essay on observational learning

Observational Learning In Psychology

Charlotte Nickerson

Research Assistant at Harvard University

Undergraduate at Harvard University

Charlotte Nickerson is a student at Harvard University obsessed with the intersection of mental health, productivity, and design.

Learn about our Editorial Process

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

On This Page:

Key Takeaways

• Observational learning involves acquiring skills or new or changed behaviors through watching the behavior of others.
• The person or actor performing the action that the observational learner replicates is called a model.
• The educational psychologist Albert Bandura was the first to recognize observational learning through his Bobo Doll experiment.
• Observational learning consists of attentive, retentive, reproductive, and motivational processes.
• Observational learning pervades how children, as well as adults, learn to interact with and behave in the world.

Observational learning, otherwise known as vicarious learning, is the acquisition of information, skills, or behavior through watching others perform, either directly or through another medium, such as video.

Those who do experiments on animals alternatively define observational learning as the conditioning of an animal to perform an act that it observes in a member of the same or a different species.

For example, a mockingbird could learn to imitate the song patterns of other kinds of birds.

The Canadian-American psychologist Albert Bandura was one of the first to recognize the phenomenon of observational learning (Bandura, 1985).

His theory, social learning theory, stresses the importance of observation and modeling of behaviors, attitudes, and the emotional reactions of others.

Stages of Observational Learning

Bandura (1985) found that humans, who are social animals, naturally gravitate toward observational learning. For example, children may watch their family members and mimic their behaviors.

In observational learning, people learn by watching others and then imitating or modeling what they do or say. Thus, the individuals or objects performing the imitated behavior are called models (Bandura, 1985).

Even infants may start imitating the mouth movements and facial expressions of the adults around them.

There are four processes that Bandura’s research identified as influencing observational learning: attention, retention, reproduction, and motivation (Debell, 2021).

• In order to learn, observers must pay attention to their environment. The attention levels of a learned person can vary based on the characteristics of the model and the environment where they are learning the behavior.
• These variables can include how similar the model is to the observer and the observer’s current mood. Humans, Bandura (1985) proposed, are likely to pay attention to the behaviors of models that are high-status, talented, intelligent, or similar to the learner in some way.
• For example, someone seeking to climb the corporate ladder may observe the behavior of their managers and the vice presidents of their company and try to mimic their behavior (Debell, 2021).
• Attention in itself, however, is not enough to learn a new behavior. Observers Must also retain or remember the behavior at a later time. In order to increase the chances of retention, the observer can structure the information in a way that is easy to remember.
• This could involve using a mnemonic device or a daily learning habit, such as spaced repetition. In the end, however, the behavior must be easily remembered so that the action can later be performed by the learner with little or no effort (Debell, 2021).

Motor Reproduction

• After retention comes the ability to actually perform a behavior in real life, often, producing a new behavior can require hours of practice in order to obtain the necessary skills to do so.
• Thus, the process of reproduction is one that can potentially take years to craft and perfect (Debell, 2021).
• Finally, all learning requires, to some extent, personal motivation. Thus, in observational learning, an observer must be motivated to produce the desired behavior.
• This motivation can be either intrinsic or extrinsic to the observer. In the latter case, motivation comes in the form of rewards and punishments.
• For example, the extrinsic motivation of someone seeking to climb the corporate ladder could include the incentive of earning a high salary and more autonomy at work (Debell, 2021).

The Bobo Doll Experiment

Bandura’s Bobo Doll experiment is one classic in the field of observational learning. In all, this experiment showed that children could and would mimic violent behaviors simply by observing others.

In these experiments, Bandura (1985) and his researchers showed children a video where a model would act aggressively toward an inflatable doll by hitting, punching, kicking, and verbally assaulting the doll.

The end of the video had three different outcomes. Either the model was punished for their behavior, rewarded for it, or there were no consequences.

After watching this behavior, the researchers gave the children a Bobo doll identical to the one in the video.

The researchers found that children were more likely to mimic violent behaviors when they observed the model receiving a reward or when no consequences occurred.

Alternatively, children who observed the model being punished for their violence showed less violence toward the doll (Debell, 2021).

Observational Learning Examples

There are numerous examples of observational learning in everyday life for people of all ages.

Nonetheless, observational learning is especially prevalent in the socialization of children. For example:

• An infant could learn to chew by watching adults chew food.
• After witnessing an older sibling being punished for taking a cookie without permission, the young child does not take cookies without permission.
• A school child may learn to write cursive letters by observing their teacher write them on the board.
• Children may learn to play hide and seek by seeing other children playing the game and being rewarded in the form of entertainment.
• Children may also learn to say swear words after watching other children say swear words and gain social status.
• A child may learn how to drive a car by making appropriate motions after seeing a parent driving.
• A young boy can swing a baseball bat without being explicitly taught how to do it after attending a baseball game. Similarly, a child could learn how to shoot hoops after a basketball game without instruction.
• A child may be able to put on roller skates and stand on them without explicit instruction.
• A student may learn not to cheat by watching another student be punished for doing so
• A child may avoid stepping on ice after seeing another child fall in front of them.

Positive and Negative Outcomes

Bandura concluded that people and animals alike watch and learn and that this learning can have both prosocial and antisocial effects.

Prosocial or positive models can be used to encourage socially acceptable behavior. For example, parents, by reading to their children, can teach their children to read more.

Meanwhile, parents who want their children to eat healthily can in themselves eat healthily and exercise, as well as spend time engaging in physical fitness activities together.

Observational learning argues that children tend to copy what parents do above what they say (Daffin, 2021).

Observational learning has also been used to explain how antisocial behaviors develop. For example, research suggests that observational learning is a reason why many abused children grow up to become abusers themselves (Murrel, Christoff, & Henning, 2007).

Abused children tend to grow up witnessing their parents deal with anger and frustration through violent and aggressive acts, often learning to behave in that manner themselves.

Some studies have also suggested that violent television shows may also have antisocial effects, though this is a controversial claim (Kirsh, 2011).

Observational Learning and Behavioral Modification

Observational learning can be used to change already learned behaviors, both positive and negative.

Bandura asserted that if all behaviors are learned by observing others, and people can model their behavior on that of those around them, then undesirable behaviors can be altered or relearned in the same way.

Banduras suggested showing people a model in a situation that usually causes them some anxiety.

For example, a psychologist may attempt to help someone overcome their fear of getting blood drawn by showing someone using relaxation techniques during a blood draw to stay calm.

By seeing the model interact nicely with the fear-evoking stimulus, the fear should subside. This method of behavioral modification is widely used in clinical, business, and classroom situations (Daffin, 2021).

In the classroom, a teacher may use modeling to demonstrate how to do a math problem for a student. Through a prompt delay, that teacher may then encourage the students to try the problem for themselves.

If the student can solve the problem, no further action is needed; however, if the student struggles, a teacher may use one of four types of prompts — verbal, gestural, modeling, or physical — to assist the student. Similarly, a trainer may show a trainee how to use a computer program to run a register.

As before, the trainer can use prompt delays and prompts to test the level of learning the employee has gained.

Reinforcers can then be delivered through social support after the trainee has successfully completed the task themself (Daffin, 2021).

Observational Learning vs. Operant and Classical Conditioning

Classical conditioning , also known as Pavlovian or respondent conditioning, is a type of learning in which an initially neutral stimulus — the conditioned stimulus — is paired with a stimulus that elicits a reflex response — the unconditioned stimulus.

This results in a learned, or conditioned, response when the conditioned stimulus is present. Perhaps the most famous example of classical conditioning is that of Pavlov’s dogs.

Pavlov conditioned a number of dogs by pairing food with the tone of a bell. After several repetitions, he was able to trigger his dogs to salivate by ringing the bell, even in the absence of food.

Operant conditioning, meanwhile, is a process of learning that takes place by seeing the consequences of behavior. For example, a trainer may teach a dog to do tricks by giving a dog a reward to, say, sit down (Daffin, 2021).

