cognition – 2/e dr. daniel b. willingham chapter 10: decision making & deductive reasoning...

Cognition – 2/eCognition – 2/eDr. Daniel B. WillinghamDr. Daniel B. Willingham

Chapter 10:Chapter 10:Decision Making & Decision Making &

Deductive ReasoningDeductive ReasoningPowerPoint by Glenn E. Meyer, Trinity UniversityPowerPoint by Glenn E. Meyer, Trinity University

© 2004 Prentice Hall© 2004 Prentice Hall

©2004 Prentice Hall©2004 Prentice Hall 22

Do People Consistently Make Do People Consistently Make Optimal Decisions?Optimal Decisions?

• Decision Making:Decision Making:A situation in which a person is presented with A situation in which a person is presented with two or more explicit courses of action, with the two or more explicit courses of action, with the

requirement that he or she select just onerequirement that he or she select just one

• Normative or Rational ModelsNormative or Rational Models• Demonstrations of Human Demonstrations of Human

IrrationalityIrrationality


NormativeNormative or Rational Models or Rational Models• Rational DecisionsRational Decisions

May not be rational - In the context of decision making, rational choices are ones that are May not be rational - In the context of decision making, rational choices are ones that are internally consistent (e.g., that show transitivity). internally consistent (e.g., that show transitivity).

Transitivity - If a relationship holds between the first and second of three elements and it holds Transitivity - If a relationship holds between the first and second of three elements and it holds between the second and third, it should hold between the first and third. If choices were between the second and third, it should hold between the first and third. If choices were rational, there would be transitivity of preference between choices. However, transitivity does rational, there would be transitivity of preference between choices. However, transitivity does not always holdnot always hold

• Normative Theories: Normative Theories: A theory of choice that describes a set of rules by which some choices are better than others and one A theory of choice that describes a set of rules by which some choices are better than others and one choice can be said to be optimal. Optimal value depends on the specific theorychoice can be said to be optimal. Optimal value depends on the specific theory Expected Value Theory: Expected Value Theory:

A normative theory of choice in which the best choice is the one that offers that largest financial A normative theory of choice in which the best choice is the one that offers that largest financial payoff. Expected values for various Casino games are seen in Table 10.1payoff. Expected values for various Casino games are seen in Table 10.1

o Example: Suppose you had a choice ofExample: Suppose you had a choice of1.1. 0.5 chance of winning $500.5 chance of winning $50 Expected Value = .5 x $50 = $25Expected Value = .5 x $50 = $252.2. 0.25 chance of winning $110 0.25 chance of winning $110 Expected Value = .25 x $110 = $27.5Expected Value = .25 x $110 = $27.5

Expected Value Theory says you pick the second choiceExpected Value Theory says you pick the second choice Expected Utility:Expected Utility:

A normative theory of choice in which the best choice is the one that offers the reward with the A normative theory of choice in which the best choice is the one that offers the reward with the greatest personal value to the individual, not necessarily the greatest financial reward. The greatest personal value to the individual, not necessarily the greatest financial reward. The theory allows that in some situations, it may be more valuable to an individual to be very likely theory allows that in some situations, it may be more valuable to an individual to be very likely to get a modest reward rather than to have a small probability to get a large rewardto get a modest reward rather than to have a small probability to get a large reward. . For For example: would you spend a dollar for the chance to win a dollar with a high probability or a example: would you spend a dollar for the chance to win a dollar with a high probability or a low probability of winning several million dollars.low probability of winning several million dollars.


DemonstrationsDemonstrations of Human Irrationality of Human Irrationality• Two principles are shown if people act rationally:Two principles are shown if people act rationally:

Description invarianceDescription invariancePeople will consistently make the same choice irrespective of how the problem is described to People will consistently make the same choice irrespective of how the problem is described to them as long as the basic structure of the choices is the same them as long as the basic structure of the choices is the same

Procedure invariance Procedure invariance A requirement of rational decision making, it is the idea that people will consistently make the A requirement of rational decision making, it is the idea that people will consistently make the same choice irrespective of the how their preference for that choice is measured. In fact, same choice irrespective of the how their preference for that choice is measured. In fact, procedure invariance is violatedprocedure invariance is violated

• Tversky and Kahneman (1986) show consistent violations of these principles due to Tversky and Kahneman (1986) show consistent violations of these principles due to differences in the differences in the problem frameproblem frame (way the problem is described). (way the problem is described).

