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Psychology, 5/e Wortman, Loftus & Weaver | |||||
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The ability of humans to solve problems is vastly greater than that of other species. This process of problem solving requires the organization of information in the mind to accomplish some desired end, also known as cognition. Because cognition is a nonobservable behavior, some psychologists have argued that it cannot or should not be studied. Even if we ask individuals to describe their thoughts, these self-reports might not always be accurate because humans do not always have complete access to their cognition (Theme 3).
The mental constructs that enable us to classify objects and events are called concepts. Concepts are the building blocks of thought; they allow us to generalize from one situation to another. Concepts are organized into hierarchies, with more general concepts that include more specific concepts. Everyday speech relies mostly on concepts at the intermediate or basic level, thereby giving neither too little nor too much detail.
Natural concepts, such as furniture or fruit, do not have a set of defining features which always apply. Eleanor Rosch has suggested we do not encode most natural concepts according to their defining features, but rather encode them in terms of a prototype--an example which best illustrates the concept. Research has shown that a feature-based model may not be incompatible with a prototype model. One such view is that we use a feature-based core to distinguish one concept from another but use a prototype-matching process to identify a particular example as belonging to a category. Ross and Spalding have suggested that concepts are best understood as exemplars, which are multiple examples of concepts we are exposed to.
Problem solving requires a knowledge of concepts and the relationship among them. Problem solving can be conceptualized as a three-step process. First, the problem must be represented, or interpreted. For a difficult problem, often the best strategy is to try to examine it from several perspectives. Humans, however, have a tendency to cling to the initial representation of a problem, despite the fact that it may not be helpful in a particular situation. This is called functional fixedness--the tendency to view an object as being used only for its customary function. The use of schemas by experts increases their ability to represent problems in ways that make them easier to solve. Also, research aimed at helping people solve arithmetic word problems suggests that more effective problem representation strategies can be learned.
The second problem-solving step is to devise solution strategies. The limits of our short-term memory make such strategies necessary. An algorithm is a precisely stated set of rules that generally solves all problems of a particular type. A heuristic is a problem-solving strategy which depends on rules-of-thumb or best guesses on how to proceed. It has the advantage of being faster than an algorithmic method. People use several general heuristics, such as subgoal analysis (dividing a complex problem into smaller component problems), means-end analysis (comparing present to desired positions and trying to find a way to reduce the difference), and backward search (starting at the end of the problem and working backward). Heuristics can be useful in overcoming the limits imposed by short-term memory, but they have the disadvantage of promoting the tendency toward repeating heuristic solutions that have worked in the past even when they clearly are no t appropriate to the present situation. The inclination to use an old perspective in a new situation is called a mental set. One way to break out of an unproductive mental set is to get away from the problem for awhile.
The third and final step in problem solving is deciding when a satisfactory solution has been reached. Sometimes deciding on the best solution is difficult; pressures of time and limits of cognitive capacity may determine when a particular problem-solving effort ends. Herbert Simon argues that humans search for solutions until they find one that works satisfactorily, even if that is not the best possible solution. Simon calls this tendency to behave rationally within certain constraints bounded rationality.
Creative solutions involve novel restructuring of information and must be workable solutions. Creative insights may occur in sudden and unpredictable ways; they may appear in the form of analogies or arise unconsciously. Creative thinkers tend to have strong motivation and persistence. Creative people are usually intelligent, but intelligent people are not always creative. People can be trained to increase the ability to perform divergent thinking, the ability to generate many different answers to a question. However, people high in divergent thinking are not always the most creative. Some research suggests that the most creative people are especially likely to take risks.
In making decisions, two sets of variables are considered: the value one places on the potential outcomes (utility), and the likelihood that each outcome will actually take place, called the probability. Although we seldom formally calculate utility and probability in making a decision, research demonstrates that we generally follow this model in decision making. Much of our problem in making complex decisions results from the limited capacity of our working memory.
People often rely on heuristics rather than statistical probability to solve problems. If the limitations of these heuristics are ignored, these strategies can lead to serious errors. The representativeness heuristic, for example, involves stereotyping people and attributing to them certain characteristics. Although this is a useful method of reducing the amount of information to be processed, people using it sometimes overlook objective information and base their judgments on inaccurate data.
