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Thinking and Intelligence Psychology: A Concise Introduction 2 nd Edition Richard Griggs Chapter 6 Prepared by J. W. Taylor V.

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Presentation on theme: "Thinking and Intelligence Psychology: A Concise Introduction 2 nd Edition Richard Griggs Chapter 6 Prepared by J. W. Taylor V."— Presentation transcript:

1 Thinking and Intelligence Psychology: A Concise Introduction 2 nd Edition Richard Griggs Chapter 6 Prepared by J. W. Taylor V

2 Thinking The processing of information to solve problems and make judgments and decisions

3 The Journey… Problem Solving Thinking Under Uncertainty Intelligent Thinking Problem Solving Thinking Under Uncertainty Intelligent Thinking

4 Problem Solving Blocks to Problem Solving Solution Strategies

5 A Problem A situation in which there is a goal, but it is not clear how to reach the goal A well-defined problem is one with clear specifications of the start state (where you are), goal state (where you want to be) and the processes for reaching the goal state (how to get there) An ill-defined problem is a problem lacking clear specification of the start state, goal state, or the processes for reaching the goal state

6 Problem Solving Involves two steps... Interpreting the problem Trying to solve the problem

7 Blocks to Problem Solving Interpretation blocks Fixation is the inability to create a new interpretation of a problem For instance, in the 9-dot problem, the directions do not say one cannot go “outside” the mental square formed by the 9 dots

8 Blocks to Problem Solving Interpretation blocks Functional fixedness is the inability to see that an object can have a function other than its typical one For example, if you need a screwdriver but don’t have one, a dime could be used to serve the purpose of a screwdriver Limits our ability to solve problems that require using an object in a novel way To combat functional fixedness, you should systematically think about the possible novel uses of all the various objects in the problem environment

9 Blocks to Problem Solving Strategy blocks Our past experience with problem solving can lead us to mental set, the tendency to use previously successful solution strategies without considering others that are more appropriate for the current problem In the two-letter series problems, mental set likely hindered you because you viewed the letters in the series as single entities and looked for relationships between them, not each of the letters as part of some larger entity Sometimes when searching for new approaches to a problem, we may experience insight, a new way of interpreting a problem that immediately gives you the solution

10 The Matchstick Problem

11 Overcoming Blocks To combat the blocks in problems solving, ask yourself questions such as: Is my interpretations of the problem unnecessarily constraining possible solutions? Can I use any of the objects in the problem in novel ways to solve the problem? Do I need a new type of solution strategy?

12 Solution Strategies Algorithm Heuristic

13 Algorithm A step-by-step procedure that guarantees a correct answer to a problem For example, using multiplication correctly guarantees you the correct solution to a multiplication problem

14 Heuristic A solution strategy that seems reasonable given your past experiences with solving problems, especially similar problems May pay off with a quick correct answer, but it may lead to no answer or an incorrect one

15 Types of Heuristics The anchoring and adjustment heuristic uses an initial estimate as an anchor and then this anchor is adjusted up or down For instance, when meeting a new person, your first impression forms an anchor of that person, and you may not process subsequent information about that person as fully as it should be processed

16 Types of Heuristics The working backward heuristic is attempting to solve a problem by working from the goal state backward to the start state For instance, consider the following situation: Water lilies growing in a pond double in area every 24 hours. On the first day of spring, only one lily pad is on the surface of the pond. Sixty days later, the entire pond is covered. On what day is the pond half covered?” If you work backward with the fact the pond is completely covered on the 60th day, you can solve this question easily…half of the pond must be covered on the 59th day.

