Chapter 8: Decision Making

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Presentation transcript:

Chapter 8: Decision Making

Classes AND FEATURES OF DM

Uncertainty Time Familiarity and Expertise Classes of DM research

AN INFORMATION PROCESSING MODEL OF DECISION MAKING

WHAT IS “GOOD’ DECISION MAKING?

DIAGNOSIS AND SITUATION ASSESSMENT IN DECISION MAKING

Estimating Cues: Perception Proportions Projections Randomness Gambler’s fallacy

Evidence Accumulation, Selective Attention: Cue Seeking and Hypothesis Formation

Evidence Accumulation, Selective Attention: Cue Seeking and Hypothesis Formation Information cues are missing Cues are numerous: Information overload Cues are differently salient Salient bias, absence of cue

Evidence Accumulation, Selective Attention: Cue Seeking and Hypothesis Formation Processed cues are not differentially weighted by information value As-if heuristic

Expectations in Diagnosis: The Role of Long-Term Memory Representativeness Base rate The availability heuristic

Belief Changes Over Time Anchoring heuristic The confirmation Bias Cost of thinking, motivational factors (consistency), self-fulfilling prophecy Decision fatigue

CHOICE OF ACTION

Certain Choice

Choice Under Uncertainty: The Expected Value Model

Heuristics and Biases in Uncertain Choice Direct retrieval Distortions of values and costs: Loss aversion

Heuristics and Biases in Uncertain Choice Temporal discounting Perception of probability The framing effect

EFFORT AND META COGNITION

Effort Performance-resource function Contingent model

Meta-Cognition and (Over) confidence Diagnostic or problem difficulty Evidence reliability

Experience and Expertise in DM Holistic decision making expertise

Experience and Expertise in DM

Improving Decision Making Training debiasing Proceduralization Displays Automation and Decision Support Tools

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