Human Information Processing

Human Information Processing Perception, Memory, Cognition, Response

Types of Information • Quantitative (e.g., 100% charged, 63% charged) • Qualitative (e.g., fully charged, partially charged) • Status (normal, abnormal) • Warning (abnormal -- potentially dangerous) • Representational (e.g., pictures, diagrams) • Identification (e.g., labels)

World Stage Model of Information Processing Mental Resources • Sensing & • Perception • vision • hearing • ... • perception Working Memory • Cognition • situation • awareness • decision making • planning • attention • task management • Response • Fitts’ Law • Hicks’ Law Long Term Memory Stimuli Responses

Sensible energy Examples visual auditory chemical tactile acceleration etc. Stimuli

Information Coding • use of stimulus attributes to convey meaning

Coding Examples: Shape radio navigation aid Size icity, population 1,000-10,000 ncity, population 10,000-100,000 Colornnormal n non-normal Pitch high barcode read low failed to read barcode Text OFF

Characteristics of Coding Systems • Detectability of codes (thresholds) • Discriminability of codes (JNDs) • Meaningfulness of codes • Standardization of codes • Code Redundancy

Sensing • Vision • Hearing • Smell • Touch • Temperature • Pain • Kinesthetic • Equilibrium • Vibration

Sensing (continued) • Sensory Memory • Iconic (visual) • Echoic (auditory) • Limits • Detection thresholds • Discrimination thresholds • Pain

Perception • Definition • interpretation of sensory stimuli • pattern recognition • preparation for further processing • Processes • feature analysis (e.g., text, object perception) • top-down processing (use of context, expectancy) • Examples • Recognizing face of friend • Detecting defect in piece of plywood

Perception - Signal Detection • Stimulus: sensory input(s) • Signal: stimulus having a special pattern • Noise: Obscuring stimuli • Task: Report “yes” when signal present, otherwise “no” • Example: steam power plant • task: detect boiler leak • stimulus: sound pressure level (SPL) • signal: higher than normal SPL

Stimulus-Response Matrix Stimulus Noise Signal + Noise Yes Response No

Signal Detection Theory (1) noise only P (stimulus intensity = x) X (decibels)

Signal Detection Theory (2) d’ noise only signal + noise P (stimulus intensity = x) X (decibels)

Signal Detection Theory (3) criterion NO YES d’ noise only signal + noise P (stimulus intensity = x) X (decibels)

Signal Absent Condition criterion NO YES d’ noise only signal + noise P (stimulus intensity = x) P(quiet) X (decibels) P(false alarm)

Signal Present Condition criterion NO YES d’ noise only signal + noise P (stimulus intensity = x) P(hit) P(miss) X (decibels)

Phenomenon low d’ leads to poor SD performance Example failure to detect defects in lumber Explanation lack of memory to memorize signal Countermeasure memory aid Signal Detection: Low d’

Phenomenon prolonged monitoring (signal detection) P(hit) decreases, P(miss) increases after about 30 min Example manufacturing process goes out of tolerance Explanation sensitivity loss/fatigue/memory loss Countermeasures training signal transformations feedback extraneous stimuli Signal Detection: Vigilance Decrement

Phenomenon failure to discriminate between > ~ 5 stimuli Example radar operator mis-identifies aircraft Explanation memory limitation Countermeasures training & experience anchors memory aids redundant coding Signal Detection: Absolute Judgment Failures

Phenomenon dichotomy between left half of brain (verbal) right half of brain (visual) Example historians vs engineers Explanation only slight indication of being influential Perception: Left vs. Right Brain

Long Term Memory • Store for all information to be retained • Contents • General Facts (declarative knowledge) • Procedures (procedural knowledge) • Current model of world (including self) • Current tasks • etc. • Limits • Unknown • Accessibility vs. Actual content

Long Term Memory (cont.) • Categories • Semantic memory (general knowledge) • Event memory • episodic memory (what happened) • prospective memory (what to do) • Mechanisms: associations • frequency of activation • recency of activation • Forgetting • exponential decay • due to • weak strength • weak associations • interfering associations

Working Memory(Short Term Memory) • Definition • store for information being actively processed • Examples of WM/STM use • telephone number to be dialed 7 3 7 2 3 5 7 • observed stimulus and standard stimuli Red Blue ? Compare with Green Yellow

Working Memory Capacity • 7 + 2 “chunks”, e.g., • digits (0, 1, 2, ...) • digit sequences (737-, 752-, 745-, 754-, ...) • names (“Bill”, “Sue”, “Nan”, etc.) • persons (Bill, Sue, Nan, etc.) • etc. • Miller’s magic number (Miller, 1956). • Very significant human limitation. • Enhanced by “chunking”.

