LEARNING THEORY

historical overview
diane f. halpern
beth donaghey

constructivist approach
mary lamon

schema theory
william f. brewer

HISTORICAL OVERVIEW

Learning theories are so central to the discipline of psychology that it is impossible to separate the history of learning theories from the history of psychology. Learning is a basic psychological process, and investigations of the principles and mechanisms of learning have been the subject of research and debate since the establishment of the first psychological laboratory by Wilhelm Wundt in Leipzeig, Germany, in 1879. Learning is defined as a lasting change in behaviors or beliefs that results from experience. The ability to learn provides every living organism with the ability to adapt to a changing environment. Learning is an inevitable consequence of living–if we could not learn, we would die.

The evolution of learning theories may be thought of as a progression from broad theories developed to explain the many ways that learning occurs to more specific theories that are limited in the types of learning they are designed to explain. Learning theories are broadly separated into two perspectives. The first perspective argues that learning can be studied by the observation and manipulation of stimulus-response associations. This is known as the behaviorist perspective because of its strict adherence to the study of observable behaviors. This perspective was first articulated in 1913 by John Watson, who argued that psychology should be the study of observable phenomena, not the study of consciousness or the mind. Watson believed that objective measurement of observable phenomena was the only way to advance the science of psychology.

The second type of learning theory argues that intervening variables are appropriate and necessary components for understanding the processes of learning. This perspective falls under the broad rubric of cognitive learning theory, and it was first articulated by Wilhem Wundt, the acknowledged "father of psychology," who used introspection as a means of studying thought processes. Although proponents of these two perspectives differ in their view of how learning can be studied, both schools of thought agree that there are three major assumptions of learning theory: (1) behavior is influenced by experience, (2) learning is adaptive for the individual and for the species, and (3) learning is a process governed by natural laws that can be tested and studied.

Behavior Theory

The behaviorist perspective dominated the study of learning throughout the first half of the twentieth century. Behaviorist theories identified processes of learning that could be understood in terms of the relationships between the stimuli that impinge on organisms and the way organisms respond, a view that came to be referred to as S-R theories. A central process in S-R theories is equipotentiality. Equipotential learning means that learning processes are the same for all animals, both human and nonhuman. By studying learning in nonhuman animals, the early behaviorists believed they were identifying the basic processes that are important in human learning. They also believed that learning could only be studied by observing events in the environment and measuring the responses to those events. According to the behaviorists, internal mental states are impossible topics for scientific inquiry, and thus are not necessary in the study of learning. For behaviorists, a change in behavior is the only appropriate indicator that learning has occurred. According to this view, all organisms come into the world with a blank mind, or, more formally, a tabula rasa (blank slate), on which the environment writes the history of learning for that organism. Learning, from the behaviorist perspective, is what happens to an organism as a result of its experiences.

Types of behavioral learning. There are two main types of learning in the behaviorist tradition. The first is classical conditioning, which is associated with the work of Ivan Pavlov (1849–1936), a Russian physiologist who studied the digestive processes of dogs. Pavlov noticed that dogs salivated in the absence of food if a particular stimulus was present that had previously been paired with the presentation of food. Pavlov investigated the way in which an association between a neutral stimulus (e.g., a lab technician who fed the dogs), an unconditioned stimulus (food), and an unconditioned reflex (salivation) was made. Pavlov's classic experiment involved the conditioning of salivation to the ringing of a bell and other stimuli that were not likely to make a dog salivate without a previously learned association with food.

In the initial stages of the classical conditioning paradigm, an unconditioned response (UCR; in this case, salivation) is elicited by the presentation of an unconditioned stimulus (UCS; in this case, food). If a neutral stimulus (one that does not elicit the UCR, such as a bell) is paired with the presentation of the UCS over a series of trials, it will come to elicit a conditioned response (CR; also salivation in this example), even when the UCS (food) is absent. In the paradigm of classical conditioning, the previously neutral stimulus (bell) becomes a conditioned stimulus (CS), which produces the conditioned response (CR) of salivation. In other words, the animal in the experiment learns to associate the bell with the opportunity to eat and begins to salivate to the bell in the absence of food. It is as though the animal came to think of the bell as "mouthwatering," although behaviorists never would have used terms like think of, because thinking is not a directly observable behavior.

Even though the original work on classical conditioning was performed using nonhuman animals, this type of learning applies to humans as well. Learned taste aversions and the development of specific phobias are examples of classical conditioning in humans. For example, the first time a person hears a drill at a dentist's office, it probably will not cause the palms to sweat and the heart rate to quicken. However, through the pairing of the sound with the unpleasant sensation of having a cavity drilled, the sound itself may come to elicit symptoms of fear and anxiety, even if one is not in the dentist's chair. Feelings of fear and anxiety may generalize so that the same fear response is elicited by the sight of the dentist's lab coat or the dental chair.

The second type of learning that is categorized in the behaviorist tradition is instrumental or operant, conditioning. The main difference between instrumental conditioning and classical conditioning is that the emphasis is on behavior that is voluntary (emitted), not reflexive (elicited). The target behavior (e.g., a peck at a lever if one is studying birds) comes before the conditioning stimulus (e.g., food), as opposed to the classical model, which presents the conditioning stimulus (e.g., bell) prior to the target behavior (e.g., salivation).

In the instrumental paradigm, behaviors are learned as a result of their consequences. Edward Thorndike (1874–1949) was a pioneer in instrumental conditioning, although he resisted the label of behaviorist. In his view, the consequences of behaving in a particular way controlled learning. Behavior was instrumental in obtaining a goal, and the consequences of the behavior were responsible for the tendency to exhibit (and repeat) a behavior. Thorndike named this principle of instrumental conditioning the law of effect. He argued that if a behavior had a positive consequence or led to a satisfying state of being, the response (behavior) would be strengthened. If, on the other hand, a behavior had a negative consequence, the response would be weakened. Thorndike developed the principles of instrumental conditioning using a puzzle box that required that an animal exhibit a certain behavior (push a latch) to obtain a goal (open a door for access to food). The animal was given the opportunity, through trial and error, to discover the required behavior, and the behavior was reinforced through the opening of the door and access to food. With practice, the animal decreased the time that it needed to open the door. In the instrumental paradigm, the animal learned an association between a given situation and the response required to obtain a goal.

Operant conditioning and reinforcement. B. F. Skinner (1904–1990) is credited with the development of the operant-conditioning paradigm. Similar to instrumental conditioning, operant conditioning requires that an organism operate on the environment to achieve a goal. A behavior is learned as a function of the consequences of the behavior, according to a schedule of reinforcement or punishment. Unlike Thorndike, who used the concept of reward and satisfying states, Skinner emphasized the influence of reinforcers. Reinforcers are events that follow a response and increase the likelihood that the response will be repeated, but they do not suggest the operation of a cognitive component such as reward (or pleasure). Learning is influenced according to the schedules of reinforcement in the operant paradigm. Skinner tested the operant theory by carefully controlling the environment to study behavior and the effects of reinforcement.

According to Skinner, operant conditioning has two laws. The first is the law of conditioning, which states that reinforcement strengthens the behavior that precedes it, which makes it more likely that the behavior will be repeated. The second is the law of extinction, which states that lack of reinforcement for a behavior will make that behavior less likely to reoccur. Reinforcement consists of two types of events, those that are positive, which means that when they are presented (e.g., present tasty food) the probability of a behavior occurring is increased (e.g., press a lever to get the tasty food), and those that are negative, which means that when they are removed (e.g., stop a loud sound or painful shock) the probability of a behavior occurring is increased (e.g., press a lever to stop a loud sound or painful shock). Punishment is defined as an event that weakens the tendency to make a response. Punishment could involve presenting an aversive stimulus (e.g., presenting a loud sound or painful shock), or it could involve removing access to a positive stimulus (e.g., removing a tasty food when a lever is pressed).

Skinner also experimented with different reinforcement schedules, and he found that different schedules produced different patterns of responding. Continuous schedules of reinforcement deliver a reinforcer every time the target behavior is exhibited. These schedules are effective in establishing the target behavior, but the behavior disappears quickly if the contingency is not met. Intermittent schedules of reinforcement deliver the reinforcer on a ratio schedule. For example, an experimenter may decide to reinforce every fourth response that an animal makes, or a reinforcer may be presented after a fixed or random time interval. The two types of intermittent schedules that maintain a high rate of responding and are very resistant to extinction are variable ratio and variable interval schedules.

Strict adherence to the behaviorist tradition excluded analysis of mental or internal events. However, Skinner acknowledged the role of thought. He maintained that thought was caused by events in the environment, and therefore a theory of learning that was concerned with the influence of the environment was appropriate. Like Pavlov and Thorndike, Skinner's work was primarily conducted with nonhuman animals, but the principles of operant conditioning can be applied to humans as well, and they are widely used in behavior therapy and education.

Cognitive Theories

Although behaviorism was a prolific and dominant theory in learning through the early decades of the twentieth century, certain concerns and observations led to a resurgence of interest in cognitive theories of learning. One area of concern was the distinction between performance and learning–that is, does behaviorism describe the factors that influence performance of learned behavior, rather than the act of learning itself? Within the behaviorist literature, evidence of cognitive elements like expectation and categorization exist. Under an intermittent reinforcement schedule, for example, animals increase their rate of response immediately before a reinforcer is delivered, thus acting as though they expect it. Similarly, animals can be trained to distinguish between types of stimuli that belong to different classes. Learning this type of distinction seems to involve classification, which is a cognitive process. Most importantly, scientists who studied learning recognized that the behaviorist theories could not account for all types of learning. Humans and animals can learn something without exhibiting what they have learned, meaning that performance does not always reflect what has been learned.

Cognitive theories grew from the concern that behavior involves more than an environmental stimulus and a response, whether it be voluntary or reflexive. These theories are concerned with the influence of thinking about and remembering experiences or behavior. The assumptions about learning under cognitive theories are not the same as those for behaviorist theories, because thinking and remembering are internal events. Inferences about the internal events such as thinking and remembering can be made as long as they are paired with careful observation of behavior. Cognitive theorists assume that some types of learning, such as language learning, are unique to humans, which is another difference between these two perspectives. Cognitive theories also focus on the organism as an active processor of information that modifies new experiences, relates them to past experiences, and organizes this information for storage and retrieval. Cognitive psychologists also recognize that learning can take place in the absence of overt behavior.

Edward Tolman (1886–1959) was among the first psychologists to investigate the organization of behavior and learning. He conducted research in the behaviorist tradition (objective research on nonhuman species), but he introduced cognitive elements to his explanation of learning. In Tolman's theory, however, the cognitive elements were based on observed behavior, not on introspection. He believed that learning involved more than stimulus and response events; it involved the development of an organized body of knowledge or expectations about a given situation. Tolman conducted many of his learning experiments using rats whose learning task was to run through a maze. By varying the conditions in the maze, he came to the conclusion that learning involved an understanding about events and their consequences, and this led to purposive, goal-directed behavior. Tolman emphasized the role of expectation and its reinforcing influence on the repetition of behavior. He popularized the concept of cognitive maps, which represent an organism's understanding of the relationship between parts of the environment, as well as the organism's relationship to the environment.

In a clear break with behaviorists, Tolman noted that reinforcement was not a necessary component of learning, and that organisms could demonstrate latent learning. Latent learning is displayed only when an organism is motivated to show it. Tolman was also concerned with differences in behavior that might be attributed to internal states of the organism, a consideration that had been largely rejected by earlier theorists. In identical learning paradigms, two organisms can show different behaviors based on their different moods, physiology, or mental states.

