Models of Long-Term Memory Connectionist Approach (Semantic LTM) Schema Theory (Episodic LTM) Network of Associations What do we need this information for? Thinking, Reasoning and Problem-Solving Learning from our Past

Cognitive Activity 1: Thinking Automatic, instantaneous, unconscious retrieval of information ‘Thinking’ is driven by the level of domain-knowledge Chunking (Chase & Simon, 1973) Subordinate Level Classification (Tanaka & Taylor, 1991) Finer level discrimination (Whorf’s linguistic hypothesis)

Cognitive Activity 2: Reasoning and Problem-Solving Effortful, time-consuming and consciously driven, linkage of information to solve a problem. Syllogistic Reasoning: All As are Bs All Bs are Cs So: All As are Cs Conditional If-Then statements Reasoning: (Wason Card Task) (Wason & Johnson-Laird, 1972)

Conditional Reasoning K 4 7 If a card has a vowel on one side then it has an even number on the other side Computers: very good at these tasks. Humans: 33% turn over E only 46% turn over E and 4 only 4% show correct performance (E, 7)

Realistic Wason-Type Task If the envelope is sealed then it needs a more expensive stamp (Johnson-Laird, Legrenzi & Legrenzi, 1972) 21/24 (87.5%) of participants produce the right combination of moves in this example (sealed envelope, envelope with cheap stamp). Knowledge overcomes previous confirmatory bias.

Problem-Solving Scenarios Recreational Problem #1: I met a man on the way to St Ives. The man had 7 wives, and each had 7 sacks. In each sack were 7 cats, and each cat had 7 kittens. How many were going to St Ives? GPS: thrown by language Humans: Can eventually reach the solution but can be lured by the detail.

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Problem-Solving Scenarios Recreational Problem #2: You have 2 measuring jugs. One holds 5 gallons. The other holds 3 gallons. How do you measure exactly 4 gallons? GPS: Finds this task difficult – violates the ‘means-end’ heuristic Humans: Difficult but insight can overcome the logical block (‘eureka’ moment)

How do Humans Solve Problems? We don’t work according to logic. We show biases: a confirmatory bias We show an influence of our prior knowledge: experience helps problem-solving through analogy/generalisation automating aspects of the solution to lighten mental load

Functional Fixedness By moving only one beaker, get to the stage whereby alternate beakers contain water. Domain-knowledge can lead to think only within one schema and only think of one (traditional) use for an object. Problem-solving through creativity requires that you overcome this functional fixedness and ‘think outside the box’.

Thinking about our Thinking Our awareness of our own memory give us: a verbal protocol – a measure of performance metamemory judgements – insight on performance Domain knowledge can affect metamemory as much as memory.

Metamemory following inaccessibility ‘TOT’ state (Tip of the Tongue State) can be accompanied by a ‘Feeling of Knowing’ (FOK – see Asher Koriat). Feeling of Knowing can bias further search of memory Domain-knowledge affects this metamemory judgement: I ought to know this I have a partial recall – I nearly have it…

Metamemory following Retrieval Successful retrieval can be accompanied by metamemory judgements which validate the retrieval (or otherwise). Speed of retrieval Ease of retrieval Processing fluency Confidence Decision to report/withhold Domain-knowledge can affect these judgements also: Familiarity, Accessibility, Expectancy, Stereotypy

Validity of Metamemory “We often have useful insights into our own mental processing, and just as often have no insight at all.” (Ashcraft, 1994, p 380)

Summary - Knowledge allows us to learn from our past associations. - Thinking is largely unconscious, instantaneous and effortless. - Reasoning and problem-solving is effortful and consciously driven. - Cognitive activity is affected by level of domain-knowledge. - Our beliefs about our cognitive activity is affected too. - Domain-knowledge can help and can hinder us.