Observational learning extends the effective range of both classical and operant conditioning.

In contrast to classical and operant conditioning, in which learning can only occur through direct experience, observational learning takes place through watching others and then imitating what they do.

While classical and operant conditioning may rely on trial and error alone as a means of changing behavior, observational conditioning creates room for observing a model whose actions someone can replicate.

This can result in a more controlled and ultimately more efficient learning process for all involved (Daffin, 2021).

Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory . Prentice-Hall, Inc.

Bandura, A. (1977). Social learning theory . Englewood Cliffs, NJ: Prentice Hall.

Bandura, A. (1977). Self-efficacy: toward a unifying theory of behavioral change. Psychological Review, 84 (2), 191.

Bandura, A. (1985). Model of causality in social learning theory. I n Cognition and psychotherapy (pp. 81-99). Springer, Boston, MA.

Bandura, A. (1986). Fearful expectations and avoidant actions as coeffects of perceived self-inefficacy.

Bandura, A. (1989). Human agency in social cognitive theory. American psychologist, 44 (9), 1175.

Bandura, A. (1998). Health promotion from the perspective of social cognitive theory. Psychology and health, 13 (4), 623-649.

Bandura, A. (2003). Social cognitive theory for personal and social change by enabling media. In Entertainment-education and social change (pp. 97-118). Routledge.

Bandura, A. Ross, D., & Ross, S. A. (1961). Transmission of aggression through the imitation of aggressive models. Journal of Abnormal and Social Psychology , 63, 575-582.

Debell, A. (2021). What is Observational Learning? 

Daffin, L. (2021). Principles of Learning and Behavior. Washington State University.

Kirsh, S. J. (2011). Children, adolescents, and media violence: A critical look at the research. 

LaMort, W. (2019). The Social Cognitive Theory. Boston University.

Murrell, A. R., Christoff, K. A., & Henning, K. R. (2007). Characteristics of domestic violence offenders: Associations with childhood exposure to violence. Journal of Family violence, 22 (7), 523-532.

Reed, M. S., Evely, A. C., Cundill, G., Fazey, I., Glass, J., Laing, A., … & Stringer, L. C. (2010). What is social learning?. Ecology and society, 15 (4).

Schunk, D. H. (2012). Social cognitive theory .

Skinner, B. F. (1950). Are theories of learning necessary?. Psychological Review, 57 (4), 193.

Related Articles

Learning Theories

Aversion Therapy & Examples of Aversive Conditioning

Learning Theories , Psychology , Social Science

Albert Bandura’s Social Learning Theory

Learning Theories , Psychology

Behaviorism In Psychology

Famous Experiments , Learning Theories

Bandura’s Bobo Doll Experiment on Social Learning

Bloom’s Taxonomy of Learning

Child Psychology , Learning Theories

Jerome Bruner’s Theory Of Learning And Cognitive Development

• Bipolar Disorder
• Therapy Center
• When To See a Therapist
• Types of Therapy
• Best Online Therapy
• Best Couples Therapy
• Best Family Therapy
• Managing Stress
• Sleep and Dreaming
• Understanding Emotions
• Self-Improvement
• Healthy Relationships
• Student Resources
• Personality Types
• Guided Meditations
• Verywell Mind Insights
• 2024 Verywell Mind 25
• Mental Health in the Classroom
• Editorial Process
• Meet Our Review Board
• Crisis Support

How Observational Learning Affects Behavior

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

• Influential Factors
• Pros and Cons

Observational learning describes the process of learning by watching others, retaining the information, and then later replicating the behaviors that were observed.

There are a number of learning theories, such as classical conditioning and operant conditioning , that emphasize how direct experience, reinforcement, or punishment can lead to learning. However, a great deal of learning happens indirectly.

For example, think about how a child may watch adults waving at one another and then imitates these actions later on. A tremendous amount of learning happens through this process. In psychology , this is referred to as observational learning.

Observational learning is sometimes called shaping, modeling, and vicarious reinforcement. While it can take place at any point in life, it tends to be the most common during childhood.

It also plays an important role in the socialization process. Children learn how to behave and respond to others by observing how their parent(s) and/or caregivers interact with other people.

Verywell / Brianna Gilmartin

History of Observational Learning

Psychologist Albert Bandura is the researcher most often associated with learning through observation. He and others have demonstrated that we are naturally inclined to engage in observational learning.

Studies suggest that imitation with social understanding tends to begin around 2 years old, but will vary depending on the specific child. In the past, research has claimed that newborns are capable of imitation, but this likely isn't true, as newborns often react to stimuli in a way that may seem like imitation, but isn't.

Basic Principles of Social Learning Theory

If you've ever made faces at a toddler and watched them try to mimic your movements, then you may have witnessed how observational learning can be such an influential force. Bandura's social learning theory stresses the power of observational learning.

Bobo Doll Experiment

Bandura's Bobo doll experiment is one of the most famous examples of observational learning. In the Bobo doll experiment , Bandura demonstrated that young children may imitate the aggressive actions of an adult model. Children observed a film where an adult repeatedly hit a large, inflatable balloon doll and then had the opportunity to play with the same doll later on.

Children were more likely to imitate the adult's violent actions when the adult either received no consequences or when the adult was rewarded. Children who saw the adult being punished for this aggressive behavior were less likely to imitate them.

Observational Learning Examples

The following are instances that demonstrate observational learning has occurred.

• A child watches their parent folding the laundry. They later pick up some clothing and imitate folding the clothes.
• A young couple goes on a date to an Asian restaurant. They watch other diners in the restaurant eating with chopsticks and copy their actions to learn how to use these utensils.
• A child watches a classmate get in trouble for hitting another child. They learn from observing this interaction that they should not hit others.
• A group of children play hide-and-seek. One child joins the group and is not sure what to do. After observing the other children play, they quickly learn the basic rules and join in.

Stages of Observational Learning

There are four stages of observational learning that need to occur for meaningful learning to take place. Keep in mind, this is different than simply copying someone else's behavior. Instead, observational learning may incorporate a social and/or motivational component that influences whether the observer will choose to engage in or avoid a certain behavior.

For an observer to learn, they must be in the right mindset to do so. This means having the energy to learn, remaining focused on what the model is engaging in, and being able to observe the model for enough time to grasp what they are doing.

How the model is perceived can impact the observer's level of attention. Models who are seen being rewarded for their behavior, models who are attractive, and models who are viewed as similar to the observer tend to command more focus from the observer.

If the observer was able to focus on the model's behavior, the next step is being able to remember what was viewed. If the observer is not able to recall the model's behavior, they may need to go back to the first stage again.

Reproduction

If the observer is able to focus and retains the information, the next stage in observational learning is trying to replicate it. It's important to note that every individual will have their own unique capacity when it comes to imitating certain behaviors, meaning that even with perfect focus and recall, some behaviors may not be easily copied.

In order for the observer to engage in this new behavior, they will need some sort of motivation . Even if the observer is able to imitate the model, if they lack the drive to do so, they will likely not follow through with this new learned behavior.

Motivation may increase if the observer watched the model receive a reward for engaging in a certain behavior and the observer believes they will also receive some reward if they imitate said behavior. Motivation may decrease if the observer had knowledge of or witnessed the model being punished for a certain behavior.

Influences on Observational Learning

According to Bandura's research, there are a number of factors that increase the likelihood that a behavior will be imitated. We are more likely to imitate:

• People we perceive as warm and nurturing
• People who receive rewards for their behavior
• People who are in an authoritative position in our lives
• People who are similar to us in age, sex, and interests
• People we admire or who are of a higher social status
• When we have been rewarded for imitating the behavior in the past
• When we lack confidence in our own knowledge or abilities
• When the situation is confusing, ambiguous, or unfamiliar

Pros and Cons of Observational Learning

Observational learning has the potential to teach and reinforce or decrease certain behaviors based on a variety of factors. Particularly prevalent in childhood, observational learning can be a key part of how we learn new skills and learn to avoid consequences.

