Problem Solving and Expertise Notes

Problem Solving and Expertise

Introduction

• Problem solving involves cognitive processing to achieve a goal when there's no obvious solution.
• Transfer refers to how past learning impacts current tasks.
• Expertise involves efficient problem-solving in a specialized area, differing from general problem-solving with its focus on knowledge and individual differences.
• All involve generating options and applying knowledge, but have evolved into separate research areas.

Problem Solving

• Problem solving is purposeful, controlled, and requires knowledge.
• Well-defined problems have clear initial states, moves, and goals, whereas ill-defined problems are underspecified.
• Psychologists focus on well-defined problems due to their optimal strategies and known answers.
• Knowledge-rich problems require specific knowledge, unlike knowledge-lean problems.
• Monty Hall Problem: Illustrates problem-solving fallibility due to heuristics, limited processing, and misrepresentation of causal structures.

Gestalt Approach

• Gestaltists emphasize productive thinking (novel restructuring) over reproductive thinking (re-use of past experiences).
• Insight involves sudden problem restructuring with an "ah-ha" experience.
• Insight may be a slower learning process rather than a sudden flash. Facilitation through cues can aid problem-solving.
• Insight existence is supported by introspective, behavioral, and neuroimaging evidence.
• Brain Activity in Insight:
  • Right hemisphere's anterior superior temporal gyrus is activated.
  • High-frequency brain activity occurs one-third of a second before insightful solutions.
  • The anterior cingulate cortex is activated during cognitive conflict.
• Functional Fixedness: Past experience can hinder problem-solving by limiting the perceived uses of objects.
• Einstellung (Mental Set): Tendency to use well-practiced strategies even when suboptimal.

Representational Change Theory

• Impasse broken by changing problem representation through elaboration, constraint relaxation, or re-encoding.
• Constraint relaxation is key to insight, as shown by the mutilated draughtboard problem.
• VI = VII + I becomes VII = VI + I
• IV = III − I becomes IV − III = I
• Constraint reduction is vital in solving insight problems.

Incubation

• Problems are solved more easily by ignoring them for some time.
• Subconscious mind continues to work toward solution.
• Effective with creative problems having multiple solutions.
• Forgetting misleading information aids in adopting new approaches.

General Problem Solver

• Computer simulations of human problem solving.
• Relies on serial processing, limited short-term memory, and long-term memory retrieval.
• Problem Space: Initial state, goal state, mental operators, and intermediate states.
• Reliance on heuristics (rules of thumb) instead of algorithms (complex methods).
• Means-ends analysis: Reducing difference between current and goal states.
• Hill climbing: Changing problem state closer to goal.
• Progress monitoring leads to changing strategies if progress is slow.

Problem Solving: Brain Systems

• Frontal cortex (especially dorsolateral prefrontal cortex) heavily involved.
• Prefrontal damage impairs planning and making difficult moves.
• Right dorsolateral prefrontal cortex linked to Tower of London/Hanoi problems, left to water-jar problems.
• Response inhibition is important for successful performance on such tasks.

Adaptive Control of Thought – Rational (ACT-R)

• Aims to provide a theoretical framework for understanding information processing and performance.
• Cognitive system comprised of seven modules, including retrieval, imaginal, goal, and procedural modules.
• Each module has a buffer containing limited information.

Transfer of Training and Analogical Reasoning

• Positive Transfer: Past experience aids current problem-solving.
• Negative Transfer: Past experience hinders current problem-solving.
• Far Transfer: Benefits in dissimilar contexts.
• Near Transfer: Benefits in similar contexts.
• Transfer influenced by task similarity, context similarity, and time interval.
• Increased by metacognitive skills, such as orienting and self-judging.

Analogical Problem Solving

• Using similarities between current and past problems.
• Types of similarity: superficial, structural, and procedural.
• Success depends on noticing and using similarities.
• Superficial Similarity: Solution-irrelevant details common to problems
• Structural Similarity: Causal relations among main components are shared
• Procedural Similarity: Procedures for turning solution principle into concrete operations are common.

Expertise

• Expertise involves highly skilled performance in a domain through knowledge and skills acquired over years.
• Medical expertise, such as accurate diagnoses, depends on experience, contrasting explicit vs. implicit reasoning.

Chess Expertise

• Requires extensive practice (ten-year rule).
• Chess masters have detailed knowledge of chess positions in long-term memory.
• Knowledge organization into chunks.

Template Theory

• Addresses weaknesses in chunking theory.
• Common chunks develop into templates, abstract schematic structures with variable slots.
• Larger and fewer templates, superior template-based knowledge.

Medical Expertise

• Medical reasoning of experts differs considerably from that of novices.
• Explicit Reasoning: Slow, deliberate, conscious.
• Implicit Reasoning: Fast, automatic, unconscious.
• Can often use stored exemplars.

Deliberate Practice

• Key to developing a wide range of expertise.
• Task difficulty appropriately, informative feedback, repetition, error correction.
• Long-term working memory: storing relevant information in long-term memory and accessing it through retrieval cues in working memory.
• Deliberate practice is not only necessary but will also lead to greater expertise.