Framing Effects:Framing Effects: People are averse to take risks if the outcome is described positively but more willing to take People are averse to take risks if the outcome is described positively but more willing to take

risks if the outcome is described negativelyrisks if the outcome is described negatively Psychic framing:Psychic framing:

How we mentally categorize money we have spent or are considering spending. Another aspect How we mentally categorize money we have spent or are considering spending. Another aspect of framing of framing

o Cost or gain of some part of an item is considered relative to the cost of the entire itemCost or gain of some part of an item is considered relative to the cost of the entire itemo Sunk Costs: An investment (e.g., of money, time, emotion) that is irretrievably spent and should not Sunk Costs: An investment (e.g., of money, time, emotion) that is irretrievably spent and should not

affect current decisions about spending but nevertheless often does affect current decisions about spending but nevertheless often does o Loss Aversion: The unpleasantness of a loss is larger than the pleasantness of a similar-sized gain Loss Aversion: The unpleasantness of a loss is larger than the pleasantness of a similar-sized gain

Choice changes depending on how choice is elicited (Tversky, Slovic and Kahneman, 1990)Choice changes depending on how choice is elicited (Tversky, Slovic and Kahneman, 1990) Satisficing (Simon, 1957);Satisficing (Simon, 1957);

To select the first choice that is satisfactory (i.e., above some threshold) rather than evaluating To select the first choice that is satisfactory (i.e., above some threshold) rather than evaluating every choice and selecting the best of those. Psychologists believe that people must satisfice every choice and selecting the best of those. Psychologists believe that people must satisfice most of the time because there are usually too many choices to allow evaluation of all of them most of the time because there are usually too many choices to allow evaluation of all of them


What Shortcuts Do People Use to What Shortcuts Do People Use to Make Decisions?Make Decisions?

• Heuristics Vs. Algorithms – an important distinctionHeuristics Vs. Algorithms – an important distinction• Algorithm: A formula that can be applied to choice situations. It has Algorithm: A formula that can be applied to choice situations. It has

the advantage of producing consistent outcomes, but algorithms may the advantage of producing consistent outcomes, but algorithms may be complex and difficult to compute. For example: Expected Value is be complex and difficult to compute. For example: Expected Value is an algorithman algorithm

• Heuristics: Simple cognitive rules that are easy to apply and that Heuristics: Simple cognitive rules that are easy to apply and that usually yield acceptable decisions but can lead to errors. usually yield acceptable decisions but can lead to errors.

• Decision HeuristicsDecision Heuristics• RepresentativenessRepresentativeness• AvailabilityAvailability• Anchoring and AdjustmentAnchoring and Adjustment• Information We IgnoreInformation We Ignore• Probabilities versus FrequenciesProbabilities versus Frequencies• Social FactorsSocial Factors


RepresentativenessRepresentativeness• Representativeness: Representativeness:

A heuristic that leads you to judge the probability of an event as A heuristic that leads you to judge the probability of an event as more likely to belong to a category if it has the features of the more likely to belong to a category if it has the features of the category that you deem importantcategory that you deem important Example from Tversky and Kahneman (1973)Example from Tversky and Kahneman (1973)

““Linda is 31 years old, single outspoken and very bright. She majored in Linda is 31 years old, single outspoken and very bright. She majored in philosophy. As a student she was deeply concerned with the issues of philosophy. As a student she was deeply concerned with the issues of discrimination and social justice, and also participated in anti-nuclear discrimination and social justice, and also participated in anti-nuclear demonstrations.” demonstrations.”

Which is more likely?Which is more likely?