However, there has also been concern about how this type of learning can lead to negative outcomes and behaviors. Some studies, inspired by Bandura's research, focused on the effects observational learning may have on children and teenagers.

For example, previous research drew a direct connection between playing certain violent video games and an increase in aggression in the short term. However, later research that focused on the short- and long-term impact video games may have on players has shown no direct connections between video game playing and violent behavior.

Similarly, research looking at sexual media exposure and teenagers' sexual behavior found that, in general, there wasn't a connection between watching explicit content and having sex within the following year.

Another study indicated that if teenagers age 14 and 15 of the same sex consumed sexual media together and/or if parents restricted the amount of sexual content watched, the likelihood of having sex was lower. The likelihood of sexual intercourse increased when opposite-sex peers consumed sexual content together.

Research indicates that when it comes to observational learning, individuals don't just imitate what they see and that context matters. This may include who the model is, who the observer is with, and parental involvement.

Uses for Observational Learning

Observational learning can be used in the real world in a number of different ways. Some examples include:

• Learning new behaviors : Observational learning is often used as a real-world tool for teaching people new skills. This can include children watching their parents perform a task or students observing a teacher engage in a demonstration.
• Strengthening skills : Observational learning is also a key way to reinforce and strengthen behaviors. For example, if a study sees another student getting a reward for raising their hand in class, they will be more likely to also raise their hand the next time they want to ask a question.
• Minimizing negative behaviors : Observational learning also plays an important role in reducing undesirable or negative behaviors. For example, if you see a coworker get reprimanded for failing to finish a task on time, it means that you may be more likely to finish your work more quickly.

A Word From Verywell

Observational learning can be a powerful learning tool. When we think about the concept of learning, we often talk about direct instruction or methods that rely on reinforcement and punishment . But, a great deal of learning takes place much more subtly and relies on watching the people around us and modeling their actions. This learning method can be applied in a wide range of settings including job training, education, counseling, and psychotherapy .

Jones SS. The development of imitation in infancy.   Philosophical Transactions of the Royal Society B: Biological Sciences . 2009;364(1528):2325-2335. doi:10.1098/rstb.2009.0045

Bandura A.  Social Learning Theory . Prentice Hall; 1977.

Kühn S, Kugler DT, Schmalen K, Weichenberger M, Witt C, Gallinat J. Does playing violent video games cause aggression? A longitudinal intervention study.  Mol Psychiatry . 2019;24(8):1220-1234. doi:10.1038/s41380-018-0031-7

Gottfried JA, Vaala SE, Bleakley A, Hennessy M, Jordan A. Does the effect of exposure to TV sex on adolescent sexual behavior vary by genre? Communication Research . 2013;40(1):73-95. doi:10.1177/0093650211415399

Parkes A, Wight D, Hunt K, Henderson M, Sargent J. Are sexual media exposure, parental restrictions on media use and co-viewing TV and DVDs with parents and friends associated with teenagers’ early sexual behaviour?   Journal of Adolescence . 2013;36(6):1121-1133. doi:10.1016/j.adolescence.2013.08.019

The impact of interactive violence on children . U.S. Senate Hearing 106-1096. March 21, 2000.

Anderson CA, Dill KE. Video games and aggressive thoughts, feelings, and behavior in the laboratory and in life .  J Pers Soc Psychol. 2000;78(4):772-790. doi:10.1037/0022-3514.78.4.772

Collins RL, Elliott MN, Berry SH, et al. Watching sex on television predicts adolescent initiation of sexual behavior . Pediatrics . 2004;114(3):e280-9. dloi:10.1542/peds.2003-1065-L

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

6.5 Observational Learning (Modeling)

Learning objectives.

By the end of this section, you will be able to:

• Define observational learning
• Discuss the steps in the modeling process
• Explain the prosocial and antisocial effects of observational learning

   Previous sections of this chapter focused on classical and operant conditioning, which are forms of associative learning. In observational learning, we learn by watching others and then imitating, or modeling, what they do or say. The individuals performing the imitated behavior are called models. Research suggests that this imitative learning involves a specific type of neuron, called a mirror neuron (Hickock, 2010; Rizzolatti, Fadiga, Fogassi, & Gallese, 2002; Rizzolatti, Fogassi, & Gallese, 2006).

Humans and other animals are capable of observational learning. As you will see, the phrase “monkey see, monkey do” really is accurate (figure below). The same could be said about other animals. For example, in a study of social learning in chimpanzees, researchers gave juice boxes with straws to two groups of captive chimpanzees. The first group dipped the straw into the juice box, and then sucked on the small amount of juice at the end of the straw. The second group sucked through the straw directly, getting much more juice. When the first group, the “dippers,” observed the second group, “the suckers,” what do you think happened? All of the “dippers” in the first group switched to sucking through the straws directly. By simply observing the other chimps and modeling their behavior, they learned that this was a more efficient method of getting juice (Yamamoto, Humle, and Tanaka, 2013).

This spider monkey learned to drink water from a plastic bottle by seeing the behavior modeled by a human. (credit: U.S. Air Force, Senior Airman Kasey Close)

   Imitation is much more obvious in humans, but is imitation really the sincerest form of flattery? Consider Claire’s experience with observational learning. Claire’s nine-year-old son, Jay, was getting into trouble at school and was defiant at home. Claire feared that Jay would end up like her brothers, two of whom were in prison. One day, after yet another bad day at school and another negative note from the teacher, Claire, at her wit’s end, beat her son with a belt to get him to behave. Later that night, as she put her children to bed, Claire witnessed her four-year-old daughter, Anna, take a belt to her teddy bear and whip it. Claire was horrified, realizing that Anna was imitating her mother. It was then that Claire knew she wanted to discipline her children in a different manner.

Like Tolman, whose experiments with rats suggested a cognitive component to learning, psychologist Albert Bandura’s ideas about learning were different from those of strict behaviorists. Bandura and other researchers proposed a brand of behaviorism called social learning theory, which took cognitive processes into account. According to Bandura , pure behaviorism could not explain why learning can take place in the absence of external reinforcement. He felt that internal mental states must also have a role in learning and that observational learning involves much more than imitation. In imitation, a person simply copies what the model does. Observational learning is much more complex. According to Lefrançois (2012) there are several ways that observational learning can occur:

• You learn a new response. After watching your coworker get chewed out by your boss for coming in late, you start leaving home 10 minutes earlier so that you won’t be late.
• You choose whether or not to imitate the model depending on what you saw happen to the model. Remember Julian and his father? When learning to surf, Julian might watch how his father pops up successfully on his surfboard and then attempt to do the same thing. On the other hand, Julian might learn not to touch a hot stove after watching his father get burned on a stove.
• You learn a general rule that you can apply to other situations.

Bandura identified three kinds of models: live, verbal, and symbolic. A live model demonstrates a behavior in person, as when Ben stood up on his surfboard so that Julian could see how he did it. A verbal instructional model does not perform the behavior, but instead explains or describes the behavior, as when a soccer coach tells his young players to kick the ball with the side of the foot, not with the toe. A symbolic model can be fictional characters or real people who demonstrate behaviors in books, movies, television shows, video games, or Internet sources (figure below).

(a) Yoga students learn by observation as their yoga instructor demonstrates the correct stance and movement for her students (live model). (b) Models don’t have to be present for learning to occur: through symbolic modeling, this child can learn a behavior by watching someone demonstrate it on television. (credit a: modification of work by Tony Cecala; credit b: modification of work by Andrew Hyde)

Steps in the modeling process.

