PSYC_200_CHAPTER_8

Chapter 8: Thinking, Decisions & Intelligence

Analogical vs Symbolic Representation

• Difference in Conveyance:

  • Analogical representation resembles what it portrays using images, maps, etc.

  • Symbolic representation uses abstract symbols like words or codes, lacking a physical resemblance.

• Strengths:

  • Analogical representation is intuitive and visual; excels in visual tasks.

  • Symbolic representation is strong in precision, abstraction, and logical reasoning; suitable for structured analysis.

Analogical Representation of Problems

• Concept:

  • Utilizes visual or spatial analogies to represent problems closely related to real-world scenarios.

• Example:

  • Electricity flow analogy:

    • Wires = pipes; Current = water; Battery = water pump.

  • This analogy aids in grasping abstract concepts by providing tangible comparisons.

Problem Solving & Decision Making

• Definitions:

  • Problem-Solving: Involves identifying and resolving challenges through generating and implementing solutions.

  • Decision-Making: Focuses on selecting the best course from alternatives, based on evaluation criteria (risks, benefits).

• Relationship:

  • Problem-solving encompasses decision-making as a step within the process.

• Buddhist Monk Problem:

  • Concept illustrates simultaneous paths of two monks climbing and descending a mountain, underlining the point of intersection where they occupy the same location at identical times on both trips.

Chi, Feltovich, & Glaser (1981) Study

• Focus:

  • Examined how experts versus novices categorize and solve physics problems.

• Findings:

  • Experts base problem-solving on deep principles (e.g., conservation laws), while novices rely on surface features.

  • Experts utilize schematic representations for efficient problem-solving, novices lack this ability.

• Implications:

  • Teaching strategies should emphasize deep structures over superficial features to cultivate expertise.

Deductive Reasoning & Problem Representation

• Importance of Representation:

  • The way problems are represented affects reasoning speed and accuracy.

• Example:

  • Syllogism: All A are B, Some B are C, Therefore some A are C lacks guaranteed truth due to premises.

• Re-Representation Techniques:

  • Using visual aids (e.g., Venn Diagrams) or concrete examples clarifies logical connections and enhances comprehension.

Logic and Reasoning

• Cognitive Influences:

  • Decision-making often swayed by confirmation bias and general knowledge.

  • Concrete framing aids in problem visibility compared to abstract presentations.

• Types of Reasoning:

  • Deductive Reasoning: Moves from general premises to specific, ensuring conclusions, reliant on the truth of premises.

  • Syllogism Structure: Major premise, minor premise, conclusion.

Conditional Reasoning

• Concept:

  • Involves "if-then" statements, where one outcome is dependent on another.

• Validity:

  • Relies on the initial conditions being true for correct outcomes.

• Research Findings:

  • Better performance in conditional reasoning tasks presented in concrete terms rather than abstract.

Cognitive Biases

• Types of Errors:

  • Form Errors: Misinterpretations of conditional logic (e.g., If P then Q ≠ If Q then P).

  • Search Errors (Confirmation Bias): Tendency to seek supportive evidence while ignoring conflicting data.

• Strategies for Mitigation:

  • Open-mindedness, evaluation of diverse perspectives, and reliance on objective data.

Heuristics in Decision-Making

• Definition:

  • Mental shortcuts simplifying decision-making, though resulting in potential biases.

• Types:

  • Availability Heuristic: Basing judgments on easy-to-recall examples.

  • Representativeness Heuristic: Judging likelihood based on prototype similarity.

  • Anchoring Bias: Heavily relying on initial information presented during decision-making.

• Shaping Decisions: Understanding heuristics' limitations can enhance decision accuracy.

Framing Effect

• Definition:

  • Describes how information presentation affects decisions, can lead to differing outcomes based on framing contexts.

• Examples:

  • Surgery success framed as 90% survival leads to more positive assessments than a 10% mortality.

Intelligence Overview

• Definition:

  • Ability to apply knowledge effectively in reasoning, problem-solving, and adapting to challenges.

• Historical Tests:

  • Binet & Simon’s initial test for educational support; Terman’s Stanford-Binet adaptation focusing on academic potential.

• Wechsler Scales:

  • Separate verbal, non-verbal, and full-scale IQ scores, using normal distribution for scoring.

Correlation of Intelligence and Academic Success

• Reliability of Tests:

  • Generally high (>0.90 correlation coefficients), ensuring consistency.

• Validity Measures:

  • Assessments predict academic success effectively (correlation with grades between 0.40 and 0.70).

• Career Success Predictions:

  • Moderate correlations between IQ and occupational attainment, income, and job performance (ranging from 0.21 to 0.50).

Emotional Intelligence (EI)

• Definition:

  • The ability to recognize, understand, and manage emotions in oneself and others, encompassing self-awareness, self-regulation, motivation, empathy, and social skills.