17 Types of Heuristics The means-ends analysis heuristic is breaking down the problem into subgoals and working toward decreasing the distance to the goal state by achieving these subgoals For example, when trying to write a major term paper, students should be encouraged (and perhaps shown) how to break down this big task into smaller tasks that, when completed, will result in a final, large term paper

18 The Tower of Hanoi Problem

19 Algorithms vs. Heuristics When going through a new grocery store looking for pickles, you could go up and down every aisle, examining each product until you found the pickles This would be using an algorithm Or, you could look at the signs above the aisles and look for the word “Condiments” and assume that pickles will be on that aisle This would be using a heuristic

20 Thinking Under Uncertainty Judging Probability Hypothesis Testing

21 Probability and Uncertainty The probability of an event is the likelihood that it will happen Probabilities range from 0 (never happen) to 1 (always happens) An event with 0.5 probability of occurring is maximally uncertain because it is equally likely to occur and not to occur In addition to judging the uncertainty of events in our environment, we attempt to reduce our uncertainty about the world by trying to find out how various events are related to each other

22 Judging Probability Two main heuristics we use to make judgments about probabilities... The Represen- tativeness Heuristic The Availability Heuristic

23 The Representativeness Heuristic A rule of thumb for judging the probability of membership in a category by how well an object resembles (i.e., is representative of) that category The more representative the object is, the more probable You hear about a person who likes to write, read, and interpret poetry. Is it more likely that this person is: A hockey fan? OR An English professor who likes hockey? We tend to use the representativeness heuristic because the mind categorizes information automatically

24 The Over-lapping Set Diagram for the Linda Problem

25 The Conjunction Fallacy The conjunction rule states that the likelihood of the overlap of two uncertain events cannot be greater than the likelihood of either of the two events because the overlap is only part of each event The conjunction fallacy, which can occur when we use the representativeness heuristic, is incorrectly judging the overlap of two uncertain events to be more likely than either of the two events

26 The Gambler’s Fallacy The erroneous belief that a chance process is self-correcting in that an event that has not occurred for a while is more likely to occur People believe that short sequences (e.g., a series of 9 coin tosses) should reflect the long-run probabilities If a coin lands heads 8 times in a row, people think there is a greater chance of it being tails on the 9th toss

27 The Availability Heuristic Is the rule of thumb that the more available an event is in our memory, the more probable it is For instance, we can think of more words beginning with the letter “r” than with “r” in the third position of a word because we organized words in our memories by how they begin, not by their third letters (actually, words with “r” in the third position are more frequent)

28 The Availability Heuristic An event may be prominent in our memories because it happened recently or because it is particularly striking or vivid For instance, deaths from shark attacks are highly publicized, creating greater fear of this mode of death than of diabetes, which is a far more likely cause of death

29 Overcoming Heuristics To overcome the representativeness and availability heuristics make sure you have not overlooked relevant probability information and plausible reasons for differential availability

30 Hypothesis Testing Confirmation Bias Illusory Correlation Belief Perseverance Person-Who Reasoning

31 Confirmation Bias The tendency to seek evidence that confirms one’s beliefs That is, people do not test their beliefs about the world by trying to disconfirm them, but rather, by trying to confirm them The four cards below have information on both sides. On one side of a card is a letter, and on the other side is a number. Consider this rule: If a card has a vowel on one side, then it has an even number on the other side. Select the card or cards that you definitely must turn over to determine whether the rule is true or false for these four cards.

32 Illusory Correlation The erroneous belief that two variables are related when they actually are not We tend to focus on instances in which there seems to be a relationship between the variables in question, ignoring all disconfirming instances If we believe a relationship exists between two things (e.g., wearing a certain color shirt and getting a good grade on a test), then we will tend to notice and remember instances that confirm this relationship

33 Belief Perseverance The tendency to cling to one’s beliefs in the face of contradictory evidence Personal-who reasoning is questioning a well- established finding because you know a person (one instance) who violates the established finding For example, a student may insist that eating a steak, baked potato loaded with butter, sour cream, cheese, and salt for dinner is healthy because his grandfather did so every night for 50 years and lived to be 90 years old

34 Intelligent Thinking Intelligence Tests Controversies about Intelligence

35 A Bit of History… First attempts to develop intelligence tests took place in late 19 th century England and in early 20 th century France Embedded in the nature-nurture controversy