Working Memory Duration • max 10 - 15 s without attention/rehearsal. • Decay rate influenced by number of items. • Greatest limitation of WM. • Very significant human limitation. • Has implications for design.

Decision Making and Problem Solving

Decision Making • Characteristics of a decision making situation • select one from several choices • some amount of information available • relatively long time frame • uncertainty

Classical Decision Theory • Normative Decision Models • expected value theory • probability of outcome, given decision • value of outcome, given decision • maximize weighted sum • subjective utility theory

Classical Decision Theory (cont.) • Humans violate classical assumptions • framing effect (differences in presentation form) • don’t explicitly evaluate all hypotheses • biased by recent experience • etc. • Descriptive Decision Models • Use of heuristics • “Satisficing” • Simplification

Information Processing Framework • Cue reception and integration • Hypothesis generation • Hypothesis evaluation and selection • Generation and selection of action(s)

Factors Affecting Decision Making • Amount/quality of cue information in WM • WM capacity limitations • Available time • Limits to attentional resources • Amount and quality of knowledge available • Ability to retrieve relevant knowledge

Heuristics and Biases • Heuristic • “rule of thumb” • usually powerful & efficient • history of success • does not guarantee best solution • may lead to bias • Bias • “irrational” tendency to favor one alternative/class of alternatives • natural result of heuristic application • Heuristic implies bias

Heuristics in Obtaining and Using Cues • Attention to limited number of cues • Cue primacy • Inattention to later cues • Cue salience • Overweighting of unreliable cues (treating all cues as if they were equal)

Heuristics in Hypothesis Generation • Generation of limited number of hypotheses/potential solutions • Availability heuristic • recency • frequency • Representativeness heuristic (“typicality”) • Overconfidence

Heuristics in Hypothesis Evaluation and Selection • Cognitive fixation • underutilize subsequent cues • Confirmation[al] bias • seek only confirming evidence • don’t seek, ignore disconfirming evidence • Note: sometimes “confirmation bias” encompasses both

Heuristics in Action Selection • Consideration of small number of actions • Availability heuristic for actions • Availability of possible outcomes

Naturalistic Decision Making • Decision making in the “real world” • Characteristics • ill-structured problems • uncertain, dynamic environments • lots of (changing) information • iterative cognition (not once-through) • multiple (conflicting, changing) goals • high risk • multiple persons • complexity

Skill-, Rule-, Knowledge-Based Performance • Knowledge-based performance • novices or novel/complex problems • knowledge-intensive • analytical processing • high attentional demand • errors: limited WM, biases • e.g., navigating to a new residence • Rule-based performance • more experienced decision makers • if-then rules • errors: wrong rule

Skill-, Rule-, Knowledge-Based Performance (cont.) • Skill-based performance • experts, experienced decisions makers • automatic, unconscious • requires less attention, but must be managed • errors: misallocation of attention

Other Topics in Naturalistic Decision Making • Cognitive continuum theory • intuition  analysis • Situation Awareness (SA) • perceiving status • comprehending relevant cues • projecting the future • Recognition-Primed Decision Making • recognized pattern of cues • triggers single course of action • intuitive

Improving Human Decision Making • Redesign • environment • displays • controls • Training • use heuristics appropriately • overcome biases • improve metacognition • enhance perceptual skills • Decision Aids • decision tables • decision trees • expert systems • decision support systems

Problem Solving • Problem • goal(s) • givens/conditions • means • initial conditions  goal(s) • Errors and Biases in Problem Solving • inappropriate representations • fixation on previous plans • functional fixedness • limited WM

Attention: The Flashlight Metaphor

Definitions focus of conscious thought means by which limited processing resources are allocated Characteristics limited in direction limited in scope Attention

Phenomenon inappropriate selection (i.e., inappropriate attention to something) Example using cell phone while driving Explanation salient cues Countermeasures control salience of cues Attention: Selection

Phenomenon tendency to be distracted Example pilot distracted by flight attendant call Explanation high salience of less important cues low salience of important cues Countermeasures remove distractions control salience Attention: Distraction

Human Information Processing