Psy i ch.7

Copyright © Allyn & Bacon 2006

Cognition and Language

Chapter Seven

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Slide author:

Cynthia K. Shinabarger Reed

Book authors:

Samuel Wood

Ellen G. Wood

Denise Boyd


Chapter Seven Overview

Imagery, Concepts, and Reasoning Imagery Concepts Reasoning

Decision Making The Additive and Elimination by Aspects

Strategies Heuristics Framing



Problem Solving Approaches to Problem Solving Impediments to Problem Solving

High-Tech Applications of Cognition Artificial Intelligence Artificial Neural Networks Robotics



Language The Structure of Language Language and the Brain Animal Language Language and Thinking Bilingualism


Imagery, Concepts, and Reasoning

• Cognition refers collectively to the mental processes involved in acquiring, storing, retrieving, and using information and includes sensation, perception, memory, imagery, concept formation, reasoning, decision making, problem solving, and language.


Imagery, Concepts, and ReasoningImagery• Imagery: the representation in the mind of a

sensory experience – visual, auditory, gustatory, motor, olfactory, or tactile.

• Stephen Kosslyn believes we mentally construct the objects we image, one part at a time, somewhat like the digital camera.

• First, stored memories of how parts of an object look are retrieved, and then mental processes are used to arrange or assemble those parts into the proper whole.



Imagery (continued)• Both the left and right hemispheres participate

in the processes of forming visual images.• Kosslyn discovered that the processes of

imaging objects and perceiving their counterparts in the real world are strongly related.

• Not only can we form a mental image of an object, but we can manipulate and move it around mentally, much as we would if we were actually holding and looking at the object.



Imagery (continued)– Shepard & Metzler

• Asked eight research participants to judge some 1,600 pairs of drawings

• Participants had to rotate the objects mentally to see if they matched

• The more the objects had to be rotated mentally, the longer it took participants to decide whether they matched



Imagery (continued)

How we use imagery

• Segal and Fusella asked student participants to form either a visual image of a tree or an auditory image of the sound of a typewriter.

• The researchers then made a faint sound on a harmonica or flashed a small, dimly lighted blue arrow, or did nothing at all.



Imagery (continued)

How we use imagery (continued)• Participants holding the visual image of a tree

were more likely to miss seeing the blue arrow, but more likely to hear the harmonica.

• Participants imaging the sound of a typewriter had the opposite experience.

• The interference happens because the brain is trying to use the same processes simultaneously on two different tasks.



Imagery (continued)How we use imagery (continued)• Professionals in many fields use imaging

effectively.• Sports psychologists have found that athletes

skilled in visualization can actually improve their performance by practicing mentally.

• The link between visualization and performance is assumed to be based on the close correspondence between brain activation during imagery and that which occurs when an individual actually engages in the imagined task.



Imagery (continued)Imagery and the Brain• Engaging in imaging based on verbal

descriptions alone activated regions of the brain known to be involved in higher-level visual processing.

• Brain-imaging studies show that, in general, the same brain areas are activated whether a person is performing a given task or mentally rehearsing the task using imagery.



Imagery (continued)Imagery and the Brain• Brain-imaging studies indicate that the same

regions in the motor cortex and related areas that are involved in the physical movements required for rotation of objects are also very active during mental imaging, although the cerebellum is more active during actual performance than during visualization.



Concepts• Concept: a mental category used to

represent a class or group of objects, people, organizations, events, situations, or relations that share common characteristics or attributes.

• Formal concept: a concept that is clearly defined by a set of rules, a formal definition, or a classification system.



Concepts (continued)• Natural concept: a concept acquired not

from a definition, but through everyday perceptions and experiences.

• We acquire many natural concepts through experiences with examples or positive instances of the concept.



Concepts (continued) • Prototype: a category member that embodies

the most common and typical features of a concept.

• Exemplars: the individual instances, or examples of a concept that are stored in memory from personal experience.

• To decide whether an unfamiliar item belongs to a concept, we compare it with exemplars (other examples) of that concept.



Concepts (continued)

• Lynch and others asked participants who were experts on trees and those who knew little about trees to rate 48 trees according to how well the trees represented the concept of tree.

