Modeling describes the process of learning or acquiring new information, skills, or behavior through observation, rather than through direct experience or trial-and-error efforts. Learning is viewed as a function of observation, rather than direct experience (Holland & Kobasigawa, 1980). When viewed as a process of learning, there are three elements involved in modeling: the model, or the person observed, the observer, the individual who acquires new knowledge or skills as a result of observing the model, and reinforcement, which, in part, determines which behaviors will be repeated. These three factors interact to affect behavior. Reinforcement entails the use of reinforcers (primary or secondary) to increase or decrease the likelihood of future behavior. Through observation of models, a student may learn to hit a baseball (motor skills), how best to interact with members of the opposite sex (social skills), or how to perform double-column addition (intellectual skills). Models can be real—people the student observes directly (e.g. teachers, parents, coaches), or they can be symbolic—characters in books, movies, and television. In either form, real or symbolic, it is difficult to imagine any society in which modeling has not played a crucial role in the transmission of knowledge, skills, and behaviors from one generation to the next.
Bandura and Walters (1963) concluded that the observation of models can result in one of three outcomes: (a) the modeling or observational learning effect, (b) the inhibitory or disinhibitory effect, and (c) the eliciting effect (which has also been referred to, by Holland and Kobasigawa, 1980, as the social facilitation or response facilitation effect). The modeling effect refers to the acquiring of new behavior as a result of observing a model, real or abstract. Learning how to hit a baseball can come from watching the coach directly or from watching a famous baseball player demonstrate the skill on a best-selling instructional video. The inhibitory or disinhibitory effect refers to the strengthening or weakening of behaviors as a result of observing a model. Many students will be inhibited about acting out in class simply by observing a classmate being punished for a particular behavior. Conversely, some students will be disinhibited, or will be more likely to act out, when they observe that same behavior not being punished. The eliciting effect occurs when a previously learned behavior happens more frequently as a result of observing a model being reinforced for the same behavior. Although it is similar in nature to the modeling effect and disinhibitory effect, Bandura (1971) suggests that the eliciting effect is unique for a couple of reasons. He notes:
Response facilitation effects can be distinguished from observational learning and disinhibition by the fact that no new responses are acquired, and disinhibitory processes are not involved because the behavior in question is socially sanctioned and, therefore, is unencumbered by restraints. (p. 656)
Advertisers rely on the eliciting effect to sell their products by trying to convince people that purchasing their special brand of product (e.g. jeans, perfume, car), will make them more attractive, sophisticated, or likeable in the eyes of others.
As has been discussed, modeling, or learning as a function of observation, involves the model, the observer, patterns of reinforcement, and how these factors interact to influence behavior or learning. Attributes typically associated with effective models include power, prestige, competence, and warmth or caring. Models that demonstrate one or more of these characteristics are likely to have a stronger influence on the observer (Bandura, 1986). On the part of the observer, in order for modeling to be effective, there are four processes that must take place: attention, retention, reproduction, and motivation. First, the observer must pay attention. People are more likely to pay attention to models in a position of power (e.g., President of the United States) or prestige (e.g., music or movie star), who demonstrate competence (e.g., recognized expert), or show warmth (e.g., a caring teacher) toward the observer. Second, the observer must be able to retain what has been observed by encoding it in long-term memory. Effective teachers incorporate modeling in lesson plans and activities that facilitate long-term learning of information and skills. Third, the observers must be able to reproduce what has been observed. Not only do they need to possess the physical capacity, but they must also believe that that are capable of reproducing the behavior or task. Lastly, the student must be motivated for modeling to be effective. When a student observes other students in the class being reinforced by the teacher for speaking up during a class discussion on World War II, this may motivate the student to overcome his or her shyness and contribute to future class discussions. At the same time, when a teacher ridicules wrong answers from students, other students are less likely to be motivated to speak up for fear of also being ridiculed if they give the wrong answer.
Much in the same way as it functions in operant conditioning, reinforcement (type and frequency) influences the response patterns of observed behavior in the process of modeling. Rather than having a direct influence, however, such as in operant conditioning, reinforcement in modeling has a more indirect role in the learning of new behavior. When individuals observe behavior being punished or rewarded in others, this may lead to the vicarious reinforcement of that behavior in the individual. According to Bandura and Walters (1963), reinforcement in modeling operates in one of four ways, three at the level of the observer, and one at the level of the model. At the level of observer, there is increased likelihood that an observed behavior will be imitated if: (a) the observer is directly reinforced by the model, such as when a teacher praises a student for correctly doing a math problem just demonstrated on the board; (b) the imitated behavior is reinforced by its own consequences, such as a mother's excitement to the child who says “mommy” for the first time; or (c) the observer experiences vicarious reinforcement, such as the shy student who speaks up more in class after observing the teacher respond positively to other students who have done so. Reinforcement occurs at the level of the model when being imitated becomes reinforcing in itself, such as the father who feels proud because his son's batting performance improves as a result of instruction from the father. The father will be more likely, in this case, to continue with the instruction because the outcome is reinforcing the modeled behavior.
