PSY 332 Reasoning

Reasoning

Purposeful mental activity that operates on information to reach conclusions

Reasoning definition

Drawing inferences from observations, facts, or assumptions

Purpose of reasoning

Helps individuals interpret and make sense of the world

Dual-process theory of reasoning

Idea that reasoning occurs through two different processing routes

Stage 1 processing

Fast, automatic, heuristic-based reasoning

Heuristic mode

Uses schemas and scripts to make quick judgments

Schemas

Mental frameworks that organize and interpret information

Scripts

Structured expectations about sequences of events

Stage 2 processing

Slow, controlled, effortful reasoning

Controlled reasoning

Uses more evidence and deliberate analysis

Conscious reasoning

Deliberate, effortful reasoning processes

Algorithm

Step-by-step procedure that guarantees a correct answer if followed correctly

Algorithm example

Calculating the area of a triangle

Logic

Reasoning based on evidence and formal arguments

Inference

Conclusion drawn from evidence and premises

Conditional reasoning

Evaluating if evidence supports an if–then relationship

Antecedent

The “if” part of a conditional statement

Consequent

The “then” part of a conditional statement

Deductive reasoning

Reasoning from general principles to specific conclusions

Deductive validity

If premises are true, the conclusion must be true

Deductive example

All cats have four legs; Shelly has four legs; therefore Shelly is a cat

Inductive reasoning

Reasoning from specific observations to general conclusions

Inductive example

Observing rain after clouds and concluding clouds predict rain

Deductive vs inductive difference

Deductive goes general → specific; inductive goes specific → general

Heuristic

Mental shortcut that simplifies decision-making but does not guarantee accuracy

Heuristic benefit

Speeds up decisions

Heuristic cost

Increases likelihood of bias and error

Availability heuristic

Judging likelihood based on how easily examples come to mind

Availability bias effect

Overestimating frequency of vivid or recent events

Framing effect

Decisions change depending on how information is presented

Framing example

Different outcomes chosen based on wording in disease scenarios

Confirmation bias

Seeking information that supports existing beliefs

Confirmation bias consequence

Ignoring contradictory evidence

Counterfactual reasoning

Thinking about alternative outcomes that did not occur

Counterfactual thinking consequence

Can produce regret or alternative explanations

Hindsight bias

Belief that events were predictable after they occur

Hindsight bias effect

Overconfidence and illusion of control

Anchoring and adjustment heuristic

Relying heavily on an initial value and adjusting insufficiently

Anchor

Initial reference point in decision-making

Anchoring bias

Final judgments remain too close to the anchor

Arbitrary anchors

Even irrelevant numbers can influence decisions

Anchoring study example

UN African nations estimate influenced by random numbers

Peak-end heuristic (Kahneman, 1999)

Evaluating experiences based on peak intensity and ending

Peak-end rule effect

Total duration of experience is underweighted

Colonoscopy study (Redelmeier & Kahneman, 1996)

Longer but less painful procedures rated more favorably

Peak-end decision consequence

People repeat experiences remembered positively despite discomfort

Bias reduction conditions

Biases decrease with time, expertise, and high stakes

Metacognition

Awareness of one’s own thinking processes

Metacognitive benefit

Helps detect and reduce biases

High-stakes decision example

Medical decisions rely less on heuristics

Decision-making process

Structured approach to choosing among alternatives

Decision objectives

Clear goals that guide choices

Evaluating alternatives

Comparing options based on objectives

Tentative decision

Initial choice evaluated before final commitment

Analysis paralysis

Overthinking that leads to decision avoidance

Choice overload

Too many options reduce satisfaction and action

Paradox of choice

Iyengar & Lepper (2000) finding on choice overload

Jam study finding

Fewer options led to higher purchase rates

Bounded rationality

Limited rationality due to cognitive constraints and time

Herbert Simon

Proposed bounded rationality theory

Satisficing

Choosing a solution that is “good enough” rather than optimal

Bounded rationality implication

Real-world decisions differ from ideal rational models

Impact bias

Overestimating emotional impact of future events

Impact bias example

Misjudging happiness after life changes

Rationalization

Justifying decisions to maintain satisfaction

Irreversible decision rationalization

People feel happier with choices they cannot change

Gilbert & Ebert (2002) study

Irreversible choices produce higher satisfaction

Psychological immune system

Mental processes that help cope with negative outcomes

Reversible vs irreversible choices

Reversible choices often reduce long-term satisfaction

Risk-taking dual-process theory

Risk behavior influenced by cognitive and emotional systems

Logical reasoning development

Matures around age 15

Psychosocial development

Impulse control and emotion regulation mature into 20s

Steinberg (2007) theory

Risk-taking due to imbalance between control and emotion systems

Peer presence effect

Adolescents take more risks around peers

Driving task studies

Show increased adolescent risk-taking in lab settings

Walsh & Ayton (2009) study

Surrogate information influences happiness predictions

Surrogate ratings

Information from people with firsthand experience

Health state prediction

People rely on others’ happiness ratings when info is limited

Kidney disease scenario

Provided happiness ratings shape expectations

Health framing implication

How information is presented affects medical decisions

Cultural Heritage Hypothesis (Mervin, 2011)

Culture shapes decision-making philosophies