Social learning theory. Social learning theory focuses on the sort of learning that occurs in a social context where modeling, or observational learning, constitutes a large part of the way that organisms learn. Social learning theorists are concerned with how expectations, memory, and awareness influence the learning process. Both humans and nonhumans can learn through observation and modeling. Consider, for example, the acquisition of sign language by the offspring of language-trained apes who learn to sign by watching their trained parents. Children learn many behaviors through modeling. A classic experiment by Albert Bandura (1961) allowed one group of children to observe an adult who aggressively pounded on a bobo doll (an inflatable doll used for punching), while another group watched a nonaggressive model and a third group had no model at all. The children who saw the aggressive adult often modeled (imitated) this behavior when given an opportunity to play with the same doll. The children who saw the nonaggressive model showed the least amount of aggressive play when compared to the other two groups. Social learning theorists retain the behaviorist principles of reinforcement and response contingencies, but they also extend the area of inquiry for learning to include components of cognitive processing such as attention, remembering, the processing of information about the environment, and the consequences of behavior.

Appreciation of the cognitive components of learning focused attention on the need to remember an experience over various time intervals. Information-processing theories developed from the cognitive perspective and involve the processes of coding, storing, and retrieving information about the environment. Information processing is used to study the processes of memory, a central cognitive component in modern learning theories. Theories of information processing are a by-product of the computer revolution, and they use the language of computers (e.g., sequential processing stages, input, output) to describe the processes of learning and memory. According to a human information-processing perspective, learning occurs in sequential stages, beginning with encoding information from the environment. Encoding of information involves the process by which information from the environment is translated into usable information. The next stage is storage, which involves keeping the information that has been encoded. Stored information builds the "database" of past learning. The final stage in the information-processing approach is retrieval, which involves accessing the stored information so that it can be used to perform a task. Organisms are seen as active participants in the information-processing model. They do not experience the environment passively or simply absorb information, but instead they seek out certain information, and then manipulate, modify, and store it for later use.

Learning theories have often been used to provide a guide for education. Earlier applications were concerned with the use of appropriate rewards and punishment, concerns that mirrored the major tenets of behaviorist theories. More recently, cognitive perspectives have shaped the field of education, and there has been more concern with learning methods that enhance long-term retention and the transfer of information and skills that are learned in schools to novel problems in out-of-school settings. For example, variability in encoding (learning material in different ways, e.g. video and text) produces more durable long-term retention, even though it is a more effortful (and generally less enjoyable) way to learn. In addition, students can become better thinkers when they receive specific instruction in thinking skills–and when the instruction is designed to enhance transfer. Teaching strategies that enhance transfer include spaced practice (viewing material over time versus cramming), using a variety of examples so learners can recognize where a concept is applicable, and practice at retrieval (repeatedly remembering material over time) with informative feedback.

Learning theories are facing new challenges as people grapple with increases in the amount of available information that needs to be learned, rapidly changing technologies that require new types of responses to new problems, and the need to continue learning throughout one's life, even into old age. Contemporary learning theories supported by empirical research offer the promise of enhanced learning and improved thinking–both of which are critical in a rapidly changing and complex world.

See also: Skinner, B. F.; Thorndike, Edward; Watson, John B.

bibliography

Bandura, Albert. 1977. Social Learning Theory. Englewood Cliffs, NJ: Prentice-Hall.

Benjamin, Ludy T. 1988. A History of Psychology: Original Sources and Contemporary Research. New York: McGraw-Hill.

De Winstanley, Patricia A., and Bjork, Robert A. 2002. "Successful Lecturing: Presenting Information in Ways That Engage Effective Processing." In New Directions for Teaching and Learning, ed. Diane F. Halpern and Milton D. Hakel. San Francisco: Jossey-Bass.

Donahoe, John W., and Wessells, Michael G. 1980. Learning, Language, and Memory. New York: Harper and Row.

Halpern, Diane F. 1997. "Sex Differences in Intelligence: Implications for Education." American Psychologist 52 (10):1091–1102.

Mowrer, Robert R., and Klein, Stephen B. 1989. "Contemporary Learning Theories: Pavlovian Conditioning and the Status of Traditional Learning Theory." In Traditional Learning Theory and the Transition to Contemporary Learning Theory, ed. Stephen B. Mowrer and Robert R. Klein. Hillsdale, NJ: Erlbaum.

Ormrod, Jeanne E. 1999. Human Learning, 3rd edition. Upper Saddle River; NJ: Prentice-Hall.

Skinner, B. F. 1938. "A System of Behavior." In A History of Psychology: Original Sources and Contemporary Research, ed. Ludy T. Benjamin. New York: McGraw-Hill.

Thorndike, Edward. L. 1913. "The Laws of Learning in Animals." In A History of Psychology: Original Sources and Contemporary Research, ed. Ludy T. Benjamin. New York: McGraw-Hill.

Tolman, Edward C. 1948. "Cognitive Maps in Rats and Men." In A History of Psychology: Original Sources and Contemporary Research, ed. Ludy T. Benjamin. New York: McGraw-Hill.

Watson, John B. 1913. "Psychology As the Behaviorist Views It." In A History of Psychology: Original Sources and Contemporary Research, ed. Ludy T. Benjamin. New York: McGraw-Hill.

Westen, Drew. 1996. Psychology: Mind, Brain, and Culture. New York: John Wiley and Sons.

Diane F. Halpern

Beth Donaghey

CONSTRUCTIVIST APPROACH

Constructivism is an epistemology, or a theory, used to explain how people know what they know. The basic idea is that problem solving is at the heart of learning, thinking, and development. As people solve problems and discover the consequences of their actions–through reflecting on past and immediate experiences–they construct their own understanding. Learning is thus an active process that requires a change in the learner. This is achieved through the activities the learner engages in, including the consequences of those activities, and through reflection. People only deeply understand what they have constructed.

A constructivist approach to learning and instruction has been proposed as an alternative to the objectivist model, which is implicit in all behaviorist and some cognitive approaches to education. Objectivism sees knowledge as a passive reflection of the external, objective reality. This implies a process of "instruction," ensuring that the learner gets correct information.

History of Constructivism

The psychological roots of constructivism began with the developmental work of Jean Piaget (1896–1980), who developed a theory (the theory of genetic epistemology) that analogized the development of the mind to evolutionary biological development and highlighted the adaptive function of cognition. Piaget proposed four stages in human development: the sensorimotor stage, the preoperational stage, the concrete operational stage, and the formal operational stage. For Piaget, the development of human intellect proceeds through adaptation and organization. Adaptation is a process of assimilation and accommodation, where external events are assimilated into existing understanding, but unfamiliar events, which don't fit with existing knowledge, are accommodated into the mind, thereby changing its organization.

Countless studies have demonstrated–or tried to discredit–Piaget's developmental stages. For example, it has become clear that most adults use formal operations in only a few domains where they have expertise. Nonetheless, Piaget's hypothesis that learning is a transformative rather than a cumulative process is still central. Children do not learn a bit at a time about some issue until it finally comes together as understanding. Instead, they make sense of whatever they know from the very beginning. This understanding is progressively reformed as new knowledge is acquired, especially new knowledge that is incompatible with their previous understanding. This transformative view of learning has been greatly extended by neo-Piagetian research.

The Russian psychologist Lev Vygotsky's (1896–1934) relevance to constructivism derives from his theories about language, thought, and their mediation by society. Vygotsky held the position that the child gradually internalizes external and social activities, including communication, with more competent others. Although social speech is internalized in adulthood (it becomes thinking), Vygotsky contended that it still preserves its intrinsic collaborative character.

In his experiments, Vygotsky studied the difference between the child's reasoning when working independently versus reasoning when working with a more competent person. He devised the notion of the zone of proximal development to reflect on the potential of this difference. Vygotsky's findings suggested that learning environments should involve guided interactions that permit children to reflect on inconsistency and to change their conceptions through communication. Vygotsky's work has since been extended in the situated approach to learning.

Vygotsky and Piaget's theories are often contrasted to each other in terms of individual cognitive constructivism (Piaget) and social constructivism (Vygotsky). Some researchers have tried to develop a synthesis of these approaches, though some, such as Michael Cole and James Wertsch, argue that the individual versus social orientation debate is over-emphasized. To them, the real difference rests on the contrast between the roles of cultural artifacts. For Vygotsky, such artifacts play a central role, but they do not appear in Piaget's theories.

For the American philosopher and educator John Dewey (1859–1952), education depended on action–knowledge and ideas emerge only from a situation in which learners have to draw out experiences that have meaning and importance to them. Dewey argued that human thought is practical problem solving, which proceeds by testing rival hypotheses. These problem-solving experiences occur in a social context, such as a classroom, where students join together in manipulating materials and observing outcomes. Dewey invented the method of progressive education in North America. The Fostering Communities of Learners (FCL) program, devised by Ann Lesley Brown and Joseph Campione, is a current attempt to put Dewey's progressive education theory to work in the classroom.

In summary, Piaget contributed the idea of transformation in learning and development; Vygotsky contributed the idea that learning and development were integrally tied to communicative interactions with others; and Dewey contributed the idea that schools had to bring real world problems into the school curriculum.

Constructivist Processes and Education

There are a number of competing constructivist views in education. Constructivists tend to celebrate complexity and multiple perspectives, though they do share at least a few educational prescriptions.

Prior knowledge. Constructivists believe that prior knowledge impacts the learning process. In trying to solve novel problems, perceptual or conceptual similarities between existing knowledge and a new problem can remind people of what they already know. This is often one's first approach towards solving novel problems. Information not connected with a learner's prior experiences will be quickly forgotten. In short, the learner must actively construct new information into his or her existing mental framework for meaningful learning to occur.

For example, Rosalind Driver has found that children's understanding of a phenomenon (interpretations that fit their experiences and expectations) differ from scientific explanations. This means that students distinguish school science from their "real world" explanations. Studies of adult scientific thinking reveal that many adults hold non-normative scientific explanations, even though they have studied science. This is what the philosopher Alfred Whitehead (1861–1947) referred to as inert knowledge. Asking students what they already know about a topic and what puzzles them affords an opportunity to assess children's prior knowledge and the processes by which they will make sense of phenomena.

Real and authentic problems. Constructivist learning is based on the active participation of learners in problem-solving and critical thinking–given real and authentic problems.

In anchored instruction, for example, as advanced in the work of the Cognition and Technology Group at Vanderbilt University, learners are invited to engage in a fictitious problem occurring in a simulated real-world environment. Rich and realistic video contexts are provided–not only to provide relevant information for solving the problem, but also to create a realistic context. If the students buy in to the proposed problems, they will be engaged in problem solving similar to what the people in the video are engaged in.

There are also many examples of project-based learning in which students take on tasks such as building a vehicle that could cross Antarctica. It is unclear whether these constitute authentic problems–or what students learn from project-based learning.

Constructivist curriculum. A constructively oriented curriculum presents an emerging agenda based on what children know, what they are puzzled by, and the teachers' learning goals. Thus, an important part of a constructivist-oriented curriculum should be the negotiation of meaning. Maggie Lampert, a mathematics teacher, guides students to make sense of mathematics by comparing and resolving discrepancies between what they know and what seems to be implied by new experience.

In constructivist classrooms, curriculum is generally a process of digging deeper and deeper into big ideas, rather than presenting a breadth of coverage. For example, in the Fostering Communities of Learners project where students learn how to learn, in knowledge-building classrooms where students seek to create new knowledge, or in Howard Gardner's classrooms where the focus is on learning for deep understanding, students might study endangered species, island biogeography, or the principles of gravity over several months. As students pursue questions, they derive new and more complex questions to be investigated. Building useful knowledge structures requires effortful and purposeful activity over an extended period.

Cognitive conflict and social context. According to Dewey, "Reflection arises because of the appearance of incompatible factors within an empirical situation. Then opposed responses are provoked which cannot be taken simultaneously in overt action" (p.326). To say this in another way, cognitive conflict or puzzlement is the stimulus for learning, and it determines the organization and nature of what is being learned. Negotiation can also occur between individuals in a classroom. This process involves discussion and attentive listening, making sense of the points of views of others, and comparing personal meanings to the theories of peers. Justifying one position over another and selecting theories that are more viable leads to a better theory. Katerine Bielaczyc and Allan Collins have summarized educational research on learning communities in classrooms where the class goal is to learn together, to appreciate and capitalize on distributed expertise, and to articulate the kinds of cognitive processes needed for learning.

