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What is concept formation?

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Introduction

Humans are faced with the task of making sense of a world that contains a seemingly endless array of unique objects and living things. To reduce this endless uniqueness to something that is mentally manageable, people form concepts. A concept can be defined as an abstract idea based on grouping objects or events according to their common properties. Concepts guide thoughts and behaviors, so it is important to understand both the nature of those concepts and how people construct them. Animals of all types also have the ability to form concepts. Animals form concepts at a much more fundamental level than humans, but they have been shown to differentiate among various colors and various geometric patterns, for example. Throughout its long history, research on concept formation has used animals, such as pigeons and rats, as well as human subjects.

In daily life, the term “concept” is used in a way that is different from the way in which psychologists use it. Whereas psychologists say that a concept exists when two or more things are grouped on the basis of a common feature or property of each, everyday language uses the term “concept” to refer to abstract ideas, such as the concept of “integrity,” or to a mental picture in one’s mind, for example, “I have a concept of how I want my room to look.” The term is used here as psychologists use it. Psychologists also frequently use the word “category” as a synonym for “concept.”

Psychologists have had to be innovative when designing experiments to study concept formation, because there is no way to observe the way in which people think or form concepts directly. The techniques vary from study to study, but subjects are typically asked to choose which of several items fits a particular concept.

The early researchers in the area, including Jerome Bruner, Jacqueline Goodnow, and George Austin, used materials in their experiments that have since been referred to as “artificial” stimuli or concepts, because they used geometric figures such as circles and squares of various sizes and shapes that were deliberately devised to have only a certain number of alterable characteristics or features. Years later, researchers such as Eleanor Rosch became interested in “natural” concepts, based on complex real-world objects, in which partial membership in a category is a possible alternative.

Techniques of Study

In a typical study on artificial concept formation, a psychologist would construct visual patterns that would not normally be encountered in daily life. The patterns would be printed on cards to create the stimulus materials, or anything presented to a subject during the course of an experiment that requires that subject to make a response. These visual patterns would vary in terms of size, shape, number, or color, for example, and would be referred to as dimensions. Basically, a dimension is any changeable characteristic of the stimulus. A dimension can have two or more values, and the value is determined by the number of sizes, shapes, numbers, or colors being utilized.

In this example, each dimension can have three values. In other words, there would be objects of small, medium, and large size; circular, triangular, and square shapes; one, two, or three items; and purple, red, and green colors. Varying those dimensions and values, the particular stimulus patterns presented to the subject would be things such as two large green squares, three small red triangles, or perhaps one medium purple circle. The concept to be learned is selected by the researcher beforehand and is kept secret from the subject, because the subject must discover the concept. The concept might be something such as “purple triangles of any size and any number.” Thus, in this case, the specific concept to be learned would be “purple and a triangle.”

In a concept-formation task, the stimuli are usually presented to the subjects in one of two ways: the reception method or the selection method. In the reception technique, the subject is shown a single card and is asked to state whether that card displays the concept that the experimenter had in mind. The experimenter then tells the subject whether the response is correct or incorrect. The subject is then shown another card.

In the selection technique, by contrast, the entire set of cards is simultaneously displayed to the subject in one large array. The number of cards in the entire set is determined by the combination of all possible dimensions and values. The subject selects a particular card from the array, stating whether it displays the concept to be learned. Following each selection and judgment, the experimenter informs the subject about correctness.

Use of Rules and Categories

Some tasks require subjects to discover the values, the rule, or both. A rule tells how the values must be combined. The two most common kinds of rules are called conjunction and disjunction. The conjunction rule uses the word “and,” as in “all figures that are both purple and triangles.” Thus, a subject learning a concept involving the conjunction rule would learn to respond yes to all purple triangles and no to all other figures. The disjunction rule uses the word “or,” as in “all figures that are purple or a triangle or both.”

An important development in research on concepts involves natural concepts or real-life categories. Rosch pointed out that the artificial-concept learning tasks use materials unlike those encountered in the everyday world. Most concepts in the everyday world do not fall into neatly defined categories. Many have fuzzy borders—conceptual borders that appear ill defined and shift according to the context in which the category member occurs—that involve some uncertainty. For example, is a tomato a fruit or a vegetable? Rosch theorized that people decide whether an item belongs to a particular category by comparing that item with a prototype or best example for that category. An apple is highly prototypical of the fruit category, whereas a coconut is a less typical example.

Making Sense of the Environment

If a person understands the concept of sunglasses, that individual can recognize something as a pair of sunglasses even though they may look different from all the other sunglasses the person has seen before. A new pair of sunglasses with iridium-coated lenses can be included within the concept because the pair has qualities that are common to the entire class of objects that people refer to as sunglasses. They have earpieces, they block out the sun to some degree, and they cover the eyes. Sunglasses belong to the even larger conceptual category of eyewear. Concepts such as eyewear, cookware, furniture, and vehicles are very useful. It would be impossible to think intelligently without the ability to form concepts. Without that ability, every time a person encountered something that was slightly different from other things, it would be necessary to learn about that object as if it were completely new.

A person would then primarily function instinctually because, according to Michael Eysenck, it would be impossible to relate prior learning to new situations. By applying concepts, a person can develop an immediate understanding of new objects or ideas, because they can be related to a general class of similar objects and ideas that are familiar. A person knows what to expect from an object, even when it is encountered for the first time. In this way, thinking beings save an amazing amount of work. Concepts reduce the complexity of the environment and eliminate the need to learn constantly.

Implications for Education

The development and refinement of some concepts take place over a long period of time. A person can have general concepts about some things, precise concepts about others, and also be in the process of refining vague concepts. In the course of life, a person’s understanding of a particular concept develops and expands with additional experience, advanced training, and new information. Understanding this has ramifications for formal education.