Modeling as a process of learning draws heavily from a variety of theoretical sources, including behaviorism (classical and operant conditioning), social learning and social cognitive theory, information processing theory, and sociocultural theory. In order to understand how characteristics of the model, the observer, and reinforcement interact to affect learning and behavior, it is necessary to understand how the various theories have uniquely contributed to our current understanding of modeling.
In early theories of human learning, namely behaviorism (i.e., classical and operant conditioning), theorists such as Ivan Pavlov (1849–1936), John B. Watson (1878–1958), and B.F. Skinner (1904–1990) used animal experiments to search out and verify explanations for human behavior. In classical conditioning, Pavlov discovered that dogs could be conditioned to respond in a certain way through the pairing of different stimuli in the environment. From this perspective, learning was viewed as a stimulus-response (S-R) relationship. A stimulus (in the environment) could be manipulated to elicit a particular response (in the individual). In classical conditioning, the focus is on how involuntary responses, such as salivating, are elicited as a result of changes in environmental conditions. As such, classical conditioning only describes one way that learning can occur in animals and humans, rather than having practical applications for classroom management. It was not until the later work of Skinner, in which he introduced the notion of reinforcement, that learning theory began to have practical implications for the classroom and student learning.
Lefrancois (2000) writes, “Simply put, Skinner's model of operant conditioning describes learning as an increase in the probability of occurrence of an operant (emitted response) as a function of reinforcement” (p. 123). With operant conditioning, Skinner expanded the behaviorist model of learning from (S-R) to include reinforcement, in which learning was viewed as (S)timulus-(R)esponse-(R)ein-forcement-(R)esponse, in which the increased or decreased likelihood of a behavior was contingent upon the type and frequency of reinforcement used. Types of reinforcement include positive reinforcement, negative reinforcement, and punishment I and II. Frequency of reinforcement refers to schedules of reinforcement, such as continuous or intermittent. Some researchers (e.g., Masia & Chase, 1997) have linked operant conditioning with observational learning by pointing out that reinforcement plays a crucial role in determining the likelihood that an observed behavior will be imitated. Further, Bandura (1977) noted that imitation itself is a class of operants that is strongly influenced by patterns of reinforcement.
Bandura played a crucial role in bridging the gap between behavioral theory, with its focus on direct experience, and social learning theory, in which many believed that much of human learning occurred through the process of socialization. Rather than having to be “conditioned” (classical conditioning) or “shaped” (operant conditioning), Bandura and other early social learning theorists posited that the adults in any society transferred the skills and knowledge of that society from one generation to the next through a socialization process. Miller (1983) notes that it was at this point that learning theory moved strictly from the realm of the laboratory and into the real world as a way to explain human learning.
Miller (1983) also notes that two major shifts occurred in the history of social learning theory. First was the early work by Bandura and others demonstrating that imitation was linked with operant conditioning through reinforcement, or, that observed behavior was more likely to be imitated when it was reinforced in some way. This presented a major shift in learning theory because, for the first time, behavior was not viewed as only being a function of direct experience. The second major shift occurred with the work of Bandura and Walters in the 1960s and 1970s in which they argued that observational learning could occur without demonstrating a particular behavior. With behaviorism's focus on observed and measurable behavior, the assumption was that learning only occurred to the extent that it could be measured. Bandura (1965) referred to the latter as “no-trial learning.” With these shifts came an increasing focus on how models and observers influenced the learning process, especially in Bandura's 1986 model of reciprocal determinism.
As discussed earlier, models can affect behavior in one of three ways, including the modeling effect, the inhibitory or disinhibitory effect, and the eliciting effect. With Ban-dura's reciprocal determinism model of learning, greater attention was paid to how the individual (observer) played a role in the learning process, especially in how cognitive and motivational processes influenced individual perceptions of observed events. Bandura (1986) notes that the greater the cognitive ability and prior knowledge on the part of the individual, the greater the perceptive ability of what is being observed. According to social cognitive theory, self-efficacy and self-regulation are important processes related to modeling in achievement contexts (i.e. school outcomes). Similarly, information processing theorists have clarified how such processes as encoding, retrieval, long- and short-term memory, and metacognition can also influence observational learning (Schunk & Zimmerman, 1996). In both cases the focus is placed on how observers perceive and process the information they are observing, and to a larger degree how capable they will be in reproducing the observed skill or behavior. Bandura (1986) refers to modeling as an “information-processing activity in which information about the structure of behavior and about environmental events is transformed into symbolic representations that serve as guides for action” (p. 51). Bandura suggests that modeling, on the part of the observer, is governed by four processes: attention, retention, production, motivation (see previous discussion on these processes for further detail).