Constructivist assessment. Assessment of student learning is of two types: formative and summative. Formative assessment occurs during learning and provides feedback to the student. It includes evaluations of ongoing portfolios, and demonstrations of work in progress. Student collaboration also provides a form of formative assessment. In FCL, for example, students report to each other periodically on their research. In knowledge-building classrooms, students can read and comment on each other's work with the Knowledge Forum software. Formative assessment rarely occurs in classrooms.

Summative assessment occurs through tests and essays at the end of a unit of study. Summative assessments provide little specific feedback. From a constructivist perspective, formative assessments are more valuable to the learner, but with the recent emphasis in North America on standards, and due to the poor alignment of constructivist approaches and standards, it is very difficult to harmonize formative and summative assessments.

Technology and constructivism. Cognitive research has uncovered successful patterns in tutorial, mentoring, and group discussion interactions. However, typical Internet chat and bulletin-board systems do not support a constructivist approach to learning and instruction. During the 1990s, researchers created tools such as Knowledge Forum, the Knowledge Integration Environment, and Co Vis to more fully address constructivist principles. Each of these tools invites collaboration by structuring the kinds of contributions learners can make, supporting meaningful relationships among those contributions, and guiding students' inquiries. Teachers who use information and communication technologies in their classrooms are more likely to have a constructivist perspective towards learning and instruction. Additionally, sophisticated information and technology communications tools can capture the cognitive processes learners engage in when solving problems. This affords teacher reflection and coaching to aid deeper learning. It also affords teachers the chance to learn from each other.

The teacher's role. The teacher's role in a constructivist classroom isn't so much to lecture at students but to act as an expert learner who can guide students into adopting cognitive strategies such as self testing, articulating understanding, asking probing questions, and reflection. The role of the teacher in constructivist classrooms is to organize information around big ideas that engage the students' interest, to assist students in developing new insights, and to connect them with their previous learning. The activities are student-centered, and students are encouraged to ask their own questions, carry out their own experiments, make their own analogies, and come to their own conclusions. Becoming a constructivist teacher may prove a difficult transformation, however, since most instructors have been prepared for teaching in the traditional, objectivist manner. It "requires a paradigm shift," as well as "the willing abandonment of familiar perspectives and practices and the adoption of new ones" (Brooks and Brooks, p. 25).

A constructivist approach to education is widely accepted by most researchers, though not by all. Carl Bereiter argues that constructivism in schools is usually reduced to project based learning, and John Anderson, Lynn Reder, and Herbert Simon claim that constructivism advocates very inefficient learning and assessment procedures. In any event, the reality is that constructivism is rarely practiced in schools.

See also: Knowledge Building; Piaget, Jean; Vygotsky, Lev.

bibliography

Anderson, John R.; Reder, Lynn; and Simon, Herbert A. 1996. "Situated Learning and Education." Educational Researcher 25 (4): 5–96.

Bereiter, Carl. 2002. Education and Mind for the Knowledge Age. Mahwah, NJ: Erlbaum.

Bereiter, Carl, and Scardamalia, Marlene. 1989. "Intentional Learning As a Goal of Instruction." In Knowing, Learning, and Instruction: Essays in Honor of Robert Glaser, ed. Lauren B. Resnick. Hillsdale NJ: Erlbaum.

Bransford, John D.; Brown, Ann L.; and Cocking, Rodney. 1999. How People Learn: Brain, Mind, Experience, and School. Washington, DC: National Academy Press.

Brooks, Jacqueline G., and Brooks, Martin G. 1993. In Search of Understanding: The Case for Constructivist Classrooms. Alexandria, VA: Association for Supervision and Curriculum Development.

Brown, Ann L., and Campione, Joseph C. 1994. "Guided Discovery in a Community of Learners." In Classroom Lessons: Integrating Cognitive Theory and Classroom Practice, ed. Kate McGilly. Cambridge, MA: MIT Press/Bradford Books.

Brown, John Seely; Collins, Allan; and Duguid, Paul. 1989. "Situated Cognition and the Culture of Learning." Educational Researcher 18 (1):32–42.

Case, Robbie. 1985. Intellectual Development: Birth to Adulthood. Orlando, FL: Academic Press.

Cobb, Paul. 1994. "Where Is the Mind? Constructivist and Sociocultural Perspectives on Mathematical Development." Educational Researcher 23:13–20.

Cognition and Technology Group at Vanderbilt. 1997. The Jasper Project: Lessons in Curriculum, Instruction, Assessment, and Professional Development. Mahwah, NJ: Erlbaum.

Driver, Rosalind. 1989. "Changing Conceptions." In Adolescent Development and School Science, ed. Philip Adey. London: Falmer.

Gardner, Howard. 1999. The Disciplined Mind: What All Students Should Understand. New York: Simon and Schuster.

Johnson-Laird, Philip N. 1983. Mental Models. Cambridge, MA: Harvard University Press.

Lampert, Magdeleine. 1986. "Knowing, Doing, and Teaching Multiplication." Cognition and Instruction 3:305–342.

Lave, Jean, and Wenger, Etienne. 1991. Situated Learning: Legitimate Peripheral Participation. New York: Cambridge University Press.

Piaget, Jean. 1952. The Origins of Intelligence in Children, trans. Margaret Cook. New York: International Universities Press.

Piaget, Jean. 1971. Biology and Knowledge. Chicago: University of Chicago Press.

Ravitz, Jason; Becker, Hank J.; and Wong, Yantien T. 2000. Constructivist-Compatible Beliefs and Practices among U.S. Teachers: Teaching, Learning, and Computing. Center for Research on Information Technology and Organizations, University of California, Irvine, and University of Minnesota.

Scardamalia, Marlene; Bereiter, Carl; and Lamon, Mary. 1994. "Bringing the Classroom into World III." In Classroom Lessons: Integrating Cognitive Theory and Classroom Practice. ed. Kate McGilly. Cambridge, MA: MIT Press.

Siegler, Robert S. 1981. "Developmental Sequences within and between Concepts." Monographs of the Society for Research in Child Development 46 (2).

Vygotsky, Lev S. 1987. Collected Works of L. S. Vygotsky, Vol. 1: Problems of General Psychology, trans. Norris Minick. New York: Plenum.

Wertsch, James V. 1991. Voices of the Mind: A Sociocultural Approach to Mediated Action. Cambridge, MA: Harvard University Press.

Whitehead, Alfred N. 1929. The Aims of Education. New York: Macmillan.

internet resources

Cole, Michael, and Wertsch, James V. 2002. "Beyond the Individual-Social Antimony in Discussions of Piaget and Vygotsky." <www.massey.ac.nz/~alock/virtual/colevyg.htm>.

Dewey, John. 1916. Democracy and Education: An Introduction to the Philosophy of Education. New York: Free Press. <www.ilt.columbia.edu/publications/dewey.html>.

Mary Lamon

SCHEMA THEORY

Schemata are psychological constructs that have been proposed as a form of mental representation for some forms of complex knowledge.

Bartlett's Schema Theory

Schemata were initially introduced into psychology and education through the work of the British psychologist Sir Frederic Bartlett (1886–1969). In carrying out a series of studies on the recall of Native American folktales, Bartlett noticed that many of the recalls were not accurate, but involved the replacement of unfamiliar information with something more familiar. They also included many inferences that went beyond the information given in the original text. In order to account for these findings, Bartlett proposed that people have schemata, or unconscious mental structures, that represent an individual's generic knowledge about the world. It is through schemata that old knowledge influences new information.

For example, one of Bartlett's participants read the phrase "something black came out of his mouth" and later recalled it as "he foamed at the mouth." This finding could be accounted for by assuming that the input information was not consistent with any schema held by the participant, and so the original information was reconstructed in a form that was consistent with one of the participant's schemata. The schema construct was developed during the period when psychology was strongly influenced by behaviorist and associationistic approaches; because the schema construct was not compatible with these worldviews, it eventually faded from view.

Minsky's Frame Theory

In the 1970s, however, the schema construct was reintroduced into psychology though the work of the computer scientist Marvin Minsky. Minsky was attempting to develop machines that would display human-like abilities (e.g., to perceive and understand the world). In the course of trying to solve these difficult problems, he came across Bartlett's work. Minsky concluded that humans were using their stored knowledge about the world to carry out many of the processes that he was trying to emulate by machine, and he therefore needed to provide his machines with this type of knowledge if they were ever to achieve human-like abilities. Minsky developed the frame construct as a way to represent knowledge in machines. Minsky's frame proposal can be seen as essentially an elaboration and specification of the schema construct. He conceived of the frame knowledge as interacting with new specific information coming from the world. He proposed that fixed generic information be represented as a frame comprised of slots that accept a certain range of values. If the world did not provide a specific value for a particular slot, then it could be filled by a default value.

For example, consider the representation of a generic (typical) elementary school classroom. The frame for such a classroom includes certain information, such as that the room has walls, a ceiling, lights, and a door. The door can be thought of as a slot which accepts values such as wood door or metal door, but does not accept a value such as a door made of jello. If a person or a machine is trying to represent a particular elementary school classroom, the person or machine instantiates the generic frame with specific information from the particular classroom (e.g., it has a window on one wall, and the door is wooden with a small glass panel). If, for some reason, one does not actually observe the lights in the classroom, one can fill the lighting slot with the default assumption that they are fluorescent lights. This proposal gives a good account of a wide range of phenomena. It explains, for example, why one would be very surprised to walk into an elementary classroom and find that it did not have a ceiling, and it accounts for the fact that someone might recall that a certain classroom had fluorescent lights when it did not.

Modern Schema Theory

Minsky's work in computer science had a strong and immediate impact on psychology and education. In 1980 the cognitive psychologist David Rumelhart elaborated on Minsky's ideas and turned them into an explicitly psychological theory of the mental representation of complex knowledge. Roger Schank and Robert Abelson developed the script construct to deal with generic knowledge of sequences of actions. Schema theory provided explanations for many experiments already in the literature, and led to a very wide variety of new empirical studies. Providing a relevant schema improved comprehension and recall of opaquely written passages, and strong schemata were shown to lead to high rates of inferential errors in recall.

Broad versus Narrow Use of Schema

In retrospect, it is clear that there has been an ambiguity in schema theory between a narrow use and a broad use of the term schema. For example, in Rumelhart's classic 1980 paper, he defined a schema as "a data structure for representing the generic concepts stored in memory" (p. 34). Yet he went on to state that "there are schemata representing our knowledge about all concepts: those underlying objects, situations, events, sequences of events, actions and sequences of actions" (p. 34). Thus, schemata are frequently defined as the form of mental representation for generic knowledge, but are then used as the term for the representation of all knowledge.

There are severe problems with the use of the term schema to refer to all forms of complex knowledge. First, there is no need for a new technical term, since the ordinary term knowledge has this meaning. In addition, if schema theory is used to account for all knowledge, then it fails. A number of writers have pointed out that schema theory, as presently developed, cannot deal with those forms of knowledge that do not involve old generic information. Thus, schema theory provides an account for the knowledge in long-term memory that the state of Oklahoma is directly above the state of Texas. However, schema theory does not provide an account of the new representation one develops of a town as one travels through it for the first time.

Therefore it seems best to use the term schema in the narrower usage, as the form of mental representation used for generic knowledge. However, if one adopts the narrower usage one has to accept that schemata are only the appropriate representations for a subset of knowledge and that other forms of mental representation are needed for other forms of knowledge. For example, mental models are needed to represent specific nonschematic aspects of knowledge, such as the layout of an unfamiliar town, while naive theories or causal mental models are needed to represent knowledge of causal/mechanical phenomena.

Schema Theory in Education

Richard Anderson, an educational psychologist, played an important role in introducing schema theory to the educational community. In a 1977 paper Anderson pointed out that schemata provided a form of representation for complex knowledge and that the construct, for the first time, provided a principled account of how old knowledge might influence the acquisition of new knowledge. Schema theory was immediately applied to understanding the reading process, where it served as an important counterweight to purely bottom-up approaches to reading. The schema-theory approaches to reading emphasize that reading involves both the bottom-up information from the perceived letters coming into the eye and the use of top-down knowledge to construct a meaningful representation of the content of the text.

