Response Yes No
Yes Hit False Alarm
No MissCorrect Rejection
Types of responses to a signal
Signal Detection Theory
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• Key parameter: Distinguish signal from noise• Signal normally distributed some distance away from 0• Noise is distributed around 0• Distance between noise and signal – inherent property of observer and stimuli• Threshold (Criterion response) – parameter that the observer adjusts• Area of signal distribution correctly classified as signal(to the right of threshold) – Hits• Area of signal to left of threshold – Miss• Noise classified as signal to the right of threshold – False alarm• Noise to the left of threshold - Correct rejection• Distance and threshold can be computed from their ratio using tables from normal
distribution
Signal Detection Theory
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• Better observers with clearer signals have greater d• Avoid missing signals -> Move threshold towards noise distribution to
capture more of signal• Reduce false alarms -> Move threshold towards centre of signal
distribution• Cost of false alarms and misses influence where threshold is set• Misses costly -> Threshold will be to the left picking more signal and
more noise• False alarms costly -> Threshold will be to the right missing more of
noise but also part of signal• Implication for system design
– SDT notes explicitly that there will be mistakes (misses and false alarms)– Interfaces should help users recover from misses and false alarms– Help differentiate between misses and false alarms– Displays help observers have clearer understanding of signal– Displays help users to adjust their thresholds to suit tasks
Minute Paper
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What’s Up Next?• Read ABCS Chapter 5 (Sections 5.6-5.12)
– Behavioral: Basic Psychology of the Senses of the User
• Come up with at least two questions / observations / comments to discuss in class
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QuickTime™ and a decompressor
are needed to see this picture.
QuickTime™ and a decompressor
are needed to see this picture.
In Class Exercise
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• Explain how signal detection theory can be used to analyze searching on the Web. Based on this analysis, provide two suggestions to your favorite search engine
• Discuss and do it in your group• Submit one answer per group on paper• Discuss overall answers with class
Information content example
• MS Mobile tag– Information content in MS Mobile tag– 5 rows, 10 triangles, 4 colors– Total: 50x2 bits = 100 bits, 12.5 bytes
• Datamatrix– Up to 144x144 x 2– Total: 20,736 bits, 2,592 bytes
Structure of the eye
Two useful effects• Popout
Word completion