   Of course, we don’t learn a behavior simply by observing a model. Bandura described specific steps in the process of modeling that must be followed if learning is to be successful: attention, retention, reproduction, and motivation. First, you must be focused on what the model is doing—you have to pay attention. Next, you must be able to retain, or remember, what you observed; this is retention. Then, you must be able to perform the behavior that you observed and committed to memory; this is reproduction. Finally, you must have motivation. You need to want to copy the behavior, and whether or not you are motivated depends on what happened to the model. If you saw that the model was reinforced for her behavior, you will be more motivated to copy her. This is known as vicarious reinforcement. On the other hand, if you observed the model being punished, you would be less motivated to copy her. This is called vicarious punishment. For example, imagine that four-year-old Allison watched her older sister Kaitlyn playing in their mother’s makeup, and then saw Kaitlyn get a time out when their mother came in. After their mother left the room, Allison was tempted to play in the make-up, but she did not want to get a time-out from her mother. What do you think she did? Once you actually demonstrate the new behavior, the reinforcement you receive plays a part in whether or not you will repeat the behavior.

Bandura researched modeling behavior, particularly children’s modeling of adults’ aggressive and violent behaviors (Bandura, Ross, & Ross, 1961). He conducted an experiment with a five-foot inflatable doll that he called a Bobo doll. In the experiment, children’s aggressive behavior was influenced by whether the teacher was punished for her behavior. In one scenario, a teacher acted aggressively with the doll, hitting, throwing, and even punching the doll, while a child watched. There were two types of responses by the children to the teacher’s behavior. When the teacher was punished for her bad behavior, the children decreased their tendency to act as she had. When the teacher was praised or ignored (and not punished for her behavior), the children imitated what she did, and even what she said. They punched, kicked, and yelled at the doll.

What are the implications of this study? Bandura concluded that we watch and learn, and that this learning can have both prosocial and antisocial effects. Prosocial (positive) models can be used to encourage socially acceptable behavior. Parents in particular should take note of this finding. If you want your children to read, then read to them. Let them see you reading. Keep books in your home. Talk about your favorite books. If you want your children to be healthy, then let them see you eat right and exercise, and spend time engaging in physical fitness activities together. The same holds true for qualities like kindness, courtesy, and honesty. The main idea is that children observe and learn from their parents, even their parents’ morals, so be consistent and toss out the old adage “Do as I say, not as I do,” because children tend to copy what you do instead of what you say. Besides parents, many public figures, such as Martin Luther King, Jr. and Mahatma Gandhi, are viewed as prosocial models who are able to inspire global social change. Can you think of someone who has been a prosocial model in your life?

The antisocial effects of observational learning are also worth mentioning. As you saw from the example of Claire at the beginning of this section, her daughter viewed Claire’s aggressive behavior and copied it. Research suggests that this may help to explain why abused children often grow up to be abusers themselves (Murrell, Christoff, & Henning, 2007). In fact, about 30% of abused children become abusive parents (U.S. Department of Health & Human Services, 2013). We tend to do what we know. Abused children, who grow up witnessing their parents deal with anger and frustration through violent and aggressive acts, often learn to behave in that manner themselves. Sadly, it’s a vicious cycle that’s difficult to break.

Some studies suggest that violent television shows, movies, and video games may also have antisocial effects (figure below) although further research needs to be done to understand the correlational and causational aspects of media violence and behavior. Some studies have found a link between viewing violence and aggression seen in children (Anderson & Gentile, 2008; Kirsch, 2010; Miller, Grabell, Thomas, Bermann, & Graham-Bermann, 2012). These findings may not be surprising, given that a child graduating from high school has been exposed to around 200,000 violent acts including murder, robbery, torture, bombings, beatings, and rape through various forms of media (Huston et al., 1992). Not only might viewing media violence affect aggressive behavior by teaching people to act that way in real life situations, but it has also been suggested that repeated exposure to violent acts also desensitizes people to it. Psychologists are working to understand this dynamic.

Can video games make us violent? Psychological researchers study this topic. (credit: “woodleywonderworks”/Flickr)

   According to Bandura, learning can occur by watching others and then modeling what they do or say. This is known as observational learning. There are specific steps in the process of modeling that must be followed if learning is to be successful. These steps include attention, retention, reproduction, and motivation. Through modeling, Bandura has shown that children learn many things both good and bad simply by watching their parents, siblings, and others.

References:

Openstax Psychology text by Kathryn Dumper, William Jenkins, Arlene Lacombe, Marilyn Lovett and Marion Perlmutter licensed under CC BY v4.0. https://openstax.org/details/books/psychology

Review Questions:

1. The person who performs a behavior that serves as an example is called a ________.

c. instructor

2. In Bandura’s Bobo doll study, when the children who watched the aggressive model were placed in a room with the doll and other toys, they ________.

a. ignored the doll

b. played nicely with the doll

c. played with tinker toys

d. kicked and threw the doll

3. Which is the correct order of steps in the modeling process?

a. attention, retention, reproduction, motivation

b. motivation, attention, reproduction, retention

c. attention, motivation, retention, reproduction

d. motivation, attention, retention, reproduction

4. Who proposed observational learning?

a. Ivan Pavlov

b. John Watson

c. Albert Bandura

d. B. F. Skinner

Critical Thinking Questions:

1. What is the effect of prosocial modeling and antisocial modeling?

2. Cara is 17 years old. Cara’s mother and father both drink alcohol every night. They tell Cara that drinking is bad and she shouldn’t do it. Cara goes to a party where beer is being served. What do you think Cara will do? Why?

Personal Application Question:

1. What is something you have learned how to do after watching someone else?

observational learning

vicarious punishment

vicarious reinforcement

Answers to Exercises

1. Prosocial modeling can prompt others to engage in helpful and healthy behaviors, while antisocial modeling can prompt others to engage in violent, aggressive, and unhealthy behaviors.

2. Cara is more likely to drink at the party because she has observed her parents drinking regularly. Children tend to follow what a parent does rather than what they say.

model:  person who performs a behavior that serves as an example (in observational learning)

observational learning:  type of learning that occurs by watching others

vicarious punishment:  process where the observer sees the model punished, making the observer less likely to imitate the model’s behavior

vicarious reinforcement:  process where the observer sees the model rewarded, making the observer more likely to imitate the model’s behavior

Share This Book

• Increase Font Size

Observational Learning: The Complete Guide

It’s not uncommon for people to conceptualize learning as an action that occurs through the use of books and lectures. This is referred to as the traditional model of learning, in which students are expected to go through rote memorization of specific information. This has long been the model adopted in the United States, though that has changed over the last few decades as more educational reforms have taken place.

One of the changes has been greater attention to observational learning, a type of social learning that does not necessarily require any type of reinforcement.

Observational learning, like its namesake implies, is a type of learning that happens as students observe a model. The learner learns by observing the behaviors of others. This social model could be any one of a number of people, including family members, teachers, or friends.

The social model tends to be a particularly powerful instructor when they occupy a higher status, such as teacher or parent, and this effect is particularly powerful among younger people. As such, children may particularly benefit from having strong social models who model behavior for them.

A Brief History

Observational learning has been thoroughly studied, with researchers originally doing in-depth research into observational learning during the 1960s and 1970s. Albert Bandura noted that children often followed the examples of older social models, displaying aggressive behavior if models were aggressive or acting more passively if the social model was passive. However, this was not the only examination of observational learning.

Researchers also noted that children made moral judgments similar to those that social models made, for instance. Over the course of two decades, researchers concluded that observational learning was linked to learning in a variety of ways and that key in all these cases was the role of modeling.

The Social Model

At the core of observational learning is the importance of the social model. Observational learning is so powerful that researchers realized that sometimes incidental behaviors that they demonstrated were picked up by learners and used in sometimes very different contexts.

As such, learners may sometimes observe behavior and learn from it without the social model even intending to model behavior for anyone else. Then, learners can transfer what they’ve learned to a completely different environment. This has significant implications for anyone who occupies the role of a social model, since their behavior may significantly influence the behavior of a learner even when they have no intention to do so.