A. Linda is a bank tellerA. Linda is a bank teller

B. Linda is bank teller and active as a feministB. Linda is bank teller and active as a feminist

Most people choose “B” based on stereotypical impressions from the descriptionMost people choose “B” based on stereotypical impressions from the description


AvailabilityAvailability• Availability: Availability:

A heuristic in which the likelihood of an event is A heuristic in which the likelihood of an event is evaluated by the ease with which examples of the event evaluated by the ease with which examples of the event can be called to mindcan be called to mind Example:Example:

Are there more words in English that start with the letter “r” Are there more words in English that start with the letter “r” or have “r” as the third letter. The latter is true but 69% chose or have “r” as the third letter. The latter is true but 69% chose the first letter. That is because it is difficult to recall words the first letter. That is because it is difficult to recall words based on their middle letter (Tversky and Kahneman, 1973).based on their middle letter (Tversky and Kahneman, 1973).

Illusory Correlation: People have a bias to judge that two Illusory Correlation: People have a bias to judge that two events or characteristics of an event go together if people had a events or characteristics of an event go together if people had a prior belief that they go together or if they are natural prior belief that they go together or if they are natural associates. Illusory correlation is related to the availability associates. Illusory correlation is related to the availability heuristic because you judge that two things are correlated if heuristic because you judge that two things are correlated if you can think of many instances in which the two things co-you can think of many instances in which the two things co-occurred occurred


Anchoring and AdjustmentAnchoring and Adjustment• Anchoring and adjustment:Anchoring and adjustment:

Heuristic used to estimate probabilities in which the person starts with some Heuristic used to estimate probabilities in which the person starts with some initial probability value (anchor) by doing a partial calculation of the problem or initial probability value (anchor) by doing a partial calculation of the problem or by using a probability statement in the problem and then adjusting that initial by using a probability statement in the problem and then adjusting that initial estimate upward or downward based on other information in the problemestimate upward or downward based on other information in the problem Example: Estimate the answer to these problems (subjects saw only one) Example: Estimate the answer to these problems (subjects saw only one) (Tversky and Kahneman)(Tversky and Kahneman) 1 x 2 x 3 x 4 x 5 x 6 x 7 x 8 = ?1 x 2 x 3 x 4 x 5 x 6 x 7 x 8 = ? 8 x 7 x 6 x 5 x 4 x 3 x 2 x 1 =? 8 x 7 x 6 x 5 x 4 x 3 x 2 x 1 =? ■■ The answer to both is 40, 320 The answer to both is 40, 320 Folks seeing the first string guessed a median answer of 512Folks seeing the first string guessed a median answer of 512 The second string elicited a median guess of 2,250The second string elicited a median guess of 2,250

• Anchoring and Adjustment heuristic has been found to influence:Anchoring and Adjustment heuristic has been found to influence: Preference judgmentsPreference judgments Judgments of answers to factual questionsJudgments of answers to factual questions Estimates of probabilities of events such as nuclear warEstimates of probabilities of events such as nuclear war Estimates of preferences for one’s spouseEstimates of preferences for one’s spouse Legal decisions such as awards in lawsuits Legal decisions such as awards in lawsuits


Information We IgnoreInformation We Ignore• Ignoring Sample SizeIgnoring Sample Size

Definition: number of things in a group that you are Definition: number of things in a group that you are evaluating. Larger samples are better.evaluating. Larger samples are better.

Sample size is crucial in determining probabilities of events, Sample size is crucial in determining probabilities of events, however people may tend to use the representativeness however people may tend to use the representativeness heuristic moreheuristic more

• Ignoring the Base RateIgnoring the Base Rate Definition: The frequency of an event in the general Definition: The frequency of an event in the general

population. population. When judging the likelihood that an event occurred, people When judging the likelihood that an event occurred, people

tend to ignore the base rate if they are given any other tend to ignore the base rate if they are given any other information about the eventinformation about the event

Example: Medical testing for breast cancer as seen in Table Example: Medical testing for breast cancer as seen in Table 10.2 (Eddy, 1982)10.2 (Eddy, 1982)


