Thinking and Intelligence

Macroposia

ThinkingThe processing of information to solve problems, make judgments,

and make decisions

Problems ❖ A problem is a situation in which there is a goal, but it isn’t clear how to reach

the goal.➢ A well-defined problem is a problem with clear specifications of that start state, goal state, and

the process needed to reach the goal state.

➢ An ill-defined problem is one in which the problem is lacking a clear specification of the start site,

goal site, or process by which the goal state can be met.

Interpreting the Problem ❖ 2 general steps to problem solving:

➢ Step One: interpreting the problem

➢ Step two: trying to solve the problem

❖ Fixation is the inability to think outside the box and create a new interpretation of a problem

❖ Functional fixedness is the inability to see that an object can have a function

other than its typical one in solving a problem

➢ Ex: We need a screwdriver but we don’t have one. However we don’t think about using

something like a coin that could function as a screwdriver

Solving the Problem ❖ Mental set is the tendency to use previously successful problem-solving

strategies without considering others that are more appropriate for the current problem➢ Don’t always try the same solution for every problem. Some problems will require unique

solutions that you haven’t tried before

❖ Insight a new way to interpret a problem that immediately gives the solution➢ Rapid understanding is the key to the solution

❖ To be good problem solvers we need to:➢ Be open to new interpretations of problems and new ways of using objects to solve them

➢ Develop a broader, more effective set of solution strategies

Solution Strategies❖ Solution strategies can be divided into two steps:

➢ Algorithms

➢ Heuristics

❖ An algorithm is a step-by-step procedure that guarantees a correct answer to solving a problem ➢ Ex: solving a math problem with long division

❖ Heuristic is a problem solving strategy that seems reasonable given one’s past experience with solving similar problems, but does not guarantee a correct answer to a problem.➢ More like an educated guess

Anchoring and Adjustment ❖ The Anchoring and Adjustment Heuristic is used in estimation problems in

which one uses his/her own initial estimate as an anchor estimate and then adjusts it up or down ➢ Ex: The inclusion of minimum payment information on credit card statements. These minimum

payments act as a psychological anchor

❖ This heuristic leads us to fail to adjust the anchor enough because we tend to be too attached to the initial anchor and don’t adjust it enough

❖ Don’t become too attached to the initial anchor amount when making judgments and decisions!

Working Backward❖ Working backward heuristic is a problem solving heuristic in which one

attempts to solve a problem by working from the goal state back towards to start state ➢ Ex: Water lilies growing in a pond double in are every 24 hours. On the first day of spring, only

one lily pad is on the surface of the pond. 60 days later, the pond is entirely covered. On what day

is the pond half covered?

❖ Working backwards is ideal for problems that have many possible paths from the start state to the goal state, but only one path (or a few) from the goal state to the start state

Means-End Analysis❖ Means-end analysis heuristic is one in which the distance to the goal state is

decreased systematically by breaking the problem down into subgoals and achieving these subgoals

Thinking Under Uncertainty ❖ We suffer from an emotional need for certainty when we live in an uncertain

world❖ We also suffer from statistical innumeracy: the inability to reason from

uncertainties and risk❖ Everything has a probability

➢ The probability that it will rain today

❖ We attempt to reduce our uncertainty of events around us by trying to figure out how various events are related to each other ➢ Ex: amount of arthritis pain and the weather conditions

Representative Heuristic❖ This is a heuristic for judging the probability of membership in a category by how

well an object resembles that category ➢ The more representative, the more probable

❖ The conjunction fallacy is incorrectly judging the overlap of two uncertain events to be more probable than either of the two events➢ Overlooks essential information for making the probability judgment

❖ Gambler’s fallacy is incorrectly believing that a chance process is self-correcting in that an event that has not occurred for a while is more likely to occur

❖ Categorization is one of the brain’s basic operational principles (normal operation)➢ We categorize people based on the information we get when we first meet them

❖ This initial judgment is an anchor that will need to be adjusted

Availability Heuristic ❖ This is the rule of thumb that the more available an event is in our memory, the

more probable it is➢ We can think of more words that begin with r than words with r in the third position because of

how we categorize words with the letter they begin with

❖ A heuristic does not guarantee a correct answer➢ Ex: we think about the various causes of death, and we think of things highly publicized such as

airplane crashes, fires, and shark attacks as more common. Whereas diabetes and emphysema

are more likely to cause death, but not highly publicized and therefore not common in our

memory

❖ Greater availability in memory doesn’t always mean greater probability

Why Do We Use Heuristics?❖ We rely on heuristics for two reasons:

➢ They are adaptive and often serve us well and lead to a correct judgment

➢ They stem from system 1 processing

❖ System 1 (automatic) processing is part of a dual processing system that is contrasted with system 2 (reflective) processing

❖ System 1 is known to be fast, intuitive, and largely unconscious thinking whereas system 2 is slow, analytical, and consciously effortful thinking

❖ System 2 can override system 1, but it is lazy❖ You should work to engage system 2 thinking