• For the novices, familiarity determined the ratings of trees as good examples of the concept.




• The tree experts, in contrast, often selected the “ideal” tree, the best of the best, as the best example.

• Goodness-of-example ratings depended more on knowledge and experience of the rater than on the attributes or qualities of the selections being rated.




• Linda Smith provided children with replicas of everyday objects along with three-dimensional representations of those objects that were made up entirely of geometric shapes.

• She wanted to know whether the children would play with the geometric shapes in the same way as the replicas.




• Smith also tested the young participants to find out how many of 200 everyday objects each could identify by name.

• She found that children who knew the most object names were the most likely to play with replicas and geometric representations in the same way.



Reasoning• Reasoning is a form of thinking in which

conclusions are drawn from a set of facts.• Deductive reasoning: reasoning from the

general to the specific, or drawing particular conclusions from general principles.

• Syllogism: a scheme for logical reasoning in which two statements known as premises (the major premise and the minor premise) are followed by a valid conclusion.



Reasoning (continued)• Inductive reasoning is a form of reasoning in

which general conclusions are drawn from particular facts or individual cases.

• This kind of reasoning results in conclusions that might be true.

• Premises can be judged to be false on the basis of conclusions, but they cannot be judged to be true.



Reasoning (continued)

Individual Differences in Reasoning Ability• Many people, especially those who don’t listen

carefully to instructions or follow them well, have difficulty with formal reasoning problems.

• Research suggests that people can improve their reasoning skills when exposed to step-by-step instruction and practice in formal reasoning.



Deduction, Induction, and the Scientific Method

• Both inductive and deductive reasoning are used in the scientific method.

• Inductive reasoning is used to formulate a hypothesis based on observations.

• Deductive reasoning is used in the design of a study.



Deduction, Induction, and the Scientific Method (continued)

• Once formulated, the hypothesis becomes a major premise, and the method used to test it, a minor premise.

• The outcome of the study is the conclusion.

• Because the major premise is arrived at through inductive reasoning, the logic of scientific research is often referred to as hypothetico-deductive rather than truly deductive.


Decision Making

Additive and Elimination-by-Aspects Strategies

• Decision making is the process of considering alternatives and choosing among them.

• Additive strategy: a decision-making approach in which each alternative is rated on each of the important factors affecting the decision and the alternative with the highest overall rating is chosen.


Decision MakingAdditive and Elimination-by-Aspects Strategies

(continued)

• Elimination by aspects: a variation of the additive strategy; a decision-making approach in which the factors on which the alternatives are to be evaluated are ordered from most important to least important.

• Any alternative that does not satisfy the most important factor is automatically eliminated.

• The process of elimination continues as each factor is considered in order.

• The alternative that survives is the one chosen.


Decision Making

Heuristics• Heuristics: rules of thumb that are derived

from experience and used in decision making and problem solving, even though there is no guarantee of their accuracy or usefulness.

• Availability heuristic: a cognitive rule of thumb that says that the probability of an event or the importance assigned to it is based on its availability in memory.

• Any information affecting a decision, whether it is accurate or not, is more likely to be considered if it is readily available.


Decision Making

Heuristics (continued)• Representativeness heuristic: A thinking

strategy based on how closely a new object or situation is judged to resemble or match an existing prototype of that object or situation.

• This heuristic can lead to good decisions if the new object or situation truly matches the appropriate prototype.

• An example of the use of the representativeness heuristic occurs when people judge others based on stereotypes.


Decision MakingFraming• Framing: the way information is presented so

as to emphasize either a potential gain or a potential loss as the outcome of a decision based on that information.

• There are numerous practical applications of framing to decision making.

• For example, customers are more readily motivated to buy products if they are on sale than if they are simply priced lower than similar products to begin with.


Problem Solving

Approaches to Problem Solving

• Problem solving: using the thoughts and actions required to achieve a desired goal that is not readily attainable.

• Trial and error: an approach to problem solving in which one solution after another is tried in no particular order until an answer is found.

• When you possess relevant background knowledge, using the knowledge to find a solution to a problem is more efficient than using trial and error.


