Expertise and Skill Acquisition

Question 1

Gladwell (2008) expert

Answer 1

Need 10,000 hours in something to become an expert

Question 2

Ericsson, Krampe and Tesch-Romer (1993)

Answer 2

Amount of practice by violinists at a music academy in Berlin. The best practiced for more than 7000 hours, the
very good practiced only 5000 hours

Deliberate practice = learners are motivated to learn and compare their performance to feedback/identify/work on any weaknesses

Question 3

Define Difference Reduction

Answer 3

Observed in humans/animals. Aim to consistently reduce the difference between the observed and desired state

e.g. Jeffries et al (1977) Hobbits and Orcs, Atwood and Polson (1976) water jugs, Kohler (1927) behaviour of a chicken attempting to reach food through a fence (just go around, have to move away from goal in order to reach it)

Question 4

Means-end Analysis

Answer 4

The means temporarily becomes the end. It solves the problem of local maxima but may require effort at first (problem solving)

Proceduralisation = learning and remembering in maths saves time/effort calculating (Anderson, 1982), skills become less reliant on declarative memory and involve more procedural memory

Logan’s instant theory of automaticity (Logan, 1988) incorporates this idea and accounts for the power of low practice findings. The more training you’ve had, the faster you will be at learning it

Question 5

Chase and Simon (1973) pattern learning

Answer 5

Expert chess players see patterns and know the names of pieces. The positions make sense to the experts, not the novices

A situation is divided into meaningful ‘chunks’ enabling the expert to take full advantage of stored knowledge in LTM

Question 6

Learned Knowledge

Answer 6

Verbal behaviour, how language is learnt (Skinner, 1957)

Question 7

Innate Knowledge

Answer 7

Language acquisition device, disagreed, there are sentences that have never been said before/make no sense, ‘poverty of the stimulus argument’ (Chomsky, 1959)

Question 8

Machine Knowledge/Learning

Answer 8

e.g. chat-GPT, ‘large language models’, artificial neural networks pretrained using reinforcement and supervised learning algorithms (involving explicit correction of errors), all learned… nothing is innate

Question 9

Face Recognition (e.g. Morton and Johnson, 1991; Johnson, Senju and Tomalski, 2015)

Answer 9

A similar process to chick imprinting is happening in infants learning human faces

Conspec = neonates have very low visual acuity (can’t see clearly) but are interested in shapes that look like faces, innate

Conlern = responsible for learning visual features of faces