Broad versus Narrow Use of Schema in Education

The problem with the broad and narrow use of the term schema surfaced in education just as it had in cognitive psychology. For example, in Anderson's classic 1977 paper on schemata in education, he clearly takes the broad view. He attacks the narrow view and says that it is impossible "that people have stored a schema for every conceivable scene, event sequence, and message" (p. 421), and that "an adequate theory must explain how people cope with novelty" (p. 421). However in a paper written at roughly the same time (1978), Anderson states that "a schema represents generic knowledge" (p. 67), and he adopts the narrow view systematically throughout the paper. In a 1991 paper on terminology in education, Patricia Alexander, Diane Schallert, and Victoria Hare note that the systematic ambiguity between the narrow and broad views has made it very difficult to interpret a given writer's use of the term schema in the education literature.

Instructional Implications of Schema Theory

A number of writers have derived instructional proposals from schema theory. They have suggested that relevant knowledge should be activated before reading; that teachers should try to provide prerequisite knowledge; and that more attention should be given to teaching higher-order comprehension processes. Many of these proposals are not novel, but schema theory appears to provide a theoretical and empirical basis for instructional practices that some experienced teachers were already carrying out.

Impact of Schema Theory on Education

Schema theory has provided education with a way to think about the representation of some forms of complex knowledge. It has focused attention on the role old knowledge plays in acquiring new knowledge, and has emphasized the role of top-down, reader-based influences in the reading process.

See also: Learning, subentry on Causal Reasoning; Literacy, subentry on Narrative Comprehension and Production; Reading, subentries on Comprehension, Content Areas.

bibliography

Adams, Marilyn J., and Collins, Allan. 1979. "A Schema-Theoretic View of Reading." In New Directions in Discourse Processing, Vol. 2: Advances in Discourse Processes, ed. Roy O. Freedle. Norwood, NJ: Ablex.

Alexander, Patricia A.; Schallert, Diane L.; and Hare, Victoria C. 1991. "Coming to Terms: How Researchers in Learning and Literacy Talk about Knowledge." Review of Educational Research 61:315–343.

Anderson, Richard C. 1977. "The Notion of Schemata and the Educational Enterprise: General Discussion of the Conference." In Schooling and the Acquisition of Knowledge, ed. Richard C. Anderson, Rand J. Spiro, and William E. Montague. Hillsdale, NJ: Erlbaum.

Anderson, Richard C. 1978. "Schema-Directed Processes in Language Comprehension." In Cognitive Psychology and Instruction, ed. Alan M. Lesgold, James W. Pellegrino, Sipke D. Fokkema, and Robert Glaser. New York: Plenum.

Anderson, Richard C. 1984. "Role of the Reader's Schema in Comprehension, Learning, and Memory." In Learning to Read in American Schools: Basal Readers and Content Texts, ed. Richard C. Anderson, Jean Osborn, and Robert J. Tierney. Hillsdale, NJ: Erlbaum.

Anderson, Richard C., and Pearson, P. David. 1984. "A Schema-Theoretic View of Basic Processes in Reading Comprehension." In Handbook of Reading Research, ed. P. David Pearson. New York: Longman.

Bartlett, Frederic C. 1932. Remembering. Cambridge, Eng.: Cambridge University Press.

Bransford, John D., and Johnson, Marcia K. 1973. "Considerations of Some Problems of Comprehension." In Visual Information Processing, ed. William G. Chase. New York: Academic.

Brewer, William F. 1987. "Schemas Versus Mental Models in Human Memory." In Modelling Cognition, ed. Peter Morris. Chichester, Eng.: Wiley.

Brewer, William F. 1999. "Scientific Theories and Naive Theories as Forms of Mental Representation: Psychologism Revived." Science and Education 8:489–505.

Brewer, William F. 2000. "Bartlett's Concept of the Schema and Its Impact on Theories of Knowledge Representation in Contemporary Cognitive Psychology." In Bartlett, Culture and Cognition, ed. Akiko Saito. Hove, Eng.: Psychology Press.

Brewer, William F., and Nakamura, Glenn V. 1984. "The Nature and Functions of Schemas." In Handbook of Social Cognition, Vol. 1, ed. Robert S. Wyer, Jr. and Thomas K. Srull. Hillsdale, NJ: Erlbaum.

Hacker, Charles J. 1980. "From Schema Theory to Classroom Practice." Language Arts 57:866–871.

Johnson-Laird, Philip N. 1983. Mental Models. Cambridge, MA: Harvard University Press.

Minsky, Marvin. 1975. "A Framework for Representing Knowledge." In The Psychology of Computer Vision, ed. Patrick H. Winston. New York: McGraw-Hill.

Rumelhart, David E. 1980. "Schemata: The Building Blocks of Cognition." In Theoretical Issues in Reading Comprehension, ed. Rand J. Spiro, Bertram C. Bruce, and William F. Brewer. Hillsdale, NJ: Erlbaum.

Schank, Roger C., and Abelson, Robert P. 1977. Scripts, Plans, Goals and Understanding. Hillsdale, NJ: Erlbaum.

William F. Brewer

Learning Theory

The development of learning theory

General approaches

Phenomena-centered theories

Current work in traditional areas

BIBLIOGRAPHY

Since its emergence as a relatively distinct topic, learning theory has played a central role in psychology. Historically, many psychologists interested in the scientific understanding of behavior have worked with learning phenomena, while psychologists with major interests in areas other than learning, as well as workers in related disciplines, have considered learning to be a pervasive process that enters into quite diverse aspects of behavior. Widespread interest in learning theory has followed the recognition that the theoretical integration of facts and laws is an integral part of what is meant by scientific understanding and that theory serves useful organizational and conceptual functions. Objections to the theory aspect of learning theory have generally reflected disagreement concerning the schedule of the theorizing relative to the empirical development of the field, rather than questions of the ultimate desirability of theorizing about learning.

At the present time the kinds of activities subsumed under the rubric of learning theory present a rapidly changing and expanding pattern of interests. Because of this situation it is impossible to define or specify learning theory in any simple way. Indeed, neither “learning” nor “theory” is a term that is used with consistent meaning by those active in the area. Commonly, learning has been considered to be a process which results from practice and which is reflected as a more or less permanent change in behavior. In many traditional learning theories, learning has been carefully specified to be some sort of associationist process as distinguished from motivational, maturational, inhibitory, and fatigue processes. While learning is thus defined in some cases, even a cursory survey of those systems called learning theories reveals that they include motivational and inhibitory factors. In most such formulations, with the exception of mathematical theories of learning, consideration of motivational variables greatly overshadows concern with the more narrowly defined learning process itself. Thus, many learning theories are in reality theories of behavior, with the term “learning” more or less limiting the range of behavior included.

Similarly, the word “theory” is used in many ways, with an even greater range of meaning than is the case with “learning.” At one extreme are theories which represent nonspecific verbal systems that better serve the “psychology of discovery” of the theorist than satisfy the basic requirement of theories with respect to the integration of data or generation of testable predictions. In this respect, it should be noted that the present discussion applies the term “theory” to a wide variety of formulations, without requiring that they meet criteria of testability, usefulness, or scope. At the other extreme are very specific uses of the term deriving from its usage in mathematical logic. In more restricted uses of the term, there are theories which represent, in varying degrees of quantitative elaboration, hypotheses about the interrelationships of systems of constructs, such as those of the intervening variable type. Further complicating the picture is the increasing use of the term “model” (Lachman 1960), which has a similar variable meaning.

It is obvious that no simple classification of learning theory is possible, and instead of an attempt to develop an arbitrary classificatory scheme attention will be directed, first, toward the development of learning theory and, second, toward a characterization of present approaches and formulations.

The development of learning theory

In the United States, systems or theories specifically concerned with learning and motivation began to emerge in the late 1930s and early 1940s. Coming from a background of “schools” of psychology, for example, structuralism, functionalism, gestalt psychology, and behaviorism, learning theory took the form of systematic positions organized around individuals who promulgated systems of constructs, principles, and research strategies in attempts to account for varying ranges of learning phenomena. Closely connected with this development were the controversies which arose about the basic nature of learning and reinforcement. These controversies, which came to dominate much of the activity in learning at that time, furthered the establishment and growth of the individualistic systems.

Major systems

The major systematic positions were the subject of Hilgard’s influential book Theories of Learning (1948), the book itself being instrumental in establishing the term “learning theory” in common usage. Among the systems described by Hilgard were Thorndike’s early connectionism, Guthrie’s emphasis on contiguous conditioning as a basic principle of learning, Hull’s attempt to develop a highly rigorous quantitative theory based on data from simple learning situations, and Tolman’s cognitive, gestalt-influenced theory, which stressed “sign-learning.” The contributions of Pavlov and Bekhterev certainly must be listed here also because of their tremendous influence on the development of learning theory and because of the importance of present-day neo-Pavlovian theory in the Soviet Union. [See the biographies of Bekhterevand Pavlov.]

The learning theories of this period were characterized by Spence (1951) as being divided on two major issues: first, the nature of the concepts used to represent the hypothetical changes taking place in learning, and, second, the conditions believed to be necessary for these changes to take place.

Sign-signiftcate versus stimulus–response. With respect to the first of these issues the comparison was between those (for example, Koffka, Köhler, Lewin, Tolman) who considered learning to reflect some kind of a perceptual reorganization or restructuring of the subject’s cognitive field which corresponded to the stimulus relationships present in the environment; and those (for example, Guthrie, Thorndike, Hull) who conceived learning to be a modification of the strength of associations, habits, or response tendencies. The former were called S–S (sign–significate) theorists, the latter S–JR (stimulus–response) theorists. The emphasis was directed, respectively, toward the effects of field conditions and other variables on perceptual organization and the relations between sensory events and toward the factors influencing the strength of associations, whether the associations were represented as empirical functional relationships or defined theoretical constructs. [See the biographies of Guthrie; Hull; Lewin; Thorn-dike; Tolman; Watson.]

Reinforcement versus contiguity. The second division was termed the reinforcement–contiguity issue. Here the distinctions concerned whether or not environmental aftereffects of behavior operated in some manner to change the strength of the learning process. Also involved were issues about the usefulness of special theories of reinforcement that attempted to identify the nature of the reinforcement or the manner in which the learning association was changed. Mention must also be made of two factor theories that generally postulated a classical–instrumental or autonomic–skeletal breakdown in which different kinds of learning were involved. These dual theories, which became increasingly popular, were held at various times by B. F. Skinner, Harold Schlosberg, O. H. Mowrer, and Kenneth Spence, among others. While many variations were proposed, contiguity principles were commonly paired with classical conditioning or with the conditioning of autonomicnervous-system responses, and reinforcement theory was usually paired with instrumental-skeletal responses.

Learning controversies

The learning theories and issues discussed above resulted in a great many disputes and controversies regarding the nature of learning, especially discrimination learning. Absolute and relational views of discrimination learning represented one such issue. The absolute position held that discrimination learning involves the strengthening or weakening of the response of approaching different aspects (discriminanda) of the total stimulus configuration, as a function of reinforcement and nonreinforcement; the relational position viewed discrimination learning as depending upon inherent perceptual-organizing tendencies, with the response always being to certain relational properties inherent in the stimulus configuration. This distinction also appeared in views of the nature of generalization and in analyses of transposition phenomena.

Another important controversy of the period centered on continuity and noncontinuity interpretations of discrimination learning, interpretations that were concerned with the question of whether an animal learns about environmental events which are being differentially reinforced but to which he is not responding differentially. The continuity position’s answer to this question was, Yes; the noncontinuity answer, No. Interest in the problem declined because of the difficulty in testing the alternative positions that developed, although in a modified and less controversial form the general question of attention in discrimination learning remains an active area of interest. Finally, mention should be made of disputes regarding “latent learning,” place (cognitive) versus response learning, and insight versus trial and error learning. [See Learning, article ondiscrimination learning; Perception, articles Onperceptual developmentanddepth perception.]