➢ Don’t rush judgments

Confirmation Bias ❖ The confirmation bias is the tendency to seek evidence that confirms one’s beliefs ❖ Confirmation bias can lead us to perceive illusory correlations between events in

our environment ❖ Illusory correlations is the erroneous belief that two variables are statistically

related when in reality they are not❖ We suffer from belief perseverance: the tendency to cling to one’s own beliefs in

the face of contradictory evidence ❖ Our beliefs constitute a large part of our identity, making it hard for us to admit

when we are wrong

❖ This denial is illustrated by person-who reasoning: questioning a well-established

research finding because one knows a person who violates the finding

History of Intelligence Tests❖ Sir Francis Galton tried to develop intelligence tests for the purpose of eugenics

(selective reproduction to enhance the capacities of the human race) in the late 19th century➢ He thought he could measure intelligence by measuring various aspects of the human brain and

nervous system

➢ He thought that more intelligent people would have more acute senses, greater strength, and

faster reactions to stimuli

❖ In France during the start of the 20th century, Alfred Binet and his assistant Theophile Simon were creating a test to diagnose children whose intellectual development was subnormal and who wouldn’t be able to keep up with their classmates➢ This test was published in 1905 as the first accepted test of intelligence

Intelligence Tests❖ The Binet-Simon test calculated a child’s mental age that could then be used to

diagnose academic retardation➢ Mental age is the age typically associated with a child’s level of test performance

❖ Lewis Terman revised the test for use with American schoolchildren ➢ He used the intelligence quotient (IQ) formula that was the mental age divided by the

chronological age, then multiplied by 100

❖ David Wechsler devised his own test that became known as the Wechsler Intelligence Scale for Children (WISC) and the Wechsler Adult Intelligence Scale (WAIS)➢ WISC was for children ages 6-16

➢ WAIS was for ages 16 and older

Deviation IQ Scores ❖ Deviation IQs involve standardization❖ Standardization is the process that allows test scores to be interpreted by

providing test norms❖ To calculate a person’s deviation IQ score, Wechsler compared the person’s

raw test score to the normal distribution of raw scores for that person’s standardization age group

❖ He then defined the deviation IQ score as: 100 plus or minus (15x the number of standard deviations the person is from the raw score mean for their standardization group)

Handout Time

IQ Handout Answers1. $.52. 253. D.4. A. and C.5. A.

Reliability and Validity ❖ In addition to being standardized, a good test must also be reliable and valid❖ Reliability is the extent to which the scores for a test are consistent

➢ Alternate-form reliability is determined by giving different forms of the test to the same sample

at different times and computing the correlation coefficient for performance on the two forms

➢ Split-half reliability is when the performance on half of the test is compared to the performance

on the other half (odd vs even)

❖ Validity is the extent to which a test measures what it is supposed to measure or predicts what it is supposed to predict ➢ Content validity is the first part, which means that the test covers the content that it is supposed

to cover

➢ Predictive validity is the second part, which means that the test predicts behavior that is related

to what is being measured by the test

Theories of Intelligence ❖ Charles Spearman argued that intelligence test performance is a function of

two types of factors:➢ G factor (general intelligence)

➢ S factors (specific intellectual abilities such as reasoning)

❖ L. L. Thurstone argued that there were 7 primary mental abilities: verbal comprehension, number facility, spatial relations, perceptual speed, word fluency, associative memory, and reasoning ➢ These 7 abilities were identified using the factor analysis: a statistical technique that identifies

clusters of test items that measure the same ability (factor)

❖ Raymond Cattell and John Horn proposed that the g factor should be viewed as 2 types of intelligence:➢ Fluid intelligence: abilities independent of acquired knowledge

➢ Crystallized intelligence: accumulated knowledge and verbal and numerical skills

Theories cont.) ❖ Howard Gardner argued that there are 8 independent intelligences: linguistic,

logical-mathematical, spatial, musical, bodily-kinesthetic, intrapersonal, interpersonal, and naturalist

❖ Robert Sternberg argues for three types of intelligence: analytical, practical, and creative

❖ Keith Stanovich believes that intelligence is a meaningful, useful construct and is not interested in expanding the definition of intelligence➢ Argues that intelligence is only one component of good thinking and thus by itself is not

sufficient to explain such thinking

❖ Dysrationalia is the failure to think and behave rationally despite having adequate intelligence

Nature vs Nurture ❖ Both components (nature and nurture) are necessary, however it is debated how

much of each one is contributed ❖ Heritability is an index of the degree that variation of a trait within a given

population is due to heredity❖ Heredity determines a reaction range: the genetically determined limits of an

individual’s intelligence ❖ Heredity places an upper and lower limits on a person’s intelligence, however the

quality of a person’s environment determines where they fall within this range❖ Two points about heritability:

➢ It is a group statistic and is not relevant to individual cases

➢ It is important to understand that heritability has nothing to do with differences that have been

observed between populations

❖ Heritability only applies to variation within a given population or group, not to variation between groups

Flynn Effect❖ The Flynn Effect is the finding that the average intelligence test score in the

United States and other industrialized nations has improved steadily over the last century

❖ Explanations for this include: improved nutrition, hygiene, and the availability of medical services to better education and smaller average family size

❖ This Flynn hypothesis is supported by the finding that large intelligence increases have not been observed for all types of cognitive functioning

The EndBy: Hannah Dunacusky, Sarah Campbell and Sullivan Stockwell