However, learners don’t simply copy a behavior and repeat it. The learners also pay attention to the consequence of a behavior. In research conducted among children, researchers noted that children observed what happened as a consequence of a social model’s behavior. If a behavior was rewarded, children were more likely to replicate the behavior. In contrast, children tried to avoid a behavior if it was punished. As such, learning through observation could either be direct or indirect.

A social model may try to demonstrate a skill to a learner and show its successful outcome, which would encourage the learner to attempt the same behavior. At other times, a social model’s actions may be rewarded. Children, observing this, will attempt the same behavior once again even if the model was not purposely attempting to demonstrate the behavior. Or, children may avoid that behavior if the model was punished. With that said, children were generally less likely to change their action based on punishments.

The implication of this was that children instead responded more strongly to rewards. For anyone in a social model role, this meant that to most strongly encourage changes in a child, rewards should be the focus of the model, rather than punishment.

Formulating Learning and Performance

For educators, observational learning has two be considered in two distinct ways: learning and performance. Learning refers to the cognitive model that a person forms, while performance refers to the actual ability to repeat the task. When testing whether modeling is working among students, instructors should assess their students first by asking them to verbally describe the task.

The greater the ability for a student to describe the steps, the greater amount of learning that has occurred. Afterward, students should be actually asked to repeat the task themselves, which indicates their performance level. Although there are correlations between the ability to describe a task and repeat it, those correlations are not always perfect. There may at times be a gap between how well a student has learned a task versus how well they can perform the task.

Returning to the value of rewards versus punishments, researchers found that there was a gap between how well participants were able to repeat a task based on rewards versus punishments. In observations of children, researchers found that those who were rewarded and punished for learning a task could both describe how to do the task at about equal levels. In other words, both those who were rewarded and punished experienced a similar level of learning. However, in actual practice, there was superior performance among the reward group.

These findings implied once again that rewarding learners was a superior approach to instructing students, though in this case specifically when it came to performance of the task. As such, teachers may find that students can similarly describe how to perform a task but may not be able to equally perform that task in practice. This may be related to the rewards and punishments system that the teacher has used.

The Stages of Observational Learning

Researchers indicated that there were four stages to observational learning. Early in the development of this learning model, Albert Bandura formulated these stages to create a theoretical system by which students progressed from initial observation to actual practice.

At the earliest stage of learning, students first needed to pay attention. Teachers should take note the importance of attention to learning. This shouldn’t be a surprising statement, but the level of attention that a learner pays to an instructor impacts how much they learn. This is no different in observational learners.

The learner must observe what’s happening and pay attention to the steps in a task. How much attention the learner pays, though, can depend on a few different factors. Researchers found that the degree to which an observer identified with the model impacted the degree of learning that occurred. This suggested that teachers should try to cultivate good relationships with their students that would help encourage increased observations during the learning process.

The second stage of the observational learning model included retention. This stage should be simple enough for students to understand. What is taught must be retained, and observers need to put what they’ve observed into their memory.

How much an observer retains goes back to the fact that they needed to have paid attention, which itself relied on how much they identified with the model. However, other factors also impact retention.

There are sometimes inherent characteristics that impacted how much a student retained. At other times, different learners had different retention strategies that helped them to more effectively retain what they had learned.

Retention would rarely be equal between learners, given the diversity of the population, which may require models to model a behavior more than once for some learners. Remembering that there is a difference between learning versus performance , at this stage, the degree of learning could be tested for by asking students to repeat the steps of the task.

The third stage of the observational learning process was the initiation stage. At this stage, learners now have to demonstrate performance by repeating the task themselves. The observer must demonstrate they are capable of repeating what they’ve been taught. It’s expected at this stage that an observer possesses all the necessary skills to repeat the task, but this may not be the case. Some tasks may be complex enough to make reproduction difficult. This is particularly the case when it comes to physical skills.

Learners may observe a model, but it may require practice to repeat the task physically even if they can verbally describe perfectly what’s happening. Physical repetition is particularly difficult with complex physical tasks that occur in areas such as sports or music.

For many teachers, this may not be a struggle they have to concern themselves with. However, there may be nuances to repeating certain tasks, such as handling equipment in a lab experiment, that impact a student’s repetition of what they’ve observed. This is where repetition and practice helps to improve the student’s performance.

The final stage of observational learning is less of a stage and more of a description of one characteristic that is necessary for learning to occur. Namely, students need to be motivated to learn.

Students that are highly motivated are more likely to want to recreate a behavior they observe. This impacts the degree of attention they pay, impacts their retention, and impacts their drive to physically reproduce the behavior. As such, teachers cannot dismiss the importance of this quality among students. To the extent that they are able to, teachers should do their best to encourage the motivation of their students in order to improve both learning and performance of a task.

Examples of Observational Learning

It’s easy to see just how many situations in which observational learning may apply. Children pick up all sorts of behaviors from their parents, for example. They may observe their parents doing laundry, such as folding clothing, and demonstrate the ability to do the same.

Children on a playground may observe other children being punished for playing roughly and avoid that behavior to avoid being punished themselves. Yet once more, children may observe other children playing a game and learn the rules for themselves by simply observing.

This also holds implications for teaching in the classroom. Take a science experiment, for example. It may be possible to describe how a science experiment might take place, but it may be far more difficult to repeat the experiment itself. In this case, it would be important for a science instructor to take their students through the experiment for themselves, step by step. However, the science instructor doesn’t have to limit observational learning to only an observation of the instructor.

Instead, instructors can also support students in the classroom by pairing more advanced learners with those who are struggling with the experiment. Peers can help to model the experiment to slower learners, taking them through the experiment step by step.

The concept of peer learning itself takes on special importance when considering that the degree to which a learner observes and retains information has a lot to do with the degree to which they identify with the instructor.

Students may find it hard to identify with their teacher, but they may find it far easier to identify with their peers. For tasks that can be observed and modeled, it may be beneficial to pair students with other students.

By doing so, teachers may increase the likeliness that learners will pay attention during the task and retain information. Students may also feel more motivated when observing their peers. For better or worse, social influence and pressure plays a role in the behavior of almost everyone.

The influence of social peers may drive students to want to perform well on a task, motivating them to pay more attention while the behavior is being modeled. This would in turn lend itself to greater observation, retention, and a stronger desire to repeat the task for themselves.

Latent Learning and Observational Learning

One last note about observational learning is that it relates to another important learning theory, the concept of latent learning . In latent learning, people learn skills and the ability to do things without being expressly instructed.

They don’t manifest those skills until they’re prompted to do so. For instance, a learner may observe someone regularly completing a task. Returning to the example of a child that watches their parents fold clothes, the child may then learn to fold clothes themselves yet never demonstrate the skill until prompted.

The important takeaway here is that learning occurs all the time, even when there is no intention to teach a person. By modeling behavior for children, skill can be encouraged indirectly. Parents who read at home will be observed by their children, and those children will then be motivated to read for themselves. That is an effect of observational learning, since it teaches children the habit of reading.

However, if there are educational resources in the environment that they can read, then children will end up reading about different educational concepts and skills. They may then demonstrate those skills in the classroom, even if they were never expressly taught to them by anyone. As such, observational learning and latent learning may work together to encourage skills in students that manifest themselves once the student is in the classroom.

Similar Posts:

• Discover Your Learning Style – Comprehensive Guide on Different Learning Styles
• 35 of the BEST Educational Apps for Teachers (Updated 2024)
• 20 Huge Benefits of Using Technology in the Classroom

Leave a Comment Cancel reply

Save my name and email in this browser for the next time I comment.

Observational Learning Analysis Essay

Observational learning is induced onto a person by a third party in all cases. This learning takes place by way of a person looking at a third party performing an action. Observational learning can and will occur in any age bracket. The beauty of observational learning is that of interest generated by the observer and the subsequent internalization of the concept learned to serve the individual’s intended motive (Chance, 2008, p. 23).