The shift from major systems

It must be recognized that these positions and controversies occupied the major attention of learning theorists for a relatively long period during the growth of interest in learning phenomena and that much of the research of this time was in the context of these issues. Thus, the shift away from these formulations that began to be evident in the early 1950s marked a distinct change in both the direction and content of learning theory. This transition, which is clearly evident in a comparison of Hilgard’s first (1948) and second (1956) editions of Theories of Learning, was due to a number of factors. Without detracting from the historical importance of these approaches or the recognition of their essential contribution to all aspects of current learning theory, it can be recognized that the problems and limitations of the systematic and controversy-oriented theory of that period were such as to lead to change. As psychology became more sophisticated about applying testability criteria to theories, the demand increased that concepts and constructs (or the systems and models into which they were incorporated) should have empirical reference. It became obvious that many of the positions and controversies that had been the focal points of debate were not formulated in a way that would provide clear-cut empirical predictions. In other words, with some exceptions these were systems at the verbal level that could not be translated into the clear-cut experimental manipulations necessary for unambiguous testing. While adequately representing general approaches and serving certain heuristic functions, many of the systems did not serve a desired function of theories—that of integrating and predicting laws. It was also recognized that one possible reason for their lack of specificity was the range of behavior included. It was found that with the existing state of empirical knowledge, learning, as an area, was much too complex to be adequately handled by these broad approaches.

By and large the systems were concerned with simple learning situations; for example, classical conditioning, instrumental learning, and simple discrimination learning. While many learning psychologists recognized the strategy of building from the simple to the complex, they were not satisfied with the pace, were skeptical of the system–controversy aspect of the activity, or felt that important variables were being neglected. These workers, therefore, applied some of the techniques and concepts to other areas of interest or became involved in different kinds of theorizing. The changes as they have developed have represented a distinct turn toward “smaller” theories that are more closely tied to empirical data and that often deal with a single or closely related group of phenomena. Thus, these “smaller” theories have not been based on the theoretical predictions of a few dominant theorists, instead, they have proliferated as phenomena or areas of investigation have been developed or have caught the interest of investigators. Concurrently, there has come a great increase in the use of the model and in the utilization of mediation process notions in all areas of theory construction.

Current learning theory

Current activity in learning theory cannot be simply classified along orthogonal dimensions, such as type of theorizing employed, type of learning phenomena involved, or experimental situations used. Rather than attempting to develop and justify a complex classificatory system, the following section will use broad categories that are intended only to serve a loose organizing function. Considered first are more general theories that have a relatively close relationship to the older systems; second, those which deal with classes of behavior or specific variables. In addition, theoretical activity concerned with traditional experimental learning situations, for example, classical conditioning, instrumental conditioning, discrimination learning, and verbal learning, is discussed, along with a brief consideration of more complex learning situations. It should be recognized that considerable overlap exists between these divisions and that many individual theories and areas of theoretical activity are omitted.

General approaches

While it is obvious that present-day learning theory is not primarily engaged in the elaboration of the theoretical structures of previous systems, the influence of older formulations is clearly represented in current work, and some theoretical activity has been rather directly derived from the “classical” positions. The latter has been the case more for S–R theory than for S–S approaches. There are several theoretical systems that are closely related to Hullian theory, and, similarly, the relationship of stimulus-sampling models to Guthrie’s position is obvious. On the other hand, the influence of S–S theory is primarily evident in approaches that stress perceptual and cognitive variables, for example, perceptual models of discrimination learning and notions of cue utilization.

Modifications of S–R approaches

Miller. The changes in S–R approaches are exemplified by Miller’s discussion of the “liberalization of S–R theory” (1959), which includes a consideration of the application of S–R concepts to central processes and the role of cybernetic-type feedback systems and attentional mechanisms in behavior. While admitting that postulation of central processes within an S–R framework reduces the difference between S–R and cognitive theory, Miller describes the S–R position as one that tends to apply the same laws to central processes as to peripheral stimuli and responses; this is in contrast to cognitive theory, which is characterized as being less specific about the laws involved. A characteristic of Miller’s work has been his attempt to apply laboratory-developed theories and concepts to complex social-behavior situations, the application of his theory of approach–avoidance conflict behavior to diverse and complex human behavioral situations being a case in point. In a sense this is a “model” approach, since the attempt is to find isomorphism between the systems developed in simple animal learning situations and complex human behavior. This approach is to be contrasted with that which attempts to expand theories dealing with a restricted range of simple phenomena by gradually integrating variables and laws from other behavioral situations. [See Conflict, article onpsychological aspects; Cybernetics.]

Spence. Spence’s theory (e.g., 1956) developed from early collaborative work with Hull. Starting with a quantitative S–R account of discrimination learning, Spence has developed in his later work a system that is more systematic than Hull’s theory and much more closely tied to empirical data. In contrast to Hull’s broader, less empirically based approach, is Spence’s detailed concern with such topics as (1) the fractional anticipatory goal response, which is proposed as the mechanism underlying incentive; (2) the role of frustration in partial reinforcement and extinction; and (3) his theory of emotionally based drive. A major objective of Spence’s theorizing has been to develop formulations that would allow for the derivation of empirical relationships found in a variety of learning situations and that could, with the addition of “composition rules,” extend to more complex learning phenomena. [See Drives, article onphysiological drives.]

Mowrer. Another theorist to be considered in this section is Mowrer. His most recent formulation (1960) assigns a central role to the classical conditioning of implicit responses or emotional states, which are called hope, disappointment, fear, or relief, depending upon the nature of the reinforcer (positive or negative) and the relation of the stimulus to the reinforcer (signaling its presence or imminent onset, or absence or approaching cessation). Mowrer is one theorist who does not follow the trend toward more restricted theorizing; rather, he proposes that his basic explanatory principles will encompass a wide range of human learning phenomena.

Mathematical theories

Perhaps the most rapidly expanding area of learning theorizing is that of mathematical (stochastic) theories of learning. Two principal lines of development have generally been distinguished. Statistical learning theory, or stimulus-sampling theory, has used conceptions of the environmental stimulus situation to obtain learning axioms and theorems about the changes that occur in response probabilities as a consequence of environmental events. Operator models, on the other hand, have been primarily concerned with those properties of response sequences that are a result of various transformation rules; assumptions about outcome effects and response classes appear in the nature of the particular model. Both approaches share similar features, such as the assumptions that the environmental outcomes associated with response alternatives change the distribution of choice probabilities and that probabilistic mechanisms govern response selections. Mathematical representations of learning have been quite successful in handling the data from some learning situations. Often, however, these situations have been specifically arranged to lend themselves to mathematical treatment and do not represent paradigms commonly used by other theorists. Further problems have been the relative difficulty of deciding when a particular formulation is appropriate and the fact that there are often a number of alternative assumptions or models that lead to essentially the same results. While promising advances have been made, the future of this approach will be determined by its success in overcoming obstacles and arriving at transsituational mathematical representations of basic learning processes. [See Models, mathematical; for a survey of this area, see Sternberg 1963.]

Phenomena-centered theories

Turning to theories which tend to deal more with certain kinds of behaviors or classes of variables, brief mention will be made of several areas in which the general shift toward phenomena-centered theorizing is evident.

Curiosity behaviors and reinforcement

One trend that has developed since the 1950s has been the increasing attention directed toward exploratory, manipulatory, and curiosity behaviors; and it is not surprising to find corresponding theoretical formulations which attempt to integrate the data of this area. One such theory is represented by the work of Berlyne (1960), who considers four variables to be of primary importance in stimulus-selection processes: novelty, uncertainty, degree of conflict, and complexity. The organism is presumed to direct attention both by central processes and by exploratory behavior (orienting responses, loco-motor exploration, and investigatory responses) that alters the stimulus field. These variables are integrated with arousal-level concepts and further tied to reinforcement, for example, in that arousal reduction may be reinforcing.[see Attention; Stimulation drives.]

Concern with the nature of the reinforcing event is characteristic of formulations dealing with the effects of novelty, exploratory behavior, curiosity, and similar stimulus variables and response patterns. To a large extent this concern has represented dissatisfaction with the tendency of older theories to expand their motivational and reinforcement notions from a single drive or drive mechanism and with their disposition to concentrate upon a few biogenic drives, for example, hunger. Also contributing to this interest has been the demonstration of the high reinforcing value of visual and manipulatory exploration. This work, in which Harlow has played a major role, has forced learning to attend to a new class of variables in a manner similar to the way in which gestalt psychology focused attention on a previously ignored set of perceptual phenomena. While theory concerned with novelty, curiosity, and similar variables has generally not reached the degree of specificity associated with some other areas of theorizing, it is an active and promising area that will undoubtedly become integrated with theories that presently do not deal with these variables to any great extent.

A similar situation exists with respect to investigations of the orienting reflex. Starting with Pavlov’s original work, the orienting reflex has proved a rich topic for research in the Soviet Union and has been the focus of a great increase of interest in the United States. The orienting reflex, which is considered to be a functional, centrally organized and integrated system of somatic, visceral, and cognitive reactions, is evoked by changes in stimulation or “novel” stimuli. Sokolov, the most prominent worker in this field, has elaborated a neuronal model concerned with the properties of the orienting reflex (1960).

Verbal processes

Of similar interest is the concern with the role of verbal processes in learning. While these processes play a major role in some theories of discrimination learning, interest in verbal processes also serves as a more general framework within which many theoretical formulations are being made. Work in the Soviet Union is particularly noteworthy in this respect. Coming from the separate but related traditions of Pavlov and L. S. Vigotski, Soviet researchers have increasingly been concerned with the second (verbal) signaling system and its relationship to learning. Luria (1961) among others has been quite active in theorizing about the verbal regulation of behavior, especially voluntary movements, with an emphasis on developmental factors both in normal and abnormal children. Note should also be made of the growing interest in relating conceptions of orienting reflex and feedback to theories of the development of voluntary action. [See Concept formation; Learning, article Onverbal learning.]

Punishment

Another area that has seen a large increase in theoretical activity is that concerned with the effects of punishment on behavior. It has become clear that punishment can have a wide variety of facilitatory, inhibitory, or suppressive effects depending upon the behavioral, situational, and punishment parameters involved, and a number of theorists have attempted to integrate these effects into existing theoretical structures or to develop principles which will link the various experimental findings. Thus, some theorists have discussed the conditioning of anticipatory punishment cues or have considered punishment to be a special case of avoidance learning, while others have emphasized the role of fear, the nature of the skeletal responses elicited by the punishment, or the stimulus properties of punishment. [See Learning, article onavoidance learning.]

Developmental psychology

Another increasingly active, area with import for learning theory is developmental psychology. The recent trend in this area has been a de-emphasis of normative, naturalistic observation and an increasing use of the experimental method. Correspondingly, there has been a turning away from the “grand” developmental theories as theories, although their utilization as a source of ideas continues. Thus, the conceptual framework and insightful observations of Piaget have occasioned intense interest in developmental psychology, and considerable effort is underway to translate the system and specific ideas into experimentally testable form. As this sort of experimental activity continues, developmental psychology seems destined to have closer ties to other areas of psychology. Indeed, those working in various content areas have also been moving toward developmental concepts. It appears obvious that learning theory must utilize, include, or become integrated with specific experimentally based developmental theory if it hopes to make significant progress in the future. [See Developmental psychology.]

Neurophysiology

Brief mention should also be made of the current work on the neurophysiological basis of learning. Although learning theory of the past has not emphasized physiological constructs to any great extent, this situation may well change as progress is made in understanding the neural basis of learning. It should also be noted that physiological theorizing has generally taken the form of hypotheses about the nature of the physiological or biochemical mechanisms involved. This is in contrast to learning theory in the United States, which has been much more inclined toward the use of systems involving defined concepts or constructs. Theorizing in both areas has felt the impact of the “model” approach, and some rapprochement may occur because of this. Learning theory in the Soviet Union has been much more closely tied to neurophysiological concepts. [See Learning, article onneurophysiological aspects; Nervous system.]