In many ways, Lev Vygotsky's sociocultural theory of intellectual development combines many of the important aspects of modeling in a way that illustrates the importance of observation in the process of learning. Vygotsky hypothesized that larger cultural and social systems played an essential role in the acquisition of language skills, intellectual development, and ultimately in becoming literate in the traditions and knowledge of a greater society (John-Steiner & Mahn, 1996). Without actually using the term modeling, Vygotsky described a process of intellectual development that started at the level of observation and eventually moved to the level of internalization. Many students are familiar with terms such as apprentice and the zone of proximal development, where through observation and reinforcement (i.e., scaffolding), students develop ever more sophisticated views of the world. While not using the exact terms, Vygotsky suggested that the tools of any society, which could be viewed as symbolic models, and teachers, who are examples of real-life models, are essential in helping children internalize and integrate skills and knowledge that are first perceived at the level of observation.
Modeling is one of the most efficient modes of learning of any new skill or knowledge (Bandura, 1986). It is difficult to imagine any society that has not relied on models in one form or another to transmit the most important and basic cultural values, customs and beliefs from one generation to the next. If all of human learning had occurred at the level of direct experience or trial-and-error efforts, human progress would have occurred at a much slower rate. From childhood through adulthood, modeling plays a key role in the acquisition and development of cognitive and metacognitive skills, fine motor skills, interpersonal skills, and later professional skills. Each of these is gained primarily through the process of observation.
Motor skill acquisition and development occur as children observe parents, siblings, and peers interact with their worlds. From the simplest act of learning how to pick up and use a fork to the complex and multifaceted process of driving a car, all of these skills are acquired through the observation of models. Which skills are learned and repeated by the observer will ultimately depend upon the types of reinforcement received, as well as how capable or motivated the observer is to repeat those behaviors.
Learning simple cognitive skills, such as basic arithmetic or reading skills, as well as more complex cognitive skills, such as critical thinking or problem solving, are facilitated when models verbalize their own thought processes as they engage in these activities. Thoughts are thus made observable, and potentially modeled, through overt verbal representation of the model's actions. Modeling both thoughts and actions has several helpful features that contribute to its effectiveness in producing lasting improvements in cognitive skills. Nonverbal modeling gains and holds attention, which is often difficult to sustain by talk alone. It also provides an informative semantic context within which to imbed verbalized rules. Behavioral referents confer meaning on cognitive abstractions. Moreover, verbalized rules and strategies can be reiterated in variant forms as often as needed to impart a cognitive skill without taxing observers' interest by using different exemplars. In addition, the more and varied application can deepen understanding of generative rules.
According to the social cognitive model of learning, the acquisition of metacognitive and self-regulatory skills and competence first develops through social interaction, otherwise known as observational learning (Schunk & Zimmerman, 1996). Schunk and Zimmerman suggest that in developing what they call self-regulatory competence, students need to be given opportunities to practice the various strategies associated with self-regulated learning in order to fully develop and master this set of skills. Mastering these skills is made easier when models provide “guidance, feedback, and social reinforcement during practice.”
Cognitive apprenticeship (Collins, Brown, & Newman, 1989; Collins, Brown, & Holum, 1991) incorporates key aspects of modeling, self-regulation and mastery learning. In cognitive apprenticeship, in which “thinking is made visible,” teachers can utilize or combine various methods (i.e., modeling, coaching, scaffolding, articulation, reflection, and exploration) to help students build on their prior knowledge in a way that allows them to become self-regulated learners. Collins and his colleagues (1991) contend that through modeling, coaching, and scaffolding, which they refer to as the “core” of cognitive apprenticeship, students develop and acquire an integrated set of skills through the processes of “observation and guided practice.”
Cognitive apprenticeship differs from traditional apprenticeship in three important ways. First, in traditional apprenticeships, the process of learning usually involves easily observable tasks. The carpenter learns his trade by following the example of the more experienced craftsman. There is little difficulty learning the “thinking” behind the successful completion of a particular task or process. In cognitive apprenticeships, the model, perhaps a teacher, has the difficult challenge of “making thinking visible,” while usually engaging in an abstract task or process. Further, in cognitive apprenticeships, both the model's and the observer's thinking need to be made explicit. For the model, this is to ensure that the observer understands the how, why, and when of solving a particular problem. For the observer, this is to ensure that he or she receives proper feedback and support (i.e., scaffolding) during the learning process. Second, in traditional apprenticeships, the process of learning usually occurs in authentic settings while engaging in actual tasks. The learning is situated in a context and presents both the model and the observer the opportunity to engage in and understand not only the final product, but also how the final product is achieved. In a cognitive apprenticeship model, such as learning in the classroom, the process of learning occurs at the abstract level. Learning at the abstract level may lead to difficulty with transfer, or the ability to generalize newly acquired skills and knowledge in future activities.