36 Francis Galton Sir Francis Galton was trying to develop an intelligence test for the purpose of eugenics, selective reproduction to enhance the capacities of the human race. Believed in the genetic determination of intelligence and thought he could measure intelligence by measuring various aspects of the human brain and nervous system (a strong nature emphasis) Developed tests of sensory abilities and reaction time and tested thousands of people (found, however, that these were not good predictors of intelligence) Nevertheless, invented the basic mathematics behind correlational statistics

37 Binet & Simon In France in the early part of the 20th century, Binet and Simon were working on the problem of mental retardation when France switched to mass public education Developed a test to diagnose children who were subnormal Published in 1905, this test was the first accepted test of intelligence

38 Binet & Simon Based on the concept of mental age – the age typically associated with a child’s level of performance If a child’s mental age was less than their chronological/actual age, they would need remedial work Demonstrates a nurture emphasis on intelligence

39 Terman Lewis Terman at Stanford University used Binet and Simon’s test, after revising it for American school children In 1916, Terman’s revision became known as the Stanford- Binet, and Terman used the classic intelligence quotient formula by William Stern, a German psychologist IQ = (mental age/chronological age) X 100 Consequently, when a child’s mental age as assessed by the test was greater than the child’s chronological age, the child’s IQ was greater than 100 When a child’s mental age as assessed by the test was less than the child’s chronological age, the child’s IQ was less than 100 Note that the IQ formula itself is no longer used

40 Weschler David Wechsler was Chief Psychologist at Bellevue Hospital in New York City in the 1930s and was in charge of adult patients of diverse backgrounds The Stanford-Binet was not designed to assess adult intelligence, and the IQ was particularly problematic for adults because at some point the mental age levels off but the chronological age keeps increasing (so a person’s IQ declines simply because of natural aging) Developed his own tests, the Wechsler Bellevue Scale, in 1939 (later called the Wechsler Adult Intelligence Scale – WAIS) Provides test scores for a battery of both verbal tests (such as vocabulary and comprehension) and performance (non- verbal) tests (such as block design and picture arrangement)

41 Psychometric Properties Standardization Reliability Validity

42 Standardization A process that allows test scores to be interpreted by providing test norms The test must be given to a large representative sample of the relevant population, and the scores of this sample serve as norms for interpretation For example, Terman standardized his Stanford-Binet on American children of various ages – any child’s raw score could be compared to the standardization norms to calculate the child’s mental age Wechsler collected standardization data for various adult age groups, and the data for each age group form a normal distribution

43 Deviation IQ Scores To calculate a person’s deviation IQ, Wechsler compared how far the person’s raw score was from the mean raw score in terms of standard deviation units from the mean To make the deviation scores resemble the IQ formula, he set the mean to 100 and the standard deviation to 15 Deviation IQ score = 100 plus or minus (15x the number of standard deviation units a person’s raw test score is from the mean for the relevant age group norms)

44 Deviation IQ Scores on the WAIS

45 Reliability The extent to which the scores for a test are consistent In the test-retest method, the test is given twice to the same sample, and the correlation coefficient for the two sets of scores is computed A reliable test yields a strong positive correlation Alternate form reliability can be assessed if multiple forms of the test are available Here, a researcher gives different forms of the test to the same sample at different times and computes the correlation coefficient for performance on the two forms Split-half reliability is determined by correlating performance of two halves of one given test For example, the odd and even number items

46 Validity The extent to which a test measures what it is supposed to measure or predict what it is supposed to predict Content validity means that the test covers the content that it is supposed to cover Predictive validity means that the test predicts behavior that is related to what is being measured by the test It is important to note that if a test is valid, it will also be reliable However, a test can be reliable, but not valid (e.g., using wrist size to measure intelligence; wrist size is quite reliable, but does not contain validity given the interest in measuring intelligence)