Probabilities versus FrequenciesProbabilities versus Frequencies• Gigerenzer and Hoffrage (1995) claim that previous work has a Gigerenzer and Hoffrage (1995) claim that previous work has a

flaw. The human mind is built to keep track of frequencies and flaw. The human mind is built to keep track of frequencies and not probabilities – based on evolutionary needs and constraintsnot probabilities – based on evolutionary needs and constraints Subjects could be presented with problems in a probability vs. Subjects could be presented with problems in a probability vs.

frequency format. The latter led to more correct solutions as seen frequency format. The latter led to more correct solutions as seen in Fig. 10.2in Fig. 10.2

Base rate neglect is more likely with probability information as Base rate neglect is more likely with probability information as our minds evolved in preliterate societies where information our minds evolved in preliterate societies where information would be remembered in terms of frequencies.would be remembered in terms of frequencies.

Other researchers argue against this view and find other factors Other researchers argue against this view and find other factors to explain the resultsto explain the results

Conclusion is that presentation format is important but reasons Conclusion is that presentation format is important but reasons for this are not clearfor this are not clear


Social FactorsSocial Factors

• Researchers may have ignored social factors in Researchers may have ignored social factors in decision making. Decisions may be based on:decision making. Decisions may be based on: Social contractsSocial contracts Opportunities to cheatOpportunities to cheat Implications for future choiceImplications for future choice Sacred Values and PrinciplesSacred Values and Principles

• Tetlock (1991, 1992, 2002) – pitting a secular value Tetlock (1991, 1992, 2002) – pitting a secular value (like assigning a monetary value) vs. a sacred (like assigning a monetary value) vs. a sacred value (saving a life) is taboo. Anger is directed value (saving a life) is taboo. Anger is directed towards those making the taboo choicetowards those making the taboo choice


Decision Making and EmotionDecision Making and Emotion

• Damasio and Tranel:Damasio and Tranel: Higher stimuli cause the ventromedial prefrontal cortex Higher stimuli cause the ventromedial prefrontal cortex

to activate somatic responses, including emotional to activate somatic responses, including emotional responses from the autonomic nervous systemresponses from the autonomic nervous system

These emotional reactions along with logical, cognitive These emotional reactions along with logical, cognitive processes limit choices of actionprocesses limit choices of action

As seen in Fig. B10.1, subjects with ventromedial As seen in Fig. B10.1, subjects with ventromedial

damage make poor decisions as they have lost the damage make poor decisions as they have lost the

ability to make associations between complex stimuli ability to make associations between complex stimuli

and their consequences.and their consequences.


Do People Reason Logically?Do People Reason Logically?

• Formal LogicFormal Logic• Human Success and Failure in Human Success and Failure in

Reasoning: Conditional StatementsReasoning: Conditional Statements• Human Success and Failure in Human Success and Failure in

Reasoning: SyllogismsReasoning: Syllogisms• General Models of ReasoningGeneral Models of Reasoning


Formal LogicFormal Logic• Do people use formal logic?Do people use formal logic?

• Important Terms:Important Terms: Deductive Reasoning: Problems to which one can apply formal logic and derive an Deductive Reasoning: Problems to which one can apply formal logic and derive an

objectively correct solution objectively correct solution

o Premise: statement of fact taken to be true for the purposes of a logical problem Premise: statement of fact taken to be true for the purposes of a logical problem

o Conclusion: A statement of fact derived by logical processes. One may confidently propose that a Conclusion: A statement of fact derived by logical processes. One may confidently propose that a

conclusion is true or false within a problem based on its logical relation to the premises. Whether conclusion is true or false within a problem based on its logical relation to the premises. Whether

the conclusion is true in the real world depends on the truth or falseness of the premises the conclusion is true in the real world depends on the truth or falseness of the premises

o Studied in terms two formats:Studied in terms two formats: Conditional Statements; A logical form composed of three statements. First premise states, “If Conditional Statements; A logical form composed of three statements. First premise states, “If

condition p is met, then q follows.” Second premise states whether p or q is true. Third is a condition p is met, then q follows.” Second premise states whether p or q is true. Third is a

conclusion about p or q as seen in Fig. 10.3conclusion about p or q as seen in Fig. 10.3