At a local competition in a game of handball, sidestepping is one among several moves that are used to penetrate the defensive wall of opponents. In any game, high scores translate to winning. Unfortunately, since my sidestep was poor I couldn’t score. I generated interest by observing how easy it was to score once I observed an opponent performing the move that subsequently translated to him scoring many goals. The essence of this illustration is that by observing how the move was performed on several occasions I was able to master this beautiful skill and eventually would be able to dislodge any defense and create chances of scoring.

There are a number of steps that are involved in observational learning and attention is one of them. The observer ought to be keen to and pay attention to details where necessary. Lack of the observer being attentive would out rightly lead to failure to grasp the underlying concepts in what is being observed. It also calls for the observer to pay attention to the major aspects of what is being observed. Failure to this learning would be deemed to have not taken place or there was little learning. The emotion of the observer also plays a role in the eventual internalization (Chance, 2008, p. 31).

The observer’s retentional processes swing into action after observation. This entails a brief imitation of what was being observed. The essence of this is that it aids the observer to recall some of the aspects of what was being observed. In the first place, it would be hard to perfectly carry out the move hence the observer would do it in his own way, immediately following what was observed. The perfection depends heavily on the observer because it is by doing it in his own way and comparing this against what was being done and identifying flaws in what he has done and that need to be done in order to attain perfection (Chance, 2008, p. 34).

An individual must have the motor reproductive processes required to perform the required processes. It translates to the individual’s ability to perform what was observed. While we may grudgingly accept that some people may observe the third party performing an action they may not be able to perform the same yet others would perform what has been observed with a lot of ease and in fact a lot better. This boils down to the fact that the motor reproductive processes vary (Knowles & McLean 1992, p. 66).

Motivation plays a major role in observational learning. it comes in several forms depending on what is being observed. Quite often they are the rewards that motivate an individual. It could come in various forms but it’s always relevant to the subject (Knowles & McLean 1992, p. 66).

By observing other players make those special moves, it dawns on me that I can perform them too and possibly give it my own personal touch and maybe do it much better. The significance of this is that it gives people a chance to learn from each other and it also gives us the opportunity to teach others what we know.

Chance, P. (2008). Learning and Behavior: Active Learning Edition . Belmont, USA: Cengage Learning

Knowles, R & McLean, G. (1992). Psychological Foundations of Moral Education and Character Development: An Integrated Theory of Moral Development . Washington DC: CRVP

• Chicago (A-D)
• Chicago (N-B)

IvyPanda. (2021, December 10). Observational Learning Analysis. https://ivypanda.com/essays/observational-learning-analysis/

"Observational Learning Analysis." IvyPanda , 10 Dec. 2021, ivypanda.com/essays/observational-learning-analysis/.

IvyPanda . (2021) 'Observational Learning Analysis'. 10 December.

IvyPanda . 2021. "Observational Learning Analysis." December 10, 2021. https://ivypanda.com/essays/observational-learning-analysis/.

1. IvyPanda . "Observational Learning Analysis." December 10, 2021. https://ivypanda.com/essays/observational-learning-analysis/.

Bibliography

IvyPanda . "Observational Learning Analysis." December 10, 2021. https://ivypanda.com/essays/observational-learning-analysis/.

• Ethnography and Participant Observation: Video Analysis
• Public Internalization of Profit and Cost Externalities
• From Observation to Instrumentation
• Basic Components of Sociological Research
• The Concept of Literary Criticism
• Similarities and Differences between Scientific and Historical Explanations
• McCluskey’s Qualitative Study “Exclusion From School?”
• Issues of Integrity in Qualitative Research

16 Observational Learning Examples

Definition of observational learning.

There are 4 key factors involved in observational learning according to Albert Bandura (1977), the father of social learning theory (later merging into the social cognitive theory ).

• Attention: The first key element is attention . Observers cannot learn if they are not actually paying attention.
• Retention: Retention means that the observation must be placed in memory.
• Reproduction: Reproduction refers to the observer’s ability to reproduce the behavior observed.
• Motivation: And finally, without motivation to engage in the behavior, it will not be reproduced.

In addition, the person being observed is also a key factor. Models that are in high-status positions, considered experts, are rewarded for their actions, or provide nurturance to the observer, are more likely to have their actions imitated.

Situated Learning Theory also highly values observational learning. This theory argues that people learn best when ‘situated’ within a group of people who are actively completing the tasks that need to be learned. For example, being an apprenticeship getting on-the-job training is seen to be far more valuable than learning about theory in a classroom.

Examples of Observational Learning

1. the bobo dolls experiment.

Dr. Albert Bandura conducted one of the most influential studies in psychology in the 1960s at Stanford University. 

His intention was to demonstrate that cognitive processes play a fundamental role in learning. At the time, Behaviorism was the predominant theoretical perspective, which completely rejected all inferences to constructs not directly observable.

So, Bandura made two versions of a video. In version #1, an adult behaved aggressively with a Bobo doll by throwing it around the room and striking it with a wooden mallet. In version #2, the adult played gently with the doll by carrying it around to different parts of the room and pushing it gently.

After showing children one of the two versions, they were taken individually to a room that had a Bobo doll.

Their behavior was observed and the results indicated that children that watched version #1 of the video were far more aggressive than those that watched version #2. Not only did Bandura’s Bobo doll study form the basis of his social learning theory, it also helped start the long-lasting debate about the harmful effects of television on children.

Note that this study had features of both experiment and observational research – for the difference, see: experiment vs observation .

2. Apprenticeships

Apprenticeships are a perfect example of observational learning. Through an apprenticeship, you can actually watch what the professional is doing rather than simply learning about it in a classroom.

Apprenticeships are therefore very common in practical and hands-on professions like plumbing, carpentry, and cooking.

A similar concept, the internship, occurs in white-collar professions. Internships involve a blend of theoretical learning and apprenticeship scenarios to allow people to learn about the nexus between theory and practice. For example, doctors will often complete their medical degree then do an internship for a few years under more experienced doctors.

3. Learning How to Walk

One of the earliest manifestations of observational learning comes as toddlers learn how to walk. They undoubtedly watch their caregivers stroll across the room countless times a day.

By watching how the legs move forward and backward, accompanied by the slight movements of the upper limbs, they begin to see the basic sequence required to walk.

Of course, standing up is first, followed by maintaining balance and not falling. Those sound easier than they really are. So, children will start by holding on to a table or the edge of the sofa and scoot along.

After some time, a toddler might manage to put together 3 or 4 steps in a row; to the great joy of mom and dad.  

4. Gender Norms

In the last 20 years, there has been increasing recognition that our traditional notions of masculinity and femininity are learned rather than innate.

In other words, boys learn to “act like men” through observing male role models in their lives. Similarly, girls learn to “be girly” by observing other females.

One way that we know that gender stereotypes are learned rather than natural is that different societies have different expressions of gender. In some societies, for example, women are the decision-makers in the household, while in others, men are seen as the head of the household. This has led sociologists and cultural theorists to claim the gender norms are ‘ social constructs ’ which create hierarchies of privilege in society (aka social stratification ).

5. Parallel Play

Parallel play is a stage of play in child development where children observe one another playing. Generally, this stage occurs between ages 2 and 4.

During parallel play, children tend not to play with other children. Instead, they will watch from a distance. You might observe, for example, a child playing with a toy while their sibling or peer keeps an eye on them. Later, that sibling will come up to the toy and play with it in a similar way to the first child. Here, we can see that the second child observed then attempted to mimic the first child.

Observational learning can also occur during cooperative play , a later play stage in Parten’s theory of play-based learning. During cooperative play, children will play together , including each other into their play narratives.

6. Chimpanzee Tool Use

Chimps have been observed in a naturalistic environment using a variety of tools. In nearly all of these observed instances of chimp tool-use, a young chimp can be seen nearby observing. This is how the skill is passed down to younger generations.