47 Controversies About Intelligence General vs. Specific Nature vs. Nurture

48 Theories of Intelligence Charles Spearman argued that intelligence test performance is a function of two types of factors A g factor (general intelligence) Some s factor (specific intellectual abilities such as reasoning) Believed that the g factor was more important because people who did well on one subtest usually did well on most of the subtests, and people who did poorly on one subtest usually did poorly on most of the subtests

49 Theories of Intelligence L. L. Thurstone argued for the importance of several mental abilities – verbal comprehension, number facility, spatial relations, perceptual speed, word fluency, associative memory, and reasoning Identified these abilities via factor analysis, which is a statistical technique that identifies cluster of test item that measure the same ability (factor)

50 Theories of Intelligence Cattell and Horn proposed two types of intelligence, which have been of interest to researchers in aging Fluid intelligence refers to abstract reasoning, memory, and the speed of information processing Crystallized intelligence refers to accumulated knowledge and verbal and numerical skills

51 Theories of Intelligence Howard Gardner’s theory of multiple intelligences includes 8 independent types of intelligence LinguisticLanguage ability (e.g., reading, writing, speaking) Logical-MathematicalMathematical problem solving & scientific analysis SpatialReasoning about visual spatial relationships MusicalMusical skills (e.g., the ability to compose and understand music) Bodily-KinestheticSkill in body movement and handling objects IntrapersonalUnderstanding oneself InterpersonalUnderstand other people NaturalistAbility to discern patterns in nature

52 Theories of Intelligence Robert Sternberg’s triarchic theory of intelligence proposes three types of intelligence 1.Analytical intelligence is essentially what is measured by standard intelligence tests, the necessary skills for good academic performance 2.Practical intelligence could be equated with good common sense or “street smarts” 3.Creative intelligence is concerned with the ability to solve novel problems and deal with unusual situations

53 Nature vs. Nurture Most contemporary psychologists believe that both heredity (nature) and environmental experiences (nurture) are important in determining intelligence The disagreement is over the relative contribution of each part to intelligence

54 The Case for Nature Genetic similarity studies are important in determining the relative contribution of nature and nurture to intelligence Identical twins have 100% genetic similarity Fraternal twins and siblings have 50% similarity Two unrelated people have 0% similarity If intelligence were due to heredity, the average correlations between intelligence scores should decrease as genetic similarity decreases, and researchers have found this to be the case

55 The Case for Nurture However, there are also results that support environmental influences on intelligence For example, if identical twins are raised together, the correlation between their intelligence test scores is +0.86, but if the identical twins are raised apart, the correlation falls to +0.72

56 Both Nature and Nurture The average correlation between fraternal twins raised together (+0.60) is less than that for identical twins reared apart (+0.72), indicating the influence of heredity The average correlation is greater than that for ordinary siblings reared together (+0.47), indicating environmental influences because the environment influences of fraternal twins is more similar than for ordinary siblings at different ages

57 Both Nature and Nurture There is a modest correlation between the intelligence test scores of adopted children with their parents, and this correlation disappears as the children age The correlation between the scores for adopted children and their biological parents, however, increases as the children age This stronger relationship between a person’s intelligence and that of their biological parents means that nature plays a larger role in determining a person’s intelligence than environmental experiences

58 Heritability An index of the degree of variation of a trait within a given population that is due to heredity For intelligence, most research suggests 50% to 70% of the variation in intelligence test scores is estimated to be due to heredity Because it is not 100%, this means that heredity and environment interact to determine intelligence In essence, heredity determines a reaction range, genetically determined limits for an individual’s intelligence, but the quality of the person’s environmental experiences determine where the individual falls within this range

59 Caveats Heritability is a group statistic and not relevant to individual people Heritability has nothing to do with the differences that have been observed between populations, such as the difference in scores for Asian versus American schoolchildren

60 The Flynn Effect Refers to the fact that in the United States and other Western industrialized nations, average intelligence scores have improved steadily over the past century Proposed explanations involve many environmental factors such as better nutrition and more education


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