Much teaching is directed toward the development of concepts. In fact, it would be almost impossible to use the vast amount of mental information that is available to human beings to solve problems, make decisions, understand language, and communicate without the ability to simplify the world by means of conceptualization. One of the principal objectives of formal education is to allow students to formulate a hypothesis, or tentative guess, about how some attribute contributes to a concept. Students are then encouraged to test the hypothesis. If it is wrong, they can adopt a new hypothesis that incorporates different attributes or the same attributes but with different rules, based on feedback they receive from an instructor.

Researchers have identified a number of factors involved in concept learning that apply to the process of education. One factor is the number of attributes. It is easier to learn a concept if there are only one or two relevant attributes, rather than several. Another factor is salience. It is easier to learn a concept if the relevant attributes are salient, or obvious. A third factor is positive examples. People tend to make better use of positive examples, although it is sometimes helpful and even necessary to give some negative examples. For example, imagine teaching a young child the concept of “house cat” by using examples that are all positive. One shows the child pictures of a Persian, a Siamese, and a Russian Blue. From the viewpoint of a teacher, it is desirable to highlight or emphasize the relevant features of the concepts to make them salient, such as mentioning that the creatures in all the pictures have fur. The child learns to say “cat” to each picture. A teacher cannot, however, be certain which aspects of the pictures determine the child’s response. For all the teacher knows, the child considers a picture of a cat to be another example of a “dog.” For this reason, it is important to include relevant negative examples. In general, negative examples tend to be more useful in later stages of training.

Artificial Intelligence

As science fiction becomes fact, it is becoming desirable to be able to “teach” computers how to form concepts. This type of investigation is conducted in the field of artificial intelligence. To develop artificial ways of duplicating human thought and intelligence, it is important to know how the thought process is accomplished by humans. Imagine a task in which a computer is asked to identify whether something is a triangle. A computer could be programmed to learn the concept, but it would take a very sophisticated program. In comparison, it is easy for humans to recognize immediately what constitutes a triangle, based on vast experience with other triangular objects. Concept formation in computers provides the foundation for the ability to recognize handwriting, fingerprints, speech, and many other things electronically.

One of the problems for computers is that, although some concepts are well defined, most are not: This is Rosch’s point. In addition, human experience and context play an important role in concept formation, which poses difficulties for computers. Even more troublesome for a computer is the fact that many conceptual categories are based on human imagination. Because people have knowledge about the world and how it operates, they adjust their conceptual categories to fit reality. Unless computers have human knowledge and experience, their concepts will not be exactly like those of humans.

Concept Theories

Throughout the history of the scientific study of concept formation, three main types of theories have become apparent. They are association theory, hypothesis-testing theory, and information-processing theory. In the associationistic view, the organism passively receives information from the environment. Each example of the concept that has yet to be learned provides the organism with an additional piece of information. In this way, relevant features are reinforced, whereas irrelevant features disappear. This approach requires nothing from the organism except a memory of previous examples. This approach was in vogue in the first half of the twentieth century. According to associationistic views, stimuli gradually become associated with some response by means of a complex form of discrimination learning. By means of discrimination learning, discriminable aspects of stimulus patterns are detected and labeled. Later modifications of association theory introduced the idea of mediation, assuming that concepts are formed because of an intervening step in the mind of the learner, which connects the stimuli with the response.

A second line of theory development, hypothesis testing, views the subject as an active participant in the process of concept learning. According to this line of thought, the organism always has some hypothesis regarding the unknown concept. Incoming information is used to check the current hypothesis and is used as the basis for modifying that hypothesis if it is incompatible with existing evidence. Eventually, the organism hits on the correct hypothesis and forms the concept. The research of Bruner, Goodnow, and Austin, which was first published in 1956, adhered to the view of the organism as an active hypothesis tester.

Finally, theories were developed that emphasized the information-processing nature of concept formation. These theories view the process in terms of a sequence of decisions made by the learner. The learner is seen as accepting external information, or stimuli, processing the information in a variety of ways, and producing some final response. One of the earliest attempts to produce an information-processing model for the learning of concepts was made by Earl Hunt in 1962.

Bibliography

Bourne, Lyle E., Jr. Human Conceptual Behavior. 1966. Reprint. Boston: Allyn, 1970. Print.

Bourne, Lyle E., Jr., Roger L. Dominowski, and Elizabeth F. Loftus. Cognitive Processes. 2d ed. Englewood Cliffs: Prentice, 1986. Print.

Braisby, Nick, and Angus Gellatly. Cognitive Psychology. Oxford: Oxford UP, 2012. Print.

Bruner, Jerome S., Jacqueline J. Goodnow, and George A. Austin. A Study of Thinking. 5th ed. New Brunswick: Transaction, 2005. Print.

Eysenck, Michael W., and Mark T. Keane. A Handbook of Cognitive Psychology. 4th ed. Hillsdale: Lawrence, 1984. Print.

Hunt, Earl B. Concept Learning: An Information Processing Problem. 1962. Reprint. New York: Krieger, 1974. Print.

Quaranta, Mario. "Fuzzy Set Theory and Concepts: A Proposal for Concept Formation and Operationalization." Comparative Sociology 12.6 (2013): 785–820. Print.

Robinson-Riegler, Bridget, and Gregory Robinson-Riegler. Cognitive Psychology: Applying the Science of the Mind. Boston: Pearson, 2012. Print.

Rosch, Eleanor H. “Classification of Real-World Objects: Origins and Representation in Cognition.” Thinking: Readings in Cognitive Science. Ed. P. N. Johnson-Laird and P. C. Wason. Cambridge: Cambridge UP, 1980. Print.

Stainton, Robert, ed. Contemporary Debates in Cognitive Science. Malden: Blackwell, 2006. Print.

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