1: reasoning skills development

Question 1

what is understanding probability

Answer 1

• important cognitive skill
• Frost et al (2019) allowing organisms to learn about regularities in environment

Question 2

understanding probability in context of sensory input

Answer 2

– understanding probability in the context of sensory input involves recognising how often different events occur

Question 3

What is statistical learning

Answer 3

• process of detecting and learning patterns or regularities in the environment that are either spatial (physical space) or temporal (time)

Question 4

What does statistical learning allow

Answer 4

Allows individuals to predict future events based on the frequencies and sequences of stimuli they encounter

Question 5

What is statistical learning an important mechanism of

Answer 5

An important mechanism of language learning

Question 6

How do infants use statistical learning to learn language

Answer 6

They detect and internalise patterns and structures in spoken language.

it involves recognizing statistical regularities in sounds and syllables and words

Helps them recognise which syllables are likely to occur together and which are not, allowing them to segment words from speech

Question 7

Statistical learning and language study

Answer 7

Saffran et al (1996)

• 8m infants could distinguish words from non words in an artificial language after being exposed to a stream of syllables based on statistical properties

Question 8

What is predictive learning and an example

Answer 8

As children grow, statistical learning allows them to predict the next word or sound based on context

For example: if a child hears “I want to eat” they may predict next word will relate to food

Question 9

3 aspects to probability understanding

Answer 9

• detecting regularities
• incorporating prior knowledge and new evidence
• generalising prior statistical knowledge to new situations

Question 10

Xu and Garcia (2008) study

Answer 10

• showed infants expected and unexpected outcomes
• infants looked longer at unexpected outcome
  -sensitive to base rates - looked longer when first shown context of box and experimenter drew unlikely sequence of balls

Question 11

What are base rates

Answer 11

• underlying distribution of a set of outcomes in a population
• statistical info which is overlooked

Question 12

What are base rates

Answer 12

• underlying distribution of a set of outcomes in a population
• statistical info which is overlooked
• base rate = general probability

Question 13

Base rate neglect

Answer 13

Cognitive bias where people tend to ignore the general probability (base rate) of an event in favour of specific info

Question 14

What does base rate neglect lead to

Answer 14

• faulty judgements like overestimating or underestimating likelihood of event

Question 15

Explain the engineer- lawyer problem

Answer 15

• how people neglect base rates for making judgements
• kahenman & Tversky (1973)

In a group of 100 people: 70 are a lawyer and 30 are an engineer

Presented with a description of a randomly selected individual from the group e.g Dave js very analytic and spends lots of time on his hobbies like maths puzzles. he prefers working alone

Asked a question on what’s the probability that Dave is a lawyer

Most people rely on the specific info about Dave and ignore the base rates

A lot more lawyers than engineers in the sample, should be more inclined to pick lawyer

Question 16

What assumption did the engineer- lawyer problem challenge

Answer 16

Challenged with the assumption that humans are always rational

Question 17

Why do some people think base rate neglect occurs? Study to back it up

Answer 17

Reasoning in probabilities is not natural for humans

gigerenenzer and Hoffrage (1995)
- people reason more accurately when probability problems are said in frequencies
- e.g instead of 10% chance, say 10 out of 100 people.
- putting problems into frequencies reduces errors

Question 18

how to identify base rate neglect in children

Answer 18

to identify specific skill in children, have to isolate crucial ability and remove unnecessary procedural knowledge.
- determine appropriate testing conditions e.g. suitable for age and developmental stage of child.

Question 19

describe Girotto and Gonzalez (2008)

Answer 19

can 3-10y use base rates to correctly choose which outcome is most likely

• shown box with blue and yellow chips
• more blue chips in box than yellow
  asked to predict wether blue or yellow chip would be drawn

5y children could identify more likely outcome
- 5y could use base rates to make correct judgements around 5

Question 20

why do adults ignore base rates if children use them

Answer 20

representative heuristic

Question 21

what is representative heuristic

Answer 21

type of initiative rule of thumb where you ignore base rate info and focus on individuating info

Question 22

Guatheri and Denison (2018)- representative heuristic study

Answer 22

• info in study either pointed to blue (nice) robot or green (bad) robot.
• base rate 80% blue, 20% green
  -base rate and specific info revealed- all children performed well
• base rate and specific case info conflicted- all groups struggled to use base rate correct

-4y relied more on base rate info- prefer statistical info
- older children nd adults preferred case specific info
- as children age past 4- start to show preferences for specific info rather than base rates

Question 23

Gualtieri et al (2019) base rates and eye witness

Answer 23

children as young as 4-5 combine base rates with eyewitness testimony accuracy- depending on reliability of eyewitness- showing reasoning skills

Question 24

what is over hypothesis learning

Answer 24

• it is not ideal for people to ignore base rates and focus on testimony
• allows learners to make predictions about general situations
• allows abstract knowledge to be formed and applied to new circumstances
  -avoids trial and error in each situation

Question 25

Frost et al (2019) over hypothesis learning

Answer 25

• relying on prior info is helpful cue
• we come to situations having already learned a lot about the world

Question 26

what is induction

Answer 26

• making generalisations from specific examples
• generalising info from specific instances to form general rules, e.g. learning words, casual reasoning
• instead of 2 different situations, needing 2 separate rules, more efficient to form general abstract rules that can be applied to multiple situations

Question 27

Dewar and Xu (2010) and how does it demonstrate inductive reasoning

Answer 27

• infants observe sequences where certain patterns were followed by outcomes which were expected or unexpected
• experimental condition- object drawn from box which breaks the pattern- reaction measured by how long they looked at outcome
  -longer gaze suggests these detect the difference
• control condition= outcome expected based on prior patterns- infants attention less drawn- shows they find outcome predictive

demonstrates how infants use inductive reasoning to form expectations about what should happen next. showed surprise when they had no built expectation on what would happen next

Question 28

over hypothesis learning study

Answer 28

Felsche et al (2019)

• is it a evolutionary primitive skill shared with other species or is it recently evolved and only found in humans
• 80 children aged 4-5 and 11 monkeys (6y)
• tested over hypothesis formation for rewards from buckets
• children would learn from previous draws and were more likely than chance to chose high value reward from new buckets
• monkeys always at chance as to which reward to pick

Question 29

when do infants start to develop over hypothesis

Answer 29

1st year of life
even in infancy- children are rational constructivist learners