For example, some chimps use a twig to collect termites out of a termite hill. The twig is used like a fishing pole to probe the termite hill and then retrieve it covered in termites. Other chimps have been observed using rocks to crack open nuts.

Furthermore, surprisingly, the mother chimp provides very little assistance. “Non-human primates are often thought to learn tool skills by watching others and practicing on their own, with little direct help from mothers or other expert tool users,” says Stephanie Musgrave, first author of the study found here , which includes some amazing videos.

7. Wolf Pack Hunting

Like Chimpanzees, wolves also learn from observation. Wolves are extremely competent hunters. They hunt in packs and take cues from the wolf pack leader.

Young wolves are given roles that are less important in the pack. Their job is to learn, watch, and develop their skills. As they get older and stronger, they move up the hierarchy and take more active roles in the hunt.

In these instances, we can see how hunting in a wolf pack is an example of observational learning. In fact, it’s the perfect example of situated learning : learning by being part of the group. You start out in the periphery, and as you get more competent, you’re given bigger and more important roles.

8. Table Manners and Cutlery

Table manners and learning how to use cutlery are other examples of observational learning.

Young children start by imitating how the spoon is held, how it scoops up food, and then moved to the mouth for consumption. Of course, there are a lot of mistakes along the way and more times than not, more food ends up on the floor than in the mouth.

Over the next few years, the child’s caregivers will demonstrate various table etiquette, such as chewing with one’s mouth closed, keeping the head upright, and not using the plate as a place to mix food and juice.

Obviously, table manners are culturally defined so what a child observes as appropriate behavior in one country might be the exact opposite of “manners” in another.

9. Culturally Defined Gestures

One lesson learned in the age of the internet and cross-cultural communication is that a simple gesture can have a multitude of meanings, completely depending on the culture it is displayed in.

For example, in many Western cultures, a thumbs-up gesture means “okay”. When you show someone that sign it means that you approve and is considered to be encouraging. However, in some Middle Eastern countries, it can be a very insulting taboo . In fact, it can be the equivalent of the middle finger in the West.

This is just one example of an observed behavior that is culturally defined. When travelling abroad, it’s best to do some research beforehand.  

10. Observing Bad Habits on T.V.

People learn a lot valuable skills and habits by watching others. Unfortunately, the same can be said of bad habits. For example, watching movie stars smoke can lead to a lot of people taking up smoking. It looks so cool on the big screen.

Drinking in excess is also a bad habit that can be observed on television. One interesting note here is that you will never see someone actually drinking on a TV commercial in the United States. Although there is no federal law prohibiting it, the industry has imposed this regulation on themselves.

So, observational learning can teach us both constructive and destructive habits.

11. YouTube Tutorial Videos

No matter what it is you want to learn how to do, there is probably a YouTube video tutorial for it.

If you want to learn how to use Photoshop or a specific video-editing program, just type in the appropriate search terms and there you go. The results will show at least a couple dozen options to choose from.

In the video, you can watch someone take you through all the necessary steps. If they go too fast, then just click pause. If what they said seemed a little unclear, then just scroll the video back a little and listen again. It’s super easy and super convenient, and a super example of observational learning.

12. Language Acquisition

Learning to speak a language is a long process. Even if the language is in your native tongue, it still takes years. If you are a second language teacher, then helping your students can take even longer.

One trick of the trade for language teachers is to instruct students to watch the teacher’s lips and mouth as they speak. Correct pronunciation has a lot to do with getting the lips to form a particular shape. Just listening to the instructor can help some, but unless the students form the right shape with their lips, their pronunciation will always be off.

We don’t usually think of learning how to speak a language as an example of observational learning, but it most definitely is.

13. Language on the Playground

The playground is a learning environment all its own. Children learn how to deal with conflicts, develop coordination, and unfortunately, sometimes foul language.

Children have a tendency to imitate others, and sometimes that doesn’t always mean imitating behaviors that are constructive.

Probably most children have heard something on the playground and then went home and repeated it do mom and dad. That can be a big mistake. Hopefully, the parents will understand and not freak out.

That leads to the next example of observational learning: when the parents show their child what is the proper way to handle this kind of situation. Remember, children observe their parents as well. So, if the parents model a certain way to handle this kind of situation, the children will likely imitate later when they have children too.

14. Wearing Seatbelts

The power of observational learning is a double-edged sword. It can lead to people picking up bad habits, or adopting good ones. Wearing a seatbelt is a classic example of how watching a public service announcement condoning a healthy habit has helped save lives.

When seatbelts were first introduced in the early days of the automobile back in the 1880s, they were not greeted warmly by the public, with tragic results.

Eventually, in 1959 Volvo offered the first three-point seatbelt in its cars and shared the patent with other manufacturers. Still, adoption by the public was reluctant.

The tide began to change, however, with the prevalence of dramatic public service announcements that showed what would happen in a car crash if you don’t wear a seatbelt. We call this vicarious punishment .

As a result, in most industrialized countries, seatbelt use is a widely accept social norm .

This is an example of how observational learning has helped save lives around the world.  

15. Cooking Shows

Learning the art of great cooking is a big part trial-and-error. It’s also something that can be learned by watching others. Fortunately, there are tons of cooking shows out there to choose from.

The chefs do a great job of demonstrating how they put together a dish. They will show viewers how to mix certain ingredients, how to slice and dice various items, and what the meal will look like when finished. Sometimes they will even go to the local farmer’s market and show viewers what to look for when selecting the ingredients.

These are all things that can be learned by reading a recipe book, but seeing it first-hand is much more informative.

16. Latent Learning

Latent learning is a form of delayed observational learning. The observed behaviors are only exhibited by the person who learned them at a much later date.

A good example is of a child who might learn new words (often swear words!), but then they do not use them until a week later. The parents turn to the child, shocked, and say “when did you learn that language!?”

But unlike most versions of observational learning (like vicarious learning,  operant conditioning , and  classical conditioning ), there doesn’t seem to be much use of rewards or punishments  in latent learning that is usually assumed to be required for learning to occur.

See More: 17 Examples of Behaviorism

Learning by observation can explain how human beings learn to do so many things. It is probably one of the most fundamental ways that people learn.

Unfortunately, that has both positive and negative manifestations. For example, toddlers learn to walk by observing their parents. Students learn proper pronunciation habits by looking closely at their teacher’s lip formations.

Yet, observing others can also get us in trouble. It can teach us bad habits such as smoking and excessive drinking. It can also be the source of innocent children going home and shocking their parents.

Like most things in life, the good must come with the bad.

Anderson, C. A., & Dill, K. E. (2000). Video games and aggressive thoughts, feelings, and behavior in the laboratory and in life. Journal of Personality and Social Psychology, 78 (4), 772–790. https://doi.org/10.1037/0022-3514.78.4.772

Bandura, A. (1977).  Social Learning Theory . Prentice Hall.

Berkowitz, L. (1990). On the formation and regulation of anger and aggression: A cognitive-neoassociationistic analysis. American Psychologist , 45 , 494–503.

Musgrave, S., Lonsdorf, E., Morgan, D., Prestipino, M., Bernstein-Kurtycz, L., Mundry, R., & Sanz, C. (2019). Teaching varies with task complexity in wild chimpanzees. Proceedings of the National Academy of Sciences, 117 , 201907476. https://doi.org/10.1073/pnas.1907476116

Stover, C. (2005). Domestic violence research: What have we learned and where do we go from here? Journal of Interpersonal Violence, 20 , 448-454. https://doi.org/10.1177/0886260504267755

Dave Cornell (PhD)

Dr. Cornell has worked in education for more than 20 years. His work has involved designing teacher certification for Trinity College in London and in-service training for state governments in the United States. He has trained kindergarten teachers in 8 countries and helped businessmen and women open baby centers and kindergartens in 3 countries.

