Discuss, with examples, the nature of well-defined knowledge-lean problems and ill-defined, knowledge-rich problems in terms of their relevance to real-world problem-solving
- Well-defined problems – all aspects of the problem clearly stated, including initial conditions
- Ill-defined problems – problems underspecified and not enough information or available resources
- Knowledge-rich problems – need specialist knowledge
- Knowledge-lean problems – information required to solve problem is contained in the problem statement
- g. researchers – well-defined, knowledge-lean problems
- Real life problems are usually ill-defined and knowledge-rich problems for which the ‘correct’ or ‘best’ solution is unknown
Compare and contrast the naturalistic and rational decision-making paradigms and discuss their relationship to notions of expertise. Consider how the dual system model of decision-making might align with the two paradigms
- Our notions of expertise are tied to our notions of good decisions and problem solving Two decision-making paradigms:
- Unconscious processing (intuitive, automatic, immediate) – proposes intuitive answers to judge problems as they arise ~ operates under time pressure and uncertainty
- Conscious processing (analytical, controlled, rational) – monitors the quality of these judgements – it may endorse, correct, or override ~ requires sufficient information and sufficient time
Naturalistic (descriptive) paradigm (Simon)
- Decision making in complex and cognitively challenging environments
- Sense making in uncertain situations
- Situational awareness (assessment)
Rational (normative) paradigm (Klein)
- Not all relevant information is known to us, and cannot compare all possible outcomes to make best choice (optimization)
- Boundaries to rationality (constraints) due to:
o Environmental constraints o Mental constraints o Temporal constraints
Rational vs Naturalistic
- Rational models of thinking dominant as they are most accessible to non-experts, and have agreed on methods and metrics
- Naturalistic models do not lend themselves to laboratory studies
- Naturalistic decision making studies use a mixture of methodologies, many of which are qualitative and opportunistic in nature
- New opportunities for studying expertise using complex game scenarios with inbuilt metrics
Discuss the nature of expert skilled performance in a specific domain. Explain the role of “chunking”, pattern abstraction templates and schemas in domain specific expertise
Expertise
- Expertise is domain-specific knowledge acquired over many years
- Routine expertise – using acquired knowledge to solve familiar problems efficiently
- Adaptive expertise – using acquired knowledge to solve novel problem or to make decisions under uncertainty or time-pressure
Domain Specific Expertise – Ericsson’s Expert Performance Model
- Complex decisions are made in risky, uncertain situations under time pressure
- Task execution involves cognitive processing and perceptuomotor coordination (vision for perception vs vision for action)
- Expertise is domain-specific and often does not transfer to new domains (can have negative transfer) – experts can have extremely deep, but narroe knowledge
- g. Experts in Chess
- Chess – a complex game of strategy that has documented levels of skill culminating in Grand Master (a universally recognized hallmark of expertise)
- Chess can then be played by novices who are then able to recognize the skill of Grand Masters
- Ericsson – long term working memory using retrieval cues (pattern fragments) based in short term memory
Chunking
- Remembering a chunk or package of information (a unit of meaning) by a pattern fragment ‘key’
- STM holds 7+/- 2 chunks of information (Miller, 1956)
- Experts appear to be able to expand their working memory by having fast information retrieval and manipulation via chunking
Describe the role of deliberate, effortful practice in the acquisition of competence and expertise. Discuss the role that expertise plays in decision-making under uncertainty or time pressure