Other phenomena

Examples of theorizing can also be seen with learning phenomena of more limited scope. Thus, the effects of partial reinforcement in acquisition and extinction have served to trigger the development of” small” theoretical formulations that attempt to isolate the effective parameters in the experimental situation and to derive the effects from more basic learning phenomena, for example, stimulus generalization, or as special cases of more general learning theories. In some cases, empirical findings that have countered common sense expectations or the simple derivations of theory have served as the focal points of theoretical activity.

In these examples the phenomena-centered nature of current learning theory is evident, in contrast to the older formulations which tended to start with general principles or postulates concerning the nature of the learning or reinforcement process.

Current work in traditional areas

Classical conditioning

Contemporary theories concerned with classical conditioning have been summarized by Grings (1963). With some exceptions, for example, Razran’s detailed schema, the primary theoretical work has been directed more toward various aspects of the conditioning process than toward the development of a general explanatory system of classical conditioning per se. Much of the interest in classical conditioning has been in its postulated role in other, presumably more complicated, kinds of behavior; for example, theorizing regarding incentive variables, such as the fractional anticipatory goal response, has made use of classical conditioning processes, or as Lachman (1960) discusses it, classical conditioning provides the model, that is, the inference rules, for fractional anticipatory goal response theory. Similar theorizing has developed with respect to

(1) the consequences of frustration, with frustration being defined either as the blocking of an ongoing response or as the omission of a reward, as in partial reinforcement or extinction; and

(2) behavioral situations involving the use of punishment. Thus, in many situations where events are conceptualized to mediate overt behavior, classical conditioning is postulated to play some role or to serve as an inference model for the mediation theory. It should be noted that this use of conditioning is in the S–R rather than the cognitive tradition. [See Drives, article onphysiological drives; Learning, article onclassical conditioning.]

Soviet work. In the Soviet Union, theorizing about classical conditioning has remained a major interest since the pioneering work of Pavlov (e.g., see Anokhin 1955). The characteristics of Pavlov’s theorizing are well known, and while many of his specific notions regarding physiological structure and function have been abandoned or modified considerably, present-day learning theory in the Soviet Union retains a physiological orientation. The current Soviet emphasis on interoceptive conditioning, semantic conditioning, and the orienting reflex is reviewed in detail by Razran (1961). Especially noteworthy, in the present context, has been the theoretical development coming from Soviet interests in configural conditioning, the role of conditioning in verbal behavior, and the ontogenetic implications of their work.

Instrumental conditioning

Theorizing involving instrumental conditioning has taken several forms. The effects of various parameters upon instrumental learning have been of interest to theorists who have attempted to integrate empirical relationships into a more comprehensive theory, or who have tried to use the laws obtained in these simple situations to develop formulations which would make it possible to derive the data previously obtained from more complicated selective-learning paradigms. The relative simplicity of instrumental conditioning has been attractive to those who have found the more complicated situations difficult to analyze in a precise manner. Phenomena-centered theorizing is quite evident here, as in other behavioral situations. To mention only two such efforts: certain partial reinforcement effects in acquisition and extinction have been of theoretical interest, and Abram Amsel’s analysis (1962) of frustrative nonreward effects has been based on data from instrumental conditioning. [See Learning, article oninstrumental learning.]

Avoidance learning. Perhaps the greatest amount of theorizing concerning instrumental behavior has taken place with respect to avoidance learning. These theoretical formulations have generally been concerned with the mediating role of anxiety or fear in avoidance behavior and with the reinforcement principles operating in the dual learning processes of (1) fear or anxiety and (2) the instrumental skeletal response. A comprehensive overview of this area is presented by Solomon and Brush (1956). More recent theorizing has been concerned with specific avoidance phenomena, again demonstrating the trend toward more molecular theorizing. [See Learning, article onavoidance learning.]

Selective learning

The original work in selective (discrimination) learning was largely concerned with controversies regarding the nature of learning and reinforcement processes. While some of this type of work is still found, current interest has largely shifted to the various processes—attention al, verbal, etc.—which presumably mediate the learning. A closely related development has been the emphasis on phylogenetic and ontogenetic considerations, in terms of discrimination-learning performance and the relative use of the postulated mediational mechanisms. One of the most important developments in the discrimination-learning area has been the learning-set work of Harlow (1959). This research focused attention on discrimination procedures, demonstrated the relevance of this sort of research for more complex learning (for example, concept formation), and provided behavioral techniques that have proved useful in comparing human and infrahuman learning. Theoretical activity has been concerned with the nature of interfering tendencies or error factors.

A great deal of current activity is concerned with discrimination-learning “transfer” situations. A number of paradigms have been used to (1) compare the learning processes in human and infrahuman organisms, (2) explicate the nature of postulated mediating mechanisms, and (3) examine the mediational processes ontogenetically. Theoretical approaches that should be mentioned here include those of Luria (1961) and Kendler and Kendler (1962), both of which have tended to identify mediational processes with verbal behavior, and that of Zeaman and House (1963), which has developed from work with retarded children and which, although mathematical in nature, emphasizes the importance of attentional responses to stimulus dimensions. These formulations demonstrate several trends in discriminationlearning theory. First, the use of multistage mediational models to account for the data; second, the increasing use of normal and retarded children as subjects; and third, as in the case of Zeaman and House, the emphasis on observing or attentional responses. Other theories proposed for selective learning include the observing–response formulation of Wyckoff (1952) and the analyzer-mechanism approach of N. S. Sutherland (1959). A succinct phrase which describes the basic process of concern in a number of these formulations is “selective attention,” which can be conceived of in terms of stimulus—response relationships and laws or perceptual–cognitive processes. Approaches which attempt the integration of verbal-behavior relationships with discrimination-learning processes are also popular.

Verbal learning

An excellent discussion of the nature of theory in verbal learning is available in a paper by Gough and Jenkins (1963). These authors point out that verbal learning—the “rote” learning of material under laboratory conditions— did not develop from the learning theories of the 1940s but from the work of Ebbinghaus and the functionalist school of psychology. As an area, verbal learning has always been very closely tied to empirical data and methodological considerations, with little in the way of broad systematic theory. The theories that have developed have been concerned with specific verbal learning or retention phenomena and, as Gough and Jenkins point out, often have been called “analyses” rather than “theories.” This lack of broad systematic formulations has led to the development of “small” testable theories, which have been quickly modified to reflect new experimental evidence. A listing of some recent theoretical formulations or analyses gives the flavor of the work. It has been proposed by Underwood and Schulz (1960) that paired-associate verbal learning can best be considered as a two-stage process involving response learning and stimulus-esponse associative stages. A considerable amount of research has demonstrated the usefulness of this conceptualization. Underwood (1957) has demonstrated that the role of proactive interference in laboratory learning is much greater than was previously assumed, an advance that has contributed to the understanding of forgetting and has led to important changes in methodology. Finally, the development of the interference theory of retroactive inhibition has witnessed the introduction of the concepts of differentiation or the discrimination of list membership and unlearning or extinction to account for discrepancies between interference theory and the obtained data. The close interplay between data and theory is apparent. [See Forgetting; Learning, article onverbal learning.]

Complex learning situations

Concept learning, skill learning, and problem solving are areas that have generally been considered to be more complex and harder to handle in terms of theory than those previously discussed. There are several dimensions of this complexity, for example, the ease or difficulty of dealing with discrete units of behavior or a limited number of basic processes and the necessity of considering sequential relationships. Until relatively recently, theorists were reluctant to deal with these situations, as demonstrated by the early discarding of problem-box situations for the simpler classical-conditioning and instrumental-learning procedures. The resurgence of interest in and of theorizing about these more complex areas has led to attempts to extend S–R and cognitive approaches to these phenomena, and, in some cases, it has led to new conceptual frameworks which bear little obvious relationship to traditional learning approaches.

Concept learning. Concept learning has, perhaps, remained closer to conventional learning research than the other areas mentioned. Kendler (1964) has pointed out that various learning models have been applied to concept learning. He lists S—R conceptions, operant conditioning, clustering, Piaget’s methods of investigation, computer simulation of cognitive processes, and mathematical models as methods and models for the analysis of concept learning. [See Concept formation.]

Skill learning. In comparison to concept learning, theoretical activity regarding skill learning has been more removed from traditional learning theorizing. While issues such as the relative role of specific associations or cognitive sets in skill learning seem closely related to learning theory, the conceptual framework is not. Thus, the language of many models of skill learning is couched in terms of communication models, involving (1) notions of information processing, with subcategories of information translation, transmission, reduction, collation, and storage; (2) control-system models emphasizing feedback systems; and (3) adaptive-system models, with programs and memory systems which allow changes in the characteristics of the model with experience. [See Learning, article onacquisition of skill; see also Fitts 1964.]

Problem solving. Problem solving has long represented an area of controversy with S–R oriented theorists opposing gestalt-cognitive approaches. The S–R approach attempts to use such concepts as mediated generalization, response hierarchies, verbal mediators, and fractional anticipatory goal responses to account for problem-solving phenomena. Gestalt theory, on the other hand, emphasizes perceptual reorganization processes within the problem. One recent formulation or suggested framework, more in the gestalt than in the S–R tradition, has been the ahistorical, relatively rationally derived notions of Miller, Galanter, and Pribram (1960), which involve informational and feedback processes. [See Problem solving.]

The question as to what extent new language and methodological approaches are needed for theorizing in these complex areas remains to be determined. It seems evident, however, that information processing and feedback concepts of some sort will greatly influence learning theorizing in the future.

Leonard E. Ross

[Directly related is the entry Learning, especially the articles onclassical conditioning, instrumental learning, reinforcement. Other relevant material may be found in Drives; Gestalt theory; Motivation.]

BIBLIOGRAPHY

Amsel, Abram 1962 Frustrative Nonreward in Partial Reinforcement and Discrimination Learning: Some Recent History and Theoretical Extension. Psychological Review 69:306–328.

Anokhin, P. K. (1955) 1961 Features of the Afferent Apparatus of the Conditional Reflex and Their Importances for Psychology. Pages 75–103 in N. O’Connor (editor), Recent Soviet Psychology. New York: Liveright.

Berlyne, D. E. 1960 Conflict, Arousal, and Curiosity. New York: McGraw-Hill.

Fitts, Paul M. 1964 Perceptual–Motor Skill Learning. Pages 243–285 in Symposium on the Psychology of Human Learning, University of Michigan, 1962, Categories of Human Learning. New York: Academic Press.

Gough, Philip B.; and Jenkins, James J. 1963 Verbal Learning and Psycholinguistics. Pages 456–474 in Melvin H. Marx (editor), Theories in Contemporary Psychology. New York: Macmillan.

Grestgs, William W. 1963 Classical Conditioning. Pages 495–526 in Melvin H. Marx (editor), Theories in Con-temporary Psychology. New York: Macmillan.

Harlow, Harry F. 1959 Learning Set and Error Factor Theory. Pages 492–537 in Sigmund Koch (editor), Psychology: A Study of a Science. Volume 2: General Systematic Formulations, Learning, and Special Processes. New York: McGraw-Hill.

Hilgard, Ernest R. (1948)1956 Theories of Learning. 2d ed. New York: Appleton.

Kendler, Howard H. 1964 The Concept of the Concept. Pages 211–236 in Symposium on the Psychology of Human Learning, University of Michigan, 1962, Categories of Human Learning. New York: Academic Press.

Kendler, Howard H.; and Kendler, Tracy S. 1962 Vertical and Horizontal Processes in Problem Solving. Psychological Review 69:1–16.

Koch, Sigmund (editor) 1959 Psychology: A Study of a Science. Volume 2: General Systematic Formulations, Learning, and Special Processes. New York: McGraw-Hill.

Lachman, Roy 1960 The Model in Theory Construction. Psychological Review 67:113–129.

Luria, Aleksandr R. 1961 The Role of Speech in the Regulation of Normal and Abnormal Behavior. New York: Liveright.

Miller, George A.; Galanter, E.; and Pribram, K. H. 1960 Plans and the Structure of Behavior. New York: Holt.

Miller, Neal E. 1959 Liberalization of Basic S–R Concepts: Extensions to Conflict Behavior, Motivation and Social Learning. Pages 196–292 in Sigmund Koch (editor), Psychology: A Study of a Science. Volume 2: General Systematic Formulations, Learning, and Special Processes. New York: McGraw-Hill.