Syllogisms: Syllogism Syllogisms: Syllogism

Logical form composed of three statements of fact: two premises & conclusionLogical form composed of three statements of fact: two premises & conclusion

Inductive Reasoning: Reasoning that allows one to say that a conclusion is more or less Inductive Reasoning: Reasoning that allows one to say that a conclusion is more or less likely to be true but does not allow one to say that a conclusion must be true likely to be true but does not allow one to say that a conclusion must be true


Formal Logic - ContinuedFormal Logic - Continued• Brain Structures and Inductive vs. Deductive Brain Structures and Inductive vs. Deductive

ReasoningReasoning Goel, et al. (1997) suggest deductive reasoning associated Goel, et al. (1997) suggest deductive reasoning associated

with activation in left interior frontal gyrus and inductive with activation in left interior frontal gyrus and inductive reasoning with broader areas of left frontal lobe and much reasoning with broader areas of left frontal lobe and much greater activity in the superior frontal gyrus as seen in Fig. greater activity in the superior frontal gyrus as seen in Fig. 10.210.2

Osherson, et al. (1998) disagree and found deductive and Osherson, et al. (1998) disagree and found deductive and inductive reasoning associated with supplementary motor inductive reasoning associated with supplementary motor area, bilateral cerebellum, right caudate and left thalamus. area, bilateral cerebellum, right caudate and left thalamus. Probability task alone with cingulate gyrus and right Probability task alone with cingulate gyrus and right midfrontal gyrus. Deductive task with second visual cortexmidfrontal gyrus. Deductive task with second visual cortex

More research is need to clarify the discrepancies in these More research is need to clarify the discrepancies in these two sets of studies.two sets of studies.


Human Success and Failure in Human Success and Failure in Reasoning: Conditional StatementsReasoning: Conditional Statements

• Philosophers (Aristotle) and psychologists (e.g. Piaget) Philosophers (Aristotle) and psychologists (e.g. Piaget) have assumed that humans are rational and will make have assumed that humans are rational and will make correct deductions. However, people may not reason well.correct deductions. However, people may not reason well. Wason Card problem (Wason, 1968, 1969)Wason Card problem (Wason, 1968, 1969)

The figure shows four cards. Each card has a letter on one side and a digit on the other side. You are to verify whether the following rule is true: If there is a vowel on one side, there is an even number on the other side. You must verify this rule by turning over the minimum number of cards

Solution: You should turn over the “A” and the “3”. Only 15% of college students get it right. They miss turning over the three.


Human Success and Failure in Reasoning - Human Success and Failure in Reasoning - ContinuedContinued

Concreteness or Familiarity – As shown by Griggs and Concreteness or Familiarity – As shown by Griggs and Cox (1982) – more familiar and/or versions of the Cox (1982) – more familiar and/or versions of the Wason problem are more easily solved (72% correct)Wason problem are more easily solved (72% correct)

The cards in front of you have information about four people sitting at a table. On one side of a card is a person’s age and on the other side of the card is what the person is drinking. Here is a rule: If a person is drinking beer, then the person must be over 19 years of age. Select the cards or cards that you definitely need to turn over to determine whether they are violating the rule.

The effect might be due to Case The effect might be due to Case Based Reasoning:Based Reasoning:

A theory that we reason about A theory that we reason about problems by remembering problems by remembering similar problems and how they similar problems and how they were solved were solved