Problem Solving

Approaches to Problem Solving (continued)• Algorithm: a systematic, step-by-step

procedure that guarantees a solution to a problem of a certain type if the algorithm is executed properly.

• Scientific and mathematical formulas are algorithms.

• Often, computers are programmed to solve problems using algorithms.


Problem Solving

Approaches to Problem Solving (continued)

• Heuristics are used in problem solving in much the same way as in decision making.

• Working backwards: A heuristic strategy in which a person discovers the steps needed to solve a problem by starting with the solution and working back through the problem.


Problem Solving

Approaches to Problem Solving continued

Heuristics (continued)• Means-end analysis: a heuristic strategy in

which the current position is compared with a desired goal, and a series of steps are formulated and taken to close the gap between them.

• Analogy heuristic: a heuristic strategy that applies a solution used for a past problem to a current problem that shares many similar features.


Problem Solving

Impediments to Problem Solving• Functional fixedness: the failure to use

familiar objects in novel ways to solve problems because of a tendency to view objects only in terms of their customary functions.

• Mental set: the tendency to apply a familiar strategy to solve a problem even though another approach might be better.


High-Tech Applicationsof Cognition

Artificial Intelligence• Artificial intelligence: refers to the

programming of computer systems to simulate human thinking in solving problems and in making judgments and decisions.

• Expert systems: computer programs designed to carry out highly specific functions within a limited domain.

• Outside its area of expertise, an expert system cannot function.


High-Tech Applications of Cognition

Artificial Neural Networks• Artificial neural networks (ANNs) are

computer systems that are intended to mimic the human brain.

• Comprehension of natural human language is by far the biggest challenge for ANN designers.

• The point of research with ANNs is not just to use a computer to bring about a particular result, but to be able to program the computer to produce the result in the same way that the human mind does.



Robotics

• Robotics: the science of automating human and animal functions.

• Some impressive achievements in robotics include the following:

– Robots help stroke patients toward recovery by assisting them in exercise movement.

– Robotic surgical assistants help surgeons make remarkable gains in precision for some difficult surgeries.



Robotics (continued)

• Impressive achievements in robotics continued:

– Robotic filling stations will keep satellites aloft.

– Miniature robots will assist tomorrow’s soldiers.

– Robots can perform many duties too dangerous for humans (cleaning up toxic spills, finding and destroying land mines, cleaning up nuclear waste sites, etc.).


Language

The Structure of Language• Language: a means of communicating

thoughts and feelings, using a system of socially shared but arbitrary symbols arranged according to rules of grammar.

• Psycholinguistics: the study of how language is acquired, produced, and used, and how the sounds and symbols of language are translated into meaning.


Language

The Structure of Language• The structure and rules governing language

involve four basic building blocks – phonemes, morphemes, syntax, and semantics.

• Phonemes: the smallest units of sound in a spoken language.– Letters combined to form sounds are also

phonemes– English uses about 45 phonemes


Language

The Structure of Language continued

• Morphemes: the smallest units of meaning in a language.

– In almost all cases in the English language, a morpheme is made of two or more phonemes.

– Morphemes, singly and in combination, form the words in a language and provide meaning.

• Syntax: the aspect of grammar that specifies the rules for arranging and combining words to form phrases and sentences.


Language

The Structure of Language (continued)• Semantics: the meaning derived from

morphemes, words, and sentences.• The same word can have different meanings,

depending on how it is used in sentences.• Noam Chomsky maintained that the ability to

glean a meaningful message from a sentence is stored in a different area of the brain than are the words used to compose the sentence.


Language

The Structure of Language (continued)

• Chomsky distinguished between the surface structure and the deep structure of a sentence.

• Surface structure: the literal words of a sentence that are spoken or written.

• Deep structure: the underlying meaning of a sentence.


Language


• In some sentences, the surface structure and the deep structure are the same.

• Alternatively, a single sentence may have one or more different deep structures.


Language


• Pragmatics: the characteristics of spoken language that help you decipher the social meaning of utterances.

• One aspect of pragmatics is prosody, or intonation.

• In English, statements fall in intonation at the end, while questions rise.