Mowrer, Orval H. 1960 Learning Theory and Behavior. New York: Wiley.

Razran, Gregory 1961 The Observable Unconscious and the Inferable Conscious in Current Soviet Psycho-physiology: Interoceptive Conditioning, Semantic Conditioning, and the Orienting Reflex. Psychological Review 68:81–147.

Sokolov, Eugene N. 1960 Neuronal Models and the Orienting Reflex. Pages 187–276 in The Central Nervous System and Behavior: Transactions of the Third Conference. Edited by M. A. B. Brazier. New York: Macy Foundation.

Solomon, Richard L.; and Brush, Elinor S. 1956 Experimentally Derived Conceptions of Anxiety and Aversions. Volume 4, pages 212–306 in Marshall R. Jones (editor), Nebraska Symposium on Motivation. Lincoln: Univ. of Nebraska Press.

Spence, Kenneth W. 1951 Theoretical Interpretations of Learning. Pages 690–729 in Stanley S. Stevens (editor), Handbook of Experimental Psychology. New York: Wiley.

Spence, Kenneth W. 1956 Behavior Theory and Conditioning. New Haven: Yale Univ. Press.

Sternberg, Saul 1963 Stochastic Learning Theory. Volume 2, pages 1–120 in R. Duncan Luce et al. (editors), Handbook of Mathematical Psychology. New York and London: Wiley.

Sutherland, N. S. 1959 Stimulus Analysing Mechanisms. Volume 2, pages 575–609 in Teddington, England, National Physical Laboratory, Mechanisation of Thought Processes: Proceedings of a Symposium. London: H.M. Stationery Office.

Underwood, Benton J. 1957 Interference and Forgetting. Psychological Review 64:49–60.

Underwood, Benton J.; and Schulz, Rudolph W. 1960 Meaningfulness and Verbal Learning. Philadelphia: Lippincott.

Wyckoff, L. B. 1952 The Role of Observing Responses in Discrimination Learning. Part 1. Psychological Review 59:431–442.

Zeaman, David; and House, Betty J. 1963 The Role of Attention in Retardate Discrimination Learning. Pages 159–223 in Norman R. Ellis (editor), Handbook of Mental Deficiency. New York: McGraw-Hill.

Learning theory

Definition

Learning is defined as a relatively permanent change in behavior as a result of experience. This definition excludes changes that might occur solely as a result of maturation, injury, or disease. To learn is to adapt. A child might stick his or her finger in a light socket, but not more than once. Sea lions in an aquarium will learn to bark and slap the water if these behaviors prompt people to toss them food. Changes that occur as a result of learning are not always positive. We may acquire bad (maladaptive) habits, as well as good ones. Three basic kinds of learning have been studied extensively by psychologists. These are: classical conditioning, operant conditioning, and observational learning.

Description

Classical conditioning

The pioneer of the study of classical conditioning was Ivan Pavlov. While studying salivation in dogs as part of his research on digestion, Pavlov discovered an interesting phenomenon. Dogs that had been repeatedly given meat in order to induce salivation began to salivate before the presentation of the meat. The sight of the pan containing the meat, or the sound of the experimenter's footsteps coming toward the laboratory was enough to initiate salivation. This was curious. Dogs do not normally salivate to the sound of footsteps, thus they must have acquired this response as a result of experience. In other words, learning had taken place.

Pavlov recognized the potential importance of the dogs' behavior, and subsequently turned his attention to the study of what we now know as conditioned reflexes . By carefully scrutinizing the dogs' behaviors under controlled laboratory conditions, Pavlov discovered and described the principles of classical conditioning. In order to understand its operation, there are a few key terms that need to be explained. An unconditional stimulus refers to a thing or event that triggers a response (change) reflexively or automatically. This response is referred to as an unconditional response. It is automatically produced; no learning is needed for it to occur. A neutral stimulus is a stimulus that elicits no response (or at least not the response being studied). When a neutral stimulus is repeatedly paired with an unconditional stimulus it will produce an effect similar to that of the unconditional stimulus. This mutated neutral stimulus, if you will, is referred to as a conditioned stimulus and the response it produces is called a conditioned response. The conditioned response, unlike the unconditioned response, is learned. Each pairing of an unconditional stimulus with a conditional stimulus is referred to as reinforcement. The pairing strengthens or reinforces the conditioned response. In classical conditioning it is important to remember that the initial stimulus and its response (i.e., the unconditioned stimulus and response) occur naturally; they are instinctual, so to speak.

HOW CLASSICAL CONDITIONING WORKS. In the first stage, the unconditioned (natural) response to an unconditioned stimulus occurs automatically. It is a natural, reflexive reaction. For example, eating meat will make a dog salivate to aid in digestion. In the second stage, a neutral stimulus is paired with the natural or unconditioned stimulus. Using our example of the dog and meat, suppose we ring a bell just before the meat is given to the dog. If we do this repeatedly the bell alone will cause the dog to salivate and this represents the third stage of classical conditioning. In other words the conditioned stimulus now produces a conditioned response. This response was not present before the conditioning process (or learning) took place. Conditioning occurs most quickly and effectively when the conditioned stimulus immediately precedes the unconditioned stimulus.

Because of classical conditioning, certain events can produce unwanted distress for reasons that are largely unrelated to the event itself. Young children, for example, often become fearful during their first visit to a barber. Barbers often wear white smocks, similar to those worn by doctors. There are also numerous metallic instruments (scissors, razors) in plain sight in the barbershop. Unpleasant experiences at the doctor's office (e.g., an injection) could become associated with accompanying stimuli (the doctor's white coat, silver instruments) in such a way that similar stimuli (in other settings) could trigger an anxiety response. Some children's barbers make a point of wearing colored (as opposed to white) jackets, and take pains to reduce any similarities between their work areas and doctors' examining rooms.

Viewpoints

On the basis of his research, Pavlov assumed that the basic associations established through classical conditioning were universal. In other words, he believed that all animals would show conditioning, and that any natural response could be conditioned to any and all neutral stimuli. More recent research has shown that there are restrictions on the kinds of associations that are amenable to conditioning. For example when tastes, sounds, and visual stimuli were used as conditioned stimuli prior to being given a nausea-inducing drink, rats very quickly learned to associate taste with illness, and forever after avoided similar tasting food. This happened even if the nausea occurred several hours after the ingestion. Moreover, neither the visual nor the auditory stimuli created aversion responses. Apparently all animals, including humans, are biologically prepared to learn some associations rather than others. It is as if nature prepares each species to learn what is best suited to its survival.

Operant conditioning

If the sole mechanism of learning were classical conditioning only a very limited number of responses could be learned. A dog may learn to salivate at the sound of a bell but how are new, voluntary responses learned? How does the animal learn to operate on its environment?

Operant conditioning provides some insight. In classical conditioning the animal is relatively passive. In operant conditioning the animal is an active part of its environment. It operates on the environment. Two pioneers of this approach are Edward L. Thorndike (1874-1949) and B. F. Skinner (1904-1990). At about the same time that Pavlov was performing his experiments with dogs, Thorndike began experimenting with cats. He devised a box from which a cat could escape only if it performed a particular action. For example, the cat would have to press a lever, which would, in turn, cause a rope to pull a bolt from the door and thus allow it to escape. Through trial-and-error the cat would eventually escape from the box. Thorndike noticed that over successive trials, it took progressively less and less time for the cat to solve its problem. Thorndike reasoned that the gratifying experience of being released from the box caused the correct response (pressing the lever) to occur more rapidly on the subsequent trials.

Skinner's research extended and elaborated this simple fact of life: behavior that is rewarded is more likely to recur.

Much of Skinner's research utilized laboratory rats and pigeons. He designed the now famous Skinner Box—a soundproof chamber with a bar or key, which, if pressed or pecked, would dispense a reward of food or water. Once the rat was placed into the box, the experimenter had total control over its environment. The equipment could be programmed to deliver positive or negative reinforcement. For example, the box could be rigged with a lever that, when pressed, turned off a mild electric shock (negative reinforcement). A negative reinforcer is one that strengthens a response by removing an aversive or unpleasant stimulus.

Before a response can be reinforced, it must first occur. Suppose you wanted to teach a dog to climb a ladder. Because this action has no probability of occurring spontaneously, you would wait forever for it to occur so that it could be reinforced. What to do? The solution is to use a procedure known as shaping. When we shape a behavior, we define some ultimate target behavior and then reinforce all actions that are even remotely related to the target behavior. Thus the dog might receive a reward for placing a paw on the bottom rung of the ladder. The trainer then requires responses that are more and more similar to the final, desired response. These responses that are rewarded on the way to the final target behavior are called successive approximations. With shaping (and patience) various animals can be taught to produce extraordinary sequences of behaviors. There are bears in the Russian circus that drive motorcycles. Seeing eye dogs act as the "eyes" for the blind, and can also be taught to assist people with spinal cord injuries by turning on light switches or opening doors. The basic principles of operant conditioning have important practical implications. These principles are at the heart of behavior modification therapy—a treatment approach that has demonstrated some impressive successes in schools, prisons, mental hospitals, and rehabilitation wards.

Observational learning

While classical conditioning and reinforcement principles are powerful and ubiquitous determinants of behavior, they do not tell the whole story, especially when it comes to human learning. We do not always learn through direct experience. Indeed, we wouldn't survive for very long if we could not learn from watching others. Observational learning plays a role in almost every aspect of our activities, from learning how to hold a fork, drive a car, smoke a cigarette, or have sex. Observational learning occurs in fish, birds, and mammals too. For example, if given a choice, rats will prefer to eat food that they have seen other rats choose. Research has demonstrated that children imitate their parents' food aversions. After the first few months of The Simpsons television show, many young girls across the country began expressing an interest in playing the baritone saxophone—Lisa Simpson's instrument of choice.

The observational learning perspective emphasizes that what is learned is 'knowledge' about behavior, in addition to the behavior itself. Role models can be quite influential. If you want to encourage a child to read, read to them, surround him or her with books and with people who read them. Not surprisingly, modeling effects cut both ways. Antisocial role models can cultivate negative patterns of behavior in the observer. Children who grow up in households where wife abuse is common are "learning" that physical assaults and intimidation are effective ways of controlling others. Models are most likely to be imitated when they have status, when their actions are rewarded, when the modeled behaviors are in the observer's repertoire, and when the observer is motivated to emulate the model. While it is disheartening to realize how easily antisocial behaviors can be acquired, the overall legacy from learning theories is one of hope. What is learnable is also (potentially) teachable. This fact inspires parents, teachers and therapists. And what is learned can also be unlearned. No matter how distressed we may feel, we are not stuck forever with our current state. Humans are remarkably capable of change through learning.

Resources

BOOKS

Barone, D., Maddux, J., & Snyder, C. R. Social cognitive psychology: History and current domains. New York: Plenum Press, 1997.

Chance, Paul. Learning and Behavior. Pacific Grove: Brooks/Cole, 1999.

Geller, E. S. The psychology of safety: How to improve behaviors and attitudes on the job. Radnor, PA: Chilton Book Co., 1996.

PERIODICALS

Steinmetz, J. E. "A renewed interest in human classical conditioning." Psychological Science 10 (1999): 24-25.

Timothy E. Moore

Learning Theory

Definition

Learning is defined as a relatively permanent change in behavior as a result of experience. This definition excludes changes that might occur solely as a result of maturation, injury, or disease. To learn is to adapt. A child might stick his or her finger in a light socket, but not more than once. Sea lions in an aquarium will learn to bark and slap the water if these behaviors prompt people to toss them food. Changes that occur as a result of learning are not always positive. We may acquire bad (maladaptive) habits, as well as good ones. Three basic kinds of learning have been studied extensively by psychologists. These are: classical conditioning, operant conditioning, and observational learning.

