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Cognitive Psychology > Expertise > Flashcards

Expertise Flashcards

1
Q

Development of expertise is similar to

A

problem-solving because experts are extremely efficient at solving various problems in their area of expertise using their extensive knowledge base.

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2
Q

What is Problem Solving?

A

It is purposeful (i.e., goal-directed)

A problem only exists when someone lacks the relevant knowledge to produce an immediate solution

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3
Q

Problem solving sequence

A

Problem solver in one state (where theres a problem)
Problem solver wants to reach another state (no problem)
Bridging gap is mutlitple step process

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4
Q

Well-Defined Problems

A

All aspects of the problem are specified.

Have an optimal strategy and one right answer

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5
Q

Ill-Defined Problems

A

Underspecified goals

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6
Q

Illustrating the difference between well defined and ill defined problems

A

Case of PF
Damage to right prefrontal cortex (involved in higher order processes in achieving a goal)
Performed well on Laboratory but not on ill-defined problems

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7
Q

Knowledge-Rich Problems

A

Can only be solved by individuals possessing a considerable amount of specific knowledge

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8
Q

Knowledge-Lean Problems

A

Don’t require the possession of specific knowledge

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9
Q

Thorndike (1898)

A

Trial-and-error learning

Used arbitrary relationships between behaviour and goal

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10
Q

Gestaltists

A

More flexible approach

Focussed on the more complex, productive thinking - insight

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11
Q

Insight

A

The sudden restructuring of a problem, not obvious

Often accompanied by an “ah-ha” experience

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12
Q

How does insight occur?

A

Representational change theory
Constraint relaxation
Re-coding
Elaboration

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13
Q

Representational change theory

A

changing representation of problem

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14
Q

Past experience

A

Functional fixedness
Mental set
Inflexible

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15
Q

Functional fixedness

A

Dunker’s (1945) candle problem

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16
Q

Mental set

A

Use previous problem solving strategy and we stick with it if it wasn’t successful

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17
Q

Computational approach-Newell & Simon (1972)

A

General Problem Solver-Computer program designed to solve numerous well-defined problems

Problem space includes
Initial state of the problem
Goal state
Possible mental operators

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18
Q

Problem-solving strategies for limited capacity

A

Heuristics
Algorithms
Means–ends analysis

19
Q

Heuristics

A

Rules of thumb
Often no clear idea of structure
Focus on short-term goals

20
Q

Algorithms

A

Methods or procedures for solving a problem

Mathematics

21
Q

Means-End Analysis

A

Note the difference between the current state of the problem and the goal state

Form a subgoal that will reduce the difference between the current and goals states

Select a mental operator that will permit attainment

22
Q

Evidence supporting Newell & Simon (1972) Computational framework

A

The approach works well with several well-defined problems

Specifies the shortest sequence of moves from initial state to goal

23
Q

Problems with Newell & Simon’s computational framework (1972)

A

Better than humans at remembering what happened on a problem but inferior to humans at planning future moves

Everyday life problems are ill-defined

Performance on insight problems?

Doesn’t take into account Individual differences

24
Q

Analogical problem solving

A

Involves using similarities between current problem and one or more problems solved in the past

25
Q

How does analogical problem-solving occur?

A

Detecting similarity between problems (Chen (2002))

Superficial similarity (solution irrelevant details)

Structural similarity

Procedural similarity

26
Q

Gick and Holyoak (1980)

A

showing the percentage of subjects who solved Dunker’s radiation problem when they were given an analogy (general-story condition) or were just asked to solve the problem (control condition).

27
Q

Analogical Problem Solving

A

Used when direct knowledge does not exist
Depends on working-memory components (Morrison, Holyoak, and Truong (2001))
Depends on frontal executive processes

28
Q

EXPERTISE

A

highly skilled performance in one or more task domains

29
Q

What Makes a Chess Expert?Chase and Simon’s (1973a) chunking theory

A

Detailed information about chess positions stored in long-term memory

30
Q

Problems with chunking

A

Predicts that it will take longer than it actually does to encode chess positions

31
Q

Template Theory

A

A core: similar to fixed information stored in chunks
Slots: contain variable information about pieces and locations
Adaptable and flexible
Abstract schematic structure

32
Q

Predictions of template theory

A

Chess positions stored in three large templates
Template knowledge can be accessed rapidly
Precise location of chess pieces stored in template

33
Q

Template Theory Strengths

A

Evidence supports notion that board positions are stored in a few templates
Outstanding chess players possess much more template-based knowledge of chess positions than non-experts
Experts have better memory for random positions

34
Q

Template Theory Limitations

A

Slow search processes are more important than credited

Doesn’t fully explain adaptive expertise

Controversy over what is stored in Long Term Memory

Individual differences

35
Q

Medical expertise

A

Ability to make rapid and accurate diagnoses

Complex decision-making

36
Q

Medical Expertise: Engle’s (2008Explicit/Analytic Reasoning or Focal Search

A

Relatively slow
Deliberate
Associated with conscious awareness
Analytic, rule-based strategies

37
Q

Medical Expertise: Engle’s (2008) Implicit/Non-Analytic Reasoning or Global Impression

A

Fast/automatic

Holistic/global

Gist-based

38
Q

Identifying diagnostic strategies used by medical novices and experts

A

Tracking eye movements while examining case slides – Krupinsky et al 2006
Pathologists spent less time examining each slide (4.5 seconds versus 7.1 residents and 11.9 students)
More information extracted from initial fixation for pathologists – relying on global impression

39
Q

Medical Expertise Research Strengths

A

Medical experts generally do rely more on fast, automatic processes in diagnosis than novices
Experts tend to outperform non-experts

40
Q

Medical Expertise Research Limitations

A

Not enough has been done to learn how experts gain their expertise

Raises the danger of underestimating analytic processing

If and how experts use stored exemplars versus gist, needs to be explored

41
Q

Chess Expertise vs. Medical Expertise: Similarities

A

Years of intensive training
Large and accessible store of relevant knowledge
Better able to make use of rigid, automatic processes
Ability to make flexible use of analytic or strategy-based processes

42
Q

Chess Expertise vs. Medical Expertise: Differences

A

Chess: knowledge stored in fairly abstract templates; need to relate current position to stored knowledge and think deeply about the implications for their subsequent moves, and their opponents
Medicine: knowledge stored as less abstract exemplars; face a more narrowly focused task, relating information they have to stored knowledge

43
Q

Plasticity

A

changes in structures and functions of the brain that can affect behaviour as a result of training

44
Q

Deliberate Practice

A 
Task difficulty
Informative feedback
Repetition of  task 
Correct errors
Relevant knowledge base
Time factor
Innate talent/ability should NOT matter

Cognitive Psychology (2 decks)

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