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John DeweyEncyclopædia Britannica, Inc.

The divergence between these theories appears, however, to represent a false dichotomy. The protocols of Köhler’s chimpanzee experiments and of the rather similar experiments performed later under Pavlov’s auspices show that insight typically is preceded by a period of groping and of misguided attempts at a solution that are eventually abandoned. On the other hand, even the trial-and-error behaviour of an animal in a simple selective-learning situation does not consist of a completely blind and random sampling of the behaviour of which the learner is capable. Rather, it consists of responses that very well might have succeeded if the circumstances had been slightly different.

Newell, Simon, and the American computer scientist J. Clifford Shaw pointed out the indispensability in creative human thinking, as in its computer simulations, of what they called “heuristics.” A large number of possibilities may have to be examined, but the search is organized heuristically in such a way that the directions most likely to lead to success are explored first. Means of ensuring that a solution will occur within a reasonable time, certainly much faster than by random hunting, include adoption of successive subgoals and working backward from the final goal (the formula to be proved, the state of affairs to be brought about). Motivational aspects of thinking

The problem to be taken up and the point at which the search for a solution will begin are customarily prescribed by the investigator for a subject participating in an experiment on thinking (or by the programmer for a computer). Thus, prevailing techniques of inquiry in the psychology of thinking have invited neglect of the motivational aspects of thinking. Investigation has barely begun on the conditions that determine when the person will begin to think in preference to some other activity, what he will think about, what direction his thinking will take, and when he will regard his search for a solution as successfully terminated (or abandon it as not worth pursuing further). Although much thinking is aimed at practical ends, special motivational problems are raised by “disinterested” thinking, in which the discovery of an answer to a question is a source of satisfaction in itself.

In the views of the Gestalt school and of the British psychologist Frederic C. Bartlett, the initiation and direction of thinking are governed by recognition of a “disequilibrium” or “gap” in an intellectual structure. Similarly, Piaget’s notion of “equilibration” as a process impelling advance from less-equilibrated structures, fraught with uncertainty and inconsistency, toward better-equilibrated structures that overcome these imperfections was introduced to explain the child’s progressive intellectual development in general. Piaget’s approach may also be applicable to specific episodes of thinking. For computer specialists, the detection of a mismatch between the formula that the program so far has produced and some formula or set of requirements that define a solution is what impels continuation of the search and determines the direction it will follow.

Neobehaviourism (like psychoanalysis) has made much of secondary reward value and stimulus generalization—i.e., the tendency of a stimulus pattern to become a source of satisfaction if it resembles or has frequently accompanied some form of biological gratification. The insufficiency of this kind of explanation becomes apparent, however, when the importance of novelty, surprise, complexity, incongruity, ambiguity, and uncertainty is considered. Inconsistency between beliefs, between items of incoming sensory information, or between one’s belief and an item of sensory information evidently can be a source of discomfort impelling a search for resolution through reorganization of belief systems or through selective acquisition of new information.

The motivational effects of such factors began receiving more attention in the middle of the 20th century, mainly because of the pervasive role they were found to perform in exploratory behaviour, play, and aesthetics. Their larger role in all forms of thinking has come to be appreciated and has been studied in relation to curiosity, conflict, and uncertainty. D.E. Berlyne Types of thinking

Philosophers and psychologists alike have long realized that thinking is not of a “single piece.” There are many different kinds of thinking, and there are various means of categorizing them into a “taxonomy” of thinking skills, but there is no single universally accepted taxonomy. One common approach divides the types of thinking into problem solving and reasoning, but other kinds of thinking, such as judgment and decision making, have been suggested as well. Problem solving

Problem solving is a systematic search through a range of possible actions in order to reach a predefined goal. It involves two main types of thinking: divergent, in which one tries to generate a diverse assortment of possible alternative solutions to a problem, and convergent, in which one tries to narrow down multiple possibilities to find a single, best answer to a problem. Multiple-choice tests, for example, tend to involve convergent thinking, whereas essay tests typically engage divergent thinking. The problem-solving cycle in thinking

Many researchers regard the thinking that is done in problem solving as cyclical, in the sense that the output of one set of processes—the solution to a problem—often serves as the input of another—a new problem to be solved. The American psychologist Robert J. Sternberg identified seven steps in problem solving, each of which may be illustrated in the simple example of choosing a restaurant:

Problem identification. In this step, the individual recognizes the existence of a problem to be solved: he recognizes that he is hungry, that it is dinnertime, and hence that he will need to take some sort of action.

Problem definition. In this step, the individual determines the nature of the problem that confronts him. He may define the problem as that of preparing food, of finding a friend to prepare food, of ordering food to be delivered, or of choosing a restaurant.

Resource allocation. Having defined the problem as that of choosing a restaurant, the individual determines the kind and extent of resources to devote to the choice. He may consider how much time to spend in choosing a restaurant, whether to seek suggestions from friends, and whether to consult a restaurant guide.

Problem representation. In this step, the individual mentally organizes the information needed to solve the problem. He may decide that he wants a restaurant that meets certain criteria, such as close proximity, reasonable price, a certain cuisine, and good service.

Strategy construction. Having decided what criteria to use, the individual must now decide how to combine or prioritize them. If his funds are limited, he might decide that reasonable price is a more important criterion than close proximity, a certain cuisine, or good service.

Monitoring. In this step, the individual assesses whether the problem solving is proceeding according to his intentions. If the possible solutions produced by his criteria do not appeal to him, he may decide that the criteria or their relative importance needs to be changed.

Evaluation. In this step, the individual evaluates whether the problem solving was successful. Having chosen a restaurant, he may decide after eating whether the meal was acceptable.

This example also illustrates how problem solving can be cyclical rather than linear. For example, once one has chosen a restaurant, one must determine how to get there, how much to tip, and so on. Structures of problems

Psychologists often distinguish between “well-structured” and “ill-structured” problems. Well-structured problems (also called well-defined problems) have clear solution paths: the problem solver is usually able to specify, with relative ease, all the steps that must be taken to reach a solution. The difficulty in such cases, if any, has to do with executing the steps. Most mathematics problems, for example, are well-structured, in the sense that determining what needs to be done is easy, though carrying out the computations needed to reach the solution may be difficult. The problem represented by the question, “What is the shortest driving route from New York City to Boston?” is also well-structured, because anyone seeking a solution can consult a map to answer the question with reasonable accuracy.