1. 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

2. 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)

3. 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)

4. Conditional ReasoningK 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)

5. 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.

6. 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.

7. Video clip

8. 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)

9. 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

10. 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’.

11. 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.

12. 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…

13. 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

14. 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)

15. 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.