The availability heuristic specifies that easy-to-remember events are more frequent than events that are difficult to remember. That is, the probability of an event occurring in the present is directly related to its frequency in the past (Theme 1). Although this information is generally useful, factors other than frequency of occurrence affect our ability to recall events. Media coverage, for instance, has a significant influence on how people will estimate causes of death. People overestimate the risk of death from highly publicized events and underestimate the risk of death from rarely reported causes. Generally, however, people are better problem solvers in real life than in the laboratory, and misperceptions do not make heuristics useless.
Language is complex and central to human existence. It is our primary means of communication. It is extremely flexible and rich in the meanings it can convey.
Because language uses symbols to represent other objects and events, it allows us to communicate beyond the concrete and the present. Furthermore, the symbolism is arbitrary, agreed on only by convention. Language is based on a principle of combination in which components are arranged in a nearly infinite number of different patterns.
Humans have a remarkable facility for using and understanding language, usually with little or no effort. Yet language depends on very complex mental processes.
Language can be analyzed at different levels. For example, a phoneme is a class of slightly varying sounds that speakers of a language perceive as linguistically similar. Different languages use somewhat different phoneme classes. Most languages exclude some phonemes that may be included in other languages. Every language has its own morphological rules for combining phonemes into meaningful units. A morpheme is the smallest unit that has meaning. Phonemes may be processed by specialized circuitry in the brain which is separate from that used to identify nonspeech noises. Other psychologists take a different view, believing that we hear phonemes clearly because the brain anticipates the speech sounds we are apt to encounter. The process of determining the meaning of a string of words and morphemes is called comprehension (Theme 4).
When we are reading sentences, rather than words, we automatically dissect them into phrases, called constituents, that make sense when taken together. From these constituents, we extract propositions, or units of meaning, that the sentence contains. The syntactic approach argues that we understand written language by relying on its syntax, the ways in which words and their parts are combined according to rules. The semantic approach analyzes language according to its meaningful components rather than the order and pattern in which the words are combined. We use both the syntactic and semantic approaches in understanding language.
In addition to syntax and meaning, we also rely on a general understanding of the current setting in our interpretation of language. We make assumptions about speech and what it refers to, and oftentimes these implied assumptions are remembered the same way we remember explicit information. The field called pragmatics studies the implicit understandings people have about how language should be used in particular social contexts.
Language and thought are intimately related, although the exact nature of this relationship is the subject of debate. For example, Benjamin Whorf argued that language shapes thought. Whorf argued that language forces us to perceive our environment in a manner shaped by and consistent with our language, a tendency called forced observation. This notion is called the linguistic relativity hypothesis.
Research on cultural differences in the perception of color reveals, however, that different cultures perceive the same colors, regardless of the number of basic color terms in a particular language. This evidence contradicts the linguistic relativity hypothesis. An alternative view is that thought processes shape language. Here, the attempt is to discover linguistic universals, features found in all languages. This view is supported by research showing that all cultures assign color names in the same order of importance.
An interesting question is whether language is a uniquely human ability. In the 1940s, early attempts to teach spoken language to chimpanzees failed, due to chimpanzees’ lack of the physiological structures necessary for speech production. Beatrice and Allen Gardner repeated these experiments with a chimp named Washoe, this time using ASL, the sign language used by deaf humans. After four years of training, Washoe had learned 160 signs, could generalize a sign to unique situations, and could use several signs in combination. The Gardners felt that Washoe’s "language" ability was roughly equivalent to that of a three-year-old child. David Premack had similar results with a chimp named Sarah, whom he taught a language based on plastic symbols that represented words. Another chimp, Lana, learned to use a special typewriter connected to a computer. She was able to create names for previously unnamed objects. From such research, some psychologists concl ude that chimps have some capacity for understanding syntax.
Other psychologists (such as Herbert Terrace, who taught sign language to a chimp named Nim Chimpsky) question whether this capacity has been adequately demonstrated. They believe that chimps simply create sentences by word substitution. Also, chimps’ language growth is extremely limited when compared to that of children, particularly with respect to asking for names of new objects. Savage-Rumbaugh and her colleagues, however, have had considerable success in teaching chimps to name tasks, thereby indicating that chimps do understand that words are not just discriminative stimuli signaling rewards but rather are symbols which stand for objects. The bonobo, or "pygmy chimp" Kanzi has displayed languagelike vocalizations.
Researchers agree that chimps do not process language in the same way that humans do. Further research will probably be directed at establishing the limits of a chimp’s ability to communicate, rather than simply determining whether or not chimps can talk.
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