Description

Classical conditioning

The pioneer of the study of classical conditioning was Ivan Pavlov. While studying salivation in dogs as part of his research on digestion, Pavlov discovered an interesting phenomenon. Dogs that had been repeatedly given meat in order to induce salivation began to salivate before the presentation of the meat. The sight of the pan containing the meat, or the sound of the experimenter's footsteps coming toward the laboratory was enough to initiate salivation. This was curious. Dogs do not normally salivate to the sound of footsteps, thus they must have acquired this response as a result of experience. In other words, learning had taken place.

Pavlov recognized the potential importance of the dogs' behavior, and subsequently turned his attention to the study of what we now know as conditioned reflexes. By carefully scrutinizing the dogs' behaviors under controlled laboratory conditions, Pavlov discovered and described the principles of classical conditioning. In order to understand its operation, there are a few key terms that need to be explained. An unconditional stimulus refers to a thing or event that triggers a response (change) reflexively or automatically. This response is referred to as an unconditional response. It is automatically produced; no learning is needed for it to occur. A neutral stimulus is a stimulus that elicits no response (or at least not the response being studied). When a neutral stimulus is repeatedly paired with an unconditional stimulus it will produce an effect similar to that of the unconditional stimulus. This mutated neutral stimulus, if you will, is referred to as a conditioned stimulus and the response it produces is called a conditioned response. The conditioned response, unlike the unconditioned response, is learned. Each pairing of an unconditional stimulus with a conditional stimulus is referred to as reinforcement. The pairing strengthens or reinforces the conditioned response. In classical conditioning it is important to remember that the initial stimulus and its response (i.e., the unconditioned stimulus and response) occur naturally; they are instinctual, so to speak.

HOW CLASSICAL CONDITIONING WORKS. In the first stage, the unconditioned (natural) response to an unconditioned stimulus occurs automatically. It is a natural, reflexive reaction. For example, eating meat will make a dog salivate to aid in digestion. In the second stage, a neutral stimulus is paired with the natural or unconditioned stimulus. Using our example of the dog and meat, suppose we ring a bell just before the meat is given to the dog. If we do this repeatedly the bell alone will cause the dog to salivate and this represents the third stage of classical conditioning. In other words the conditioned stimulus now produces a conditioned response. This response was not present before the conditioning process (or learning) took place. Conditioning occurs most quickly and effectively when the conditioned stimulus immediately precedes the unconditioned stimulus.

Because of classical conditioning, certain events can produce unwanted distress for reasons that are largely unrelated to the event itself. Young children, for example, often become fearful during their first visit to a barber. Barbers often wear white smocks, similar to those worn by doctors. There are also numerous metallic instruments (scissors, razors) in plain sight in the barbershop. Unpleasant experiences at the doctor's office (e.g., an injection) could become associated with accompanying stimuli (the doctor's white coat, silver instruments) in such a way that similar stimuli (in other settings) could trigger an anxiety response. Some children's barbers make a point of wearing colored (as opposed to white) jackets, and take pains to reduce any similarities between their work areas and doctors' examining rooms.

Viewpoints

On the basis of his research, Pavlov assumed that the basic associations established through classical conditioning were universal. In other words, he believed that all animals would show conditioning, and that any natural response could be conditioned to any and all neutral stimuli. More recent research has shown that there are restrictions on the kinds of associations that are amenable to conditioning. For example when tastes, sounds, and visual stimuli were used as conditioned stimuli prior to being given a nausea-inducing drink, rats very quickly learned to associate taste with illness, and forever after avoided similar tasting food. This happened even if the nausea occurred several hours after the ingestion. Moreover, neither the visual nor the auditory stimuli created aversion responses. Apparently all animals, including humans, are biologically prepared to learn some associations rather than others. It is as if nature prepares each species to learn what is best suited to its survival.

Operant conditioning

If the sole mechanism of learning were classical conditioning only a very limited number of responses could be learned. A dog may learn to salivate at the sound of a bell but how are new, voluntary responses learned? How does the animal learn to operate on its environment?

Operant conditioning provides some insight. In classical conditioning the animal is relatively passive. In operant conditioning the animal is an active part of its environment. It operates on the environment. Two pioneers of this approach are Edward L. Thorndike (1874–1949) and B. F. Skinner (1904–1990). At about the same time that Pavlov was performing his experiments with dogs, Thorndike began experimenting with cats. He devised a box from which a cat could escape only if it performed a particular action. For example, the cat would have to press a lever, which would, in turn, cause a rope to pull a bolt from the door and thus allow it to escape. Through trial-and-error the cat would eventually escape from the box. Thorndike noticed that over successive trials, it took progressively less and less time for the cat to solve its problem. Thorndike reasoned that the gratifying experience of being released from the box caused the correct response (pressing the lever) to occur more rapidly on the subsequent trials.

Skinner's research extended and elaborated this simple fact of life: behavior that is rewarded is more likely to recur.

Much of Skinner's research utilized laboratory rats and pigeons. He designed the now famous Skinner Box—a soundproof chamber with a bar or key, which, if pressed or pecked, would dispense a reward of food or water. Once the rat was placed into the box, the experimenter had total control over its environment. The equipment could be programmed to deliver positive or negative reinforcement. For example, the box could be rigged with a lever that, when pressed, turned off a mild electric shock (negative reinforcement). A negative reinforcer is one that strengthens a response by removing an aversive or unpleasant stimulus.

Before a response can be reinforced, it must first occur. Suppose you wanted to teach a dog to climb a ladder. Because this action has no probability of occurring spontaneously, you would wait forever for it to occur so that it could be reinforced. What to do? The solution is to use a procedure known as shaping. When we shape a behavior, we define some ultimate target behavior and then reinforce all actions that are even remotely related to the target behavior. Thus the dog might receive a reward for placing a paw on the bottom rung of the ladder. The trainer then requires responses that are more and more similar to the final, desired response. These responses that are rewarded on the way to the final target behavior are called successive approximations. With shaping (and patience) various animals can be taught to produce extraordinary sequences of behaviors. There are bears in the Russian circus that drive motorcycles. Seeing eye dogs act as the "eyes" for the blind, and can also be taught to assist people with spinal cord injuries by turning on light switches or opening doors. The basic principles of operant conditioning have important practical implications. These principles are at the heart of behavior modification therapy—a treatment approach that has demonstrated some impressive successes in schools, prisons, mental hospitals, and rehabilitation wards.

Observational learning

While classical conditioning and reinforcement principles are powerful and ubiquitous determinants of behavior, they do not tell the whole story, especially when it comes to human learning. We do not always learn through direct experience. Indeed, we wouldn't survive for very long if we could not learn from watching others. Observational learning plays a role in almost every aspect of our activities, from learning how to hold a fork, drive a car, smoke a cigarette, or have sex. Observational learning occurs in fish, birds, and mammals too. For example, if given a choice, rats will prefer to eat food that they have seen other rats choose. Research has demonstrated that children imitate their parents' food aversions. After the first few months of The Simpsons television show, many young girls across the country began expressing an interest in playing the baritone saxophone—Lisa Simpson's instrument of choice.

The observational learning perspective emphasizes that what is learned is 'knowledge' about behavior, in addition to the behavior itself. Role models can be quite influential. If you want to encourage a child to read, read to them, surround him or her with books and with people who read them. Not surprisingly, modeling effects cut both ways. Antisocial role models can cultivate negative patterns of behavior in the observer. Children who grow up in households where wife abuse is common are "learning" that physical assaults and intimidation are effective ways of controlling others. Models are most likely to be imitated when they have status, when their actions are rewarded, when the modeled behaviors are in the observer's repertoire, and when the observer is motivated to emulate the model. While it is disheartening to realize how easily antisocial behaviors can be acquired, the overall legacy from learning theories is one of hope. What is learnable is also (potentially) teachable. This fact inspires parents, teachers and therapists. And what is learned can also be unlearned. No matter how distressed we may feel, we are not stuck forever with our current state. Humans are remarkably capable of change through learning.

Resources

BOOKS

Barone, D., Maddux, J., & Snyder, C. R. Social cognitive psychology: History and Current Domains. New York: Plenum Press, 1997.

Chance, Paul. Learning and Behavior. Pacific Grove: Brooks/Cole, 1999.

Geller, E. S. The Psychology of Safety: How To Improve Behaviors and Attitudes On The Job. Radnor, PA: Chilton Book Co., 1996.

PERIODICALS

Steinmetz, J. E. "A renewed interest in human classical conditioning." Psychological Science 10 (1999): 24-25.

Learning theory

Theory about how people learn and modify pre-existing thoughts and behavior.

Psychologists have suggested a variety of theories to explain the process of learning. During the first half of the 20th century, American psychologists approached the concept of learning primarily in terms of behaviorist principles that focused on the automatic formation of associations between stimuli and responses. One form of associative learning— classical conditioning—is based on the pairing of two stimuli. Through an association with an unconditioned stimulus (such as meat offered to a dog), a conditioned stimulus (such as a bell) eventually elicits a conditioned response (salivation), even when the unconditioned stimulus is absent. Principles of classical conditioning include the extinction of the response if the conditioned and unconditioned stimuli cease to be paired, and the generalization of the response to stimuli that are similar but not identical to the original ones. In operant conditioning , a response is learned because it leads to a particular consequence (reinforcement ), and it is strengthened each time it is reinforced. Positive reinforcement strengthens a response if it is presented afterwards, while negative reinforcement strengthens it by being withheld. Once a response has been learned, it may be sustained by partial reinforcement, which is provided only after selective responses.

In contrast to theories of classical and operant conditioning , which describe learning in terms of observable behavior, intervening variable theories introduce such elements as memory , motivation , and cognition . Edward Tolman demonstrated in the 1920s that learning can involve knowledge without observable performance. The performance of rats who negotiated the same maze on consecutive days with no reward improved drastically after the introduction of a goal box with food, leading to the conclusion that they had developed "cognitive maps" of the maze earlier, even in the absence of a reward, although this "latent learning" had not been reflected in their observable behavior. Even earlier, Wolfgang Köhler , a founder of the Gestalt school of psychology, had argued for the place of cognition in learning. Based on experiments conducted on the island of Tenerife during World War I, Köhler concluded that insight played a role in problem-solving by chimpanzees. Rather than simply stumbling on solutions through trial and error, the animals he observed seemed to demonstrate a holistic understanding of problems, such as getting hold of fruit that was placed out of reach, by arriving at solutions in a sudden moment of revelation or insight.

The drive-reduction theory of Clark L. Hull and Kenneth W. Spence, which became influential in the 1930s, introduced motivation as an intervening variable in the form of homeostasis, the tendency to maintain equilibrium by adjusting physiological responses. An imbalance creates needs, which in turn create drives. Actions can be seen as attempts to reduce these drives by meeting the associated needs. According to drive-reduction theory, the association of stimulus and response in classical and operant conditioning only results in learning if accompanied by drive reduction.

In recent decades, cognitive theories such as those of social learning theorist Albert Bandura have been influential. Bandura is particularly known for his work on observational learning, also referred to as modeling or imitation . It is common knowledge that children learn by watching their parents, other adults, and their peers. According to Bandura, the extent to which children and adults learn behaviors through imitation is influenced not only by the observed activity itself but also by its consequences. Behavior that is rewarded is more readily imitated than behavior that is punished. Bandura coined the term "vicarious conditioning" for learning based on the observed consequences of others' actions, listing the following requirements for this type of learning: attention to the behavior; retention of what is seen; ability to reproduce the behavior; and motivation. Cognitive approaches such as Bandura's have led to an enhanced understanding of how conditioning works, while conditioning principles have helped researchers better understand certain facets of cognition.

Computers play an important role in current research on learning, both in the areas of computer-assisted learning and in the attempt to further understand the neurological processes involved in learning through the development of computer-based neural networks that can simulate various forms of learning.

Further Reading

Bower, G. H., and E. Hilgard. Theories of Learning. 5th ed. Englewood Cliffs, NJ: Prentice-Hall, 1981.

Grippin, Pauline. Learning Theory and Learning Outcomes: The Connection. Lanham, MD: University Press of America, 1984.

Norman, D.A. Learning and Memory. San Francisco: Freeman, 1982.