• Pragmatic Reasoning Schemas (Cheng and Holyoak, 1985):Pragmatic Reasoning Schemas (Cheng and Holyoak, 1985):Sets of rules defined in relation to goals that can be used to evaluate situations such Sets of rules defined in relation to goals that can be used to evaluate situations such as permissions or obligations. A key aspect of pragmatic reasoning schemas is that as permissions or obligations. A key aspect of pragmatic reasoning schemas is that they encourage conclusions that are practical in the real world, as opposed to formal they encourage conclusions that are practical in the real world, as opposed to formal logic, which can lead to conclusions that are technically correct but not usefullogic, which can lead to conclusions that are technically correct but not useful Lead to inferences that are practical in solving problems. Logical rules may lead Lead to inferences that are practical in solving problems. Logical rules may lead

valid inferences that are not much helpvalid inferences that are not much help Schemas exist for:Schemas exist for:

o PermissionsPermissionso Obligations Obligations o CausationsCausations

Prior knowledge activates the appropriate schema to be applied to a problemPrior knowledge activates the appropriate schema to be applied to a problem Abstract and unfamiliar problems couched in terms of one of these schema are Abstract and unfamiliar problems couched in terms of one of these schema are

solved more easily.solved more easily.



• Evolutionary Perspective –as before :Evolutionary Perspective –as before : Humans evolved as social animalsHumans evolved as social animals Social networks require us to help or punish other community membersSocial networks require us to help or punish other community members Rules based on this principle are easier to understandRules based on this principle are easier to understand Example – determining who is a cheater but depends on observer’s social Example – determining who is a cheater but depends on observer’s social

perspective as seen in Fig. 10.7perspective as seen in Fig. 10.7 Cheng and Holyoak (1989) point out subjects solve precaution and Cheng and Holyoak (1989) point out subjects solve precaution and

permission rules well and this is not part of the social exchange structurepermission rules well and this is not part of the social exchange structure Evolutionary psychologists propose two modules to handle this:Evolutionary psychologists propose two modules to handle this:

o Catching CheatersCatching Cheaterso Dealing with precautionsDealing with precautions

Critics regard this as post-hoc and therefore suspectCritics regard this as post-hoc and therefore suspect


Human Success and Failure in Human Success and Failure in Reasoning: SyllogismsReasoning: Syllogisms

• Syllogism: A logical form composed of three statements of fact: two Syllogism: A logical form composed of three statements of fact: two premises and a conclusion premises and a conclusion

• Performance is usually bad on these sorts of reasoning tasks due to Performance is usually bad on these sorts of reasoning tasks due to several factors:several factors: Conversion Errors: An error in dealing with a syllogism in which a person Conversion Errors: An error in dealing with a syllogism in which a person

reverses one of the premises. For example the premise reads “All As are reverses one of the premises. For example the premise reads “All As are Bs” and the participant believes that it is also true that “All Bs are As.”Bs” and the participant believes that it is also true that “All Bs are As.”

Conversational implicature: The tendency for people to treat the language Conversational implicature: The tendency for people to treat the language of logic as though it has the same meaning as everyday languageof logic as though it has the same meaning as everyday language

Atmosphere : A situation in which two premises of a syllogism are both Atmosphere : A situation in which two premises of a syllogism are both either positive or negative or use the same quantifier. People are biased to either positive or negative or use the same quantifier. People are biased to accept as valid a conclusion that maintains the atmosphere accept as valid a conclusion that maintains the atmosphere

Prior Bias: Real-world knowledge that can influence people’s evaluation of Prior Bias: Real-world knowledge that can influence people’s evaluation of a syllogism. They are more likely to accept as true a syllogism with a a syllogism. They are more likely to accept as true a syllogism with a conclusion that they know is true and to reject a syllogism with a conclusion that they know is true and to reject a syllogism with a conclusion that they know is falseconclusion that they know is false

No one error or factor is known to be the conclusive factor in most cases of No one error or factor is known to be the conclusive factor in most cases of error. error.


General Models of ReasoningGeneral Models of Reasoning• There are three families of deductive reasoning models:There are three families of deductive reasoning models:

Syntactic: Models proposing that humans reason by accepting premises Syntactic: Models proposing that humans reason by accepting premises and then applying a set of processes that manipulate the premises in an and then applying a set of processes that manipulate the premises in an effort to evaluate a given conclusion or derive a conclusioneffort to evaluate a given conclusion or derive a conclusion

o Braine’s (1990) Natural Logic Theory: proposes a set of simple Braine’s (1990) Natural Logic Theory: proposes a set of simple inference schema called primary skills used in a universal reasoning inference schema called primary skills used in a universal reasoning program with two steps:program with two steps:

British Museum Algorithm: a reasoning scheme based on the play on British Museum Algorithm: a reasoning scheme based on the play on that idea that given an infinite amount of time and a typewriter, a that idea that given an infinite amount of time and a typewriter, a chimp could produce all the books in the British Museum. The chimp could produce all the books in the British Museum. The algorithm is similarly extensive and time consuming. It is a direct stepalgorithm is similarly extensive and time consuming. It is a direct step

Introduction of Suppositions: Something that one supposes to be true Introduction of Suppositions: Something that one supposes to be true to evaluate the consequences of its being true. Suppositions are to evaluate the consequences of its being true. Suppositions are important in some theories of deductive reasoning.important in some theories of deductive reasoning.

The more inference schemas used, the more errors occurThe more inference schemas used, the more errors occur


General Models of Reasoning - ContinuedGeneral Models of Reasoning - Continued Semantic: Models based on the idea that a conclusion is Semantic: Models based on the idea that a conclusion is

true if it can be shown to be true under all conditions in true if it can be shown to be true under all conditions in

which the premises are truewhich the premises are trueo Johnson-Laird’s (1999) Mental Models Theory: Assumes meaning of Johnson-Laird’s (1999) Mental Models Theory: Assumes meaning of

a problem is crucial to its solution. Premises are used to construct a a problem is crucial to its solution. Premises are used to construct a

mental model of a possible situation in the world as seen in Fig. 10.8mental model of a possible situation in the world as seen in Fig. 10.8 Mental Models can be combined as seen in Fig. 10.9 Mental Models can be combined as seen in Fig. 10.9

Success in reasoning would depend on capacity of working memory Success in reasoning would depend on capacity of working memory

(Evans, et al., 1999)(Evans, et al., 1999)

Many errors arise from the principle of truth: Proposal in Johnson- Many errors arise from the principle of truth: Proposal in Johnson-

Laird’s model of deductive reasoning that people tend to construct Laird’s model of deductive reasoning that people tend to construct

models representing only what is true, not what is false models representing only what is true, not what is false


General Models of Reasoning - General Models of Reasoning - ContinuedContinued

Probability: An approach to studying reasoning, Probability: An approach to studying reasoning, based on the idea that when presented with what based on the idea that when presented with what experimenters think of as reasoning problems, experimenters think of as reasoning problems, participants actually treat them as probability participants actually treat them as probability problemsproblems

o Oaksford and Charter’s Information Gain ModelOaksford and Charter’s Information Gain Model People use probabilities to assess the likelihood that they will People use probabilities to assess the likelihood that they will

find useful information as in the Wason card problem in Fig. find useful information as in the Wason card problem in Fig. 10.11. They don’t assume the potential relations of P and Q 10.11. They don’t assume the potential relations of P and Q are equally probable in the worldare equally probable in the world

People seek out information they think is maximally People seek out information they think is maximally informative as compared to following formal logic rulesinformative as compared to following formal logic rules


Mental Models, Spatial Reasoning and Mental Models, Spatial Reasoning and Brain ImagingBrain Imaging

• Goel, et al. (1998) had participants evaluate three Goel, et al. (1998) had participants evaluate three kinds of stimuli – syllogisms, spatial relational and kinds of stimuli – syllogisms, spatial relational and nonspatial relationalnonspatial relational

• Consider overlap shown in activation with each Consider overlap shown in activation with each condition. condition.

• Most active areas: left inferior frontal gyrus, left Most active areas: left inferior frontal gyrus, left middle frontal gyrus, left cingulate gyrus as seen middle frontal gyrus, left cingulate gyrus as seen in Fig. B10.3in Fig. B10.3

• Predominance of left hemisphere indicates that Predominance of left hemisphere indicates that reasoning seems largely language based, even with reasoning seems largely language based, even with inherently spatial problems. However, more work inherently spatial problems. However, more work is needed.is needed.

cognition – 2/e dr. daniel b. willingham chapter 10: decision making & deductive reasoning...

Documents