To enhance learning in a cognitive apprenticeship model, Collins, Brown, and Holum (1991) offer a few suggestions for teachers. First, they suggest that teachers offer students a variety of tasks that range from “systematic to diverse.” By presenting a diversity of tasks, teachers challenge students to generalize what they have observed. Second, they encourage teachers to help students reflect on their experiences in ways that help students “articulate the elements that are common across tasks” (p. 41). Lastly, they suggest helping students to understand the relevance of what they learn in order to motivate them to utilize newly acquired skills and knowledge in future endeavors. Clearly, the cognitive apprenticeship model requires that both the model and observer be active members of the learning process.
Models and modeling play an essential role in observational learning. At its core, modeling refers to imitation as a function of observation; however, it is much more than simple mimicry (Bandura, 1986). As a process of learning, modeling draws from various theoretical perspectives, including behaviorism (classical and operant conditioning), social learning and social cognitive theory, sociocultural theory, and information processing theory to explain how the model, the observer, and patterns of reinforcement interact to affect learning and behavior. Contrary to earlier views of learning, modeling assumes that individuals can learn vicariously through the experiences of others. In addition, learning is assumed to occur even in the absence of a direct demonstration of a particular learned skill or behavior. It may simply be a matter of choice on the part of the individual not to perform the newly acquired skill. Models can be either real or abstract, and have been shown to influence behavior in one of three ways: (a) the observational learning or modeling effect, (b) the inhibitory or disinhibitory effect, and (c) the eliciting effect. In order for modeling to be effective, the observer must be able to attend to, retain, reproduce, and be motivated to perform the observed behavior.
Contemporary views of modeling have linked this process of learning with the acquisition of fine and basic motor skills, interpersonal skills, cognitive development, and metacognition and self-regulation. Most contemporary views link aspects of the model, the observer, and reinforcement in a way as to explain new and effective ways of learning. One example of this would be cognitive apprenticeship (Collins et al., 1991), in which teachers, as effective models, make their thinking explicit to help student growth and development. As Schunk and Zimmerman (1996) have noted, when models also provide assistance and guided practice, student learning is enhanced.
Bandura. A. (1965a). Vicarious processes: A case of no-trial learning. In L. Berkowitz (Ed.), Advances in Experimental Social Psychology, II (pp. 1–55). New York: Academic Press.
Bandura, A. (1971). Psychotherapy based upon modeling principles. In A. E. Bergin & S. L. Garfield (Eds.), Handbook of psychotherapy and behavior change: An empirical analysis (pp. 653–708). New York: Wiley.
Bandura, A. (1977). Social learning theory. Englewood Cliffs, NJ: Prentice-Hall.
Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice-Hall.
Bandura, A., & Walters, R. (1963). Social learning and personality development. New York: Holt, Rinehart, & Winston.
Collins, A., Brown, J. S., & Holum, A. (1991). Cognitive apprenticeship: Making thinking visible. American Educator, 6(11), 38–46.
Collins, A., Brown, J. S., & Newman, S. E. (1989). Cognitive apprenticeship: Teaching the crafts of reading, writing, and mathematics. In L. B. Resnick (Ed.), Knowing, learning, and instruction (pp. 453–494). Hillsdale, NJ: Erlbaum.
Duncan, S. L. S. (1996). Cognitive apprenticeship in classroom instruction: Implications for industrial and technical teacher education. Journal of Industrial Teacher Education, 33, 66–86.
Holland, C. J., & Kobasigawa, A. (1980). Observational learning: Bandura. In G. M. Gazda & R. J. Corsini (Eds.), Theories of learning: A comparative approach (pp. 370–403). Itasca, IL: F. E. Peacock.
John-Steiner, V., & Mahn, H. (1996). Sociocultural contexts for teaching and learning. In D. C. Berliner & R. C. Calfee (Eds.), Handbook of educational psychology (pp. 125–151). New York: Macmillan.
Lefrancois, G. R. (2000). Theories of human learning (4th ed.). Belmont, CA: Wadsworth/Thomson Learning.
Masia, C. L., & Chase, P. N. (1997). Vicarious learning revisited: A contemporary behavior analytic interpretation. Journal of Behavior Therapy & Experimental Psychiatry, 28(1), 41–51.
Miller, P. H. (1983). Theories of developmental psychology. San Francisco: W. H. Freeman.
Schunk, D. H., & Zimmerman, B. J. (1996). Self-regulation and learning. In D. C. Berliner & R. C. Calfee (Eds.), Handbook of educational psychology (pp. 59–78). New York: Macmillan.
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