Language

Language and the Brain• Researchers used PET scans to view activity in areas

of the brains of Italian and English speakers while they read aloud a list of words and nonwords.

• Compared with the English speakers, the Italian speakers showed greater brain activity in an upper area of the left temporal lobe when reading both words and nonwords.

• Research provides some support for the assumption that the more proficient and the more expert a person is at a given task, the greater the neural activity in the brain structure that handles that task.


Language

Animal Language

• As far as scientists know, humans are the only species to have developed this rich, varied, and complex system of communication.

• Chimpanzee communication

– Allen and Beatrix Gardner took in Washoe when she was one year old and taught her sign language.

– By the end of her fifth year she had mastered about 160 signs.


Language

Animal Language (continued)

Chimpanzee Language (continued)

• David Premack taught another chimp, Sarah, to use an artificial language he developed.

• Its symbols consisted of magnetized chips of various shapes, sizes and colors.

• Sarah mastered the concepts of similarities and differences, and eventually she could signal whether two objects were the same or different with nearly perfect accuracy.


Sarah’s SymbolsCopyright © Allyn & Bacon 2006


Language


Chimpanzee Language (continued)

• Herbert Terrace taught sign language to a chimp they called Nim Chimpsky and reported Nim’s progress from the age of 2 weeks to 4 years.

• Nim learned 125 symbols, which is respectable, but does not amount to language.

• Chimps like Nim simply imitate their trainers and make responses to get reinforcers, according to the principles of operant conditioning, not the rules of language.


Language


Communication in Other Animals

• Most animal species studied by language researchers are limited to motor responses, such as sign language, gestures, using magnetic symbols, or pressing keys on symbol boards.

• Research with sea mammals such as whales and dolphins has established that they apparently use complicated systems of grunts, whistles, clicks, and other sounds to communicate within their species.


Language

Language and Thinking• Linguistic relativity hypothesis: the notion

that the language a person speaks largely determines the nature of that person’s thoughts.

• Eleanor Rosch tested whether people whose language contains many names for colors are better at thinking about and discriminating among colors than people whose language has only a few color names.

• Rosch’s study did not support the linguistic relativity hypothesis.


Language

Language and Thinking (continued)

Sexism in Language

• Studies confirm that the generic use of he, him, and his is interpreted heavily in favor of males.

• If this were not the case, the following sentence would not seem unusual at all: “Like other mammals, man bears his offspring live.”


Language

Bilingualism

• Most native-born Americans speak only English.

• But in many other countries around the world, the majority of citizens speak two or even more languages.

• Research suggests that there are both advantages and disadvantages to learning two languages early in life.


Language

Bilingualism (continued)• One of the plusses is that, among preschool

and school-age children, bilingualism is associated with better metalinguistic skills, the capacity to think about language.

• On the downside, even in adulthood, bilingualism is sometimes associated with decreased efficiency in memory tasks involving words.


Language

Bilingualism (continued)• Researchers have found that there is no age at

which it is impossible to acquire a new language.

• People who are younger when they learn a new language are far more likely to be able to speak it with an appropriate accent.

• One reason for this difference between early and late language learners may have to do with slight variations in neural processing in Broca’s area, the area of the brain that controls speech production.


Review of Learning Objectives


1. How do we form images, and how does imagery help us think?

2. How do formal and natural concepts differ?

3. What is the difference between deductive and inductive reasoning?



Decision Making

1. How are the additive strategy and elimination by aspects used in decision making?

2. What are the strengths and weaknesses of the availability and representativeness heuristics?

3. How does framing help with decision making?



Problem Solving

1. What are three basic approaches to problem solving, and how do they differ?

2. How do functional fixedness and mental set impede problem solving?



High-Tech Applications of Cognition

• In what ways does artificial intelligence resemble human cognition?

• How do scientists use artificial neural networks?

• What are some practical applications of robotics?



Language1. What are the necessary components of any

language?2. What areas of the brain are involved in

producing and comprehending language?3. How does animal communication differ from

that of humans?4. In what ways does thinking influence

language?5. What is the best time in life to learn a second

language, and why?

Technology

Psy i ch.7