• Dave Cornell (PhD) https://helpfulprofessor.com/author/dave-cornell-phd/ 25 Positive Punishment Examples
• Dave Cornell (PhD) https://helpfulprofessor.com/author/dave-cornell-phd/ 25 Dissociation Examples (Psychology)
• Dave Cornell (PhD) https://helpfulprofessor.com/author/dave-cornell-phd/ 15 Zone of Proximal Development Examples
• Dave Cornell (PhD) https://helpfulprofessor.com/author/dave-cornell-phd/ Perception Checking: 15 Examples and Definition

Chris Drew (PhD)

This article was peer-reviewed and edited by Chris Drew (PhD). The review process on Helpful Professor involves having a PhD level expert fact check, edit, and contribute to articles. Reviewers ensure all content reflects expert academic consensus and is backed up with reference to academic studies. Dr. Drew has published over 20 academic articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education and holds a PhD in Education from ACU.

• Chris Drew (PhD) #molongui-disabled-link 25 Positive Punishment Examples
• Chris Drew (PhD) #molongui-disabled-link 25 Dissociation Examples (Psychology)
• Chris Drew (PhD) #molongui-disabled-link 15 Zone of Proximal Development Examples
• Chris Drew (PhD) #molongui-disabled-link Perception Checking: 15 Examples and Definition

Leave a Comment Cancel Reply

Your email address will not be published. Required fields are marked *

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• Front Psychol

Observational Learning: Tell Beginners What They Are about to Watch and They Will Learn Better

Observation aids motor skill learning. When multiple models or different levels of performance are observed, does learning improve when the observer is informed of the performance quality prior to each observation trial or after each trial? We used a knock-down barrier task and asked participants to learn a new relative timing pattern that differed from that naturally emerging from the task constraints (Blandin et al., 1999 ). Following a physical execution pre-test, the participants observed two models demonstrating different levels of performance and were either informed of this performance prior to or after each observation trial. The results of the physical execution retention tests of the two experiments reported in the present study indicated that informing the observers of the demonstration quality they were about to see aided learning more than when this information was provided after each observation trial. Our results suggest that providing advanced information concerning the quality of the observation may help participants detect errors in the model's performance, which is something that novice participants have difficulty doing, and then learn from these observations.

Introduction

You are an avid golfer and you want to learn a new shot. How would you proceed? There is a fair chance that you will observe someone (live, on video, on Youtube, etc.) who knows how to perform this shot, and you will try to understand what to do and how to do it. Research clearly indicates that this learning strategy is successful because observation has been shown to promote the learning of a wide variety of motor skills (see McCullagh et al., 1989 ; Hodges et al., 2007 ; Vogt and Thomaschke, 2007 ; Ste-Marie et al., 2012 ; Lago-Rodríguez et al., 2014 , for reviews on observational learning). This is because observation has much commonality with physical practice, which is the first determinant of motor skill learning. Specifically, it has been demonstrated that variables, such as the amount of practice (Carroll and Bandura, 1990 ; Blandin, 1994 ), the frequency of knowledge of results ([KR], Badets and Blandin, 2004 , 2005 ; Badets et al., 2006 ), and the practice schedule (Blandin et al., 1994 ; Wright et al., 1997 ), affect learning via observational practice and physical practice in similar ways. These data led to the proposition that observation and physical practice use very similar processes. This proposition is supported by the results of neuroimaging studies that showed that an ensemble of neural structures (including the premotor cortex, the inferior parietal lobule, the superior temporal sulcus, the supplementary motor area, the cingulate gyrus, and the cerebellum), also called the “action observation network” (AON) (Kilner et al., 2009 ; Oosterhof et al., 2010 ), is activated both when individuals perform a given motor task and when they observe others performing that same motor task (Grafton et al., 1997 ; Buccino et al., 2001 ; Gallese et al., 2002 ; Cisek and Kalaska, 2004 ; Frey and Gerry, 2006 ; Cross et al., 2009 ; Dushanova and Donoghue, 2010 ; Rizzolatti and Fogassi, 2014 ; Rizzolatti et al., 2014 ).

Observation favors motor skill learning, but who should you observe to learn that new golf shot? An expert who masters the shot presumably will help you develop a reference of what to do and how to do it, but should you observe someone like you who is learning that shot and who presumably gives you a better chance of detecting and learning from errors or changes in strategy? Research has shown that observing both a skilled model (Martens et al., 1976 ; McCullagh et al., 1989 ; Lee et al., 1994 ; Al-Abood et al., 2001 ; Heyes and Foster, 2002 ; Hodges et al., 2003 ; Bird and Heyes, 2005 ) and a novice model leads to significant learning (Lee and White, 1990 ; McCullagh and Caird, 1990 ; Pollock and Lee, 1992 ; McCullagh and Meyer, 1997 ; Black and Wright, 2000 ; Buchanan et al., 2008 ; Buchanan and Dean, 2010 ; Hayes et al., 2010 ). However, recent results from our laboratory showed that observational learning of a new motor skill is improved following observation of both novice and expert models rather than either a novice or an expert model alone (Rohbanfard and Proteau, 2011 ; Andrieux and Proteau, 2013 , 2014 ). We believe that this “variable” observation format leads to not only the development of a good movement representation (expert observation) but also the development of efficient processes for error detection and correction (novice observation).

In the present study, the question of interest is a simple but important one. When using a variable schedule of observation, will learning be better when the observers are informed beforehand of the “quality” of the performance they are about to see or will it be better when the observers are left to evaluate the performances before receiving feedback. Informing the observers of what they are about to see may enable them to select whether they will observe to imitate or rather observe to detect error, or weaknesses in the model's performance, which might facilitate the development of these processes. Alternatively, having the participants evaluate the performance quality they observed may activate more elaborate cognitive processes than when this information is fed forward (e.g., error detection and recognition, or evaluation of alternative strategy), thus resulting in better learning of the task.

The task that we chose required the participants to change the relative timing pattern that naturally emerged from the task constraints (Collier and Wright, 1995 ; Blandin et al., 1999 ) to a new, imposed pattern of relative timing. This is similar to changing one's tempo when executing a serve in tennis or a drive in golf (Rohbanfard and Proteau, 2011 ). The participants observed two models demonstrating a wide variety of performances. In one group, observers were informed before each trial of the quality level (expert, advanced, intermediate, novice, or beginner performance) of what they were about to see, whereas a second group of observers was provided the same information only after each observation trial was completed.

Experiment 1

Participants.

Ninety right-handed students (45 males and 45 females; mean age = 20.5 years; SD = 0.9 years) from the Département de kinésiologie at the Université de Montréal participated in this experiment. The participants were naive to the purpose of the study and had no prior experience with the task, and all participants were self-declared as being right-handed. None of the participants reported neurological disorders, and all had normal or corrected-to-normal vision. The participants completed and signed individual consent forms before participation. The Health Sciences Research Ethics Committee of the Université de Montréal approved this experiment.

Apparatus and task

The apparatus was similar to that used by Rohbanfard and Proteau ( 2011 ). As illustrated in Figure ​ Figure1, 1 , it consisted of a wooden base (45 × 54 cm), three wooden barriers (11 × 8 cm), and a starting button embedded in a target (11 × 8 cm). The distance between the starting button and the first barrier was 15 cm. The distances of the remaining three segments of the task were 32, 18, and 29 cm, respectively. The barriers were placed perpendicular to the wooden base at the beginning of each trial, yielding a closed microswitch circuit. All of the microswitches were connected to a computer via the I/O port of an A–D converter (National Instruments, Austin, Texas, USA), and a millisecond timer was used to record both the total movement time (TMT) and the time required to complete each segment of the task (intermediate times, ITs).

Sketch of the apparatus . Participants had to leave the starting button and hit the first, second, and third barriers in a clockwise motion before finally reaching the target.

For the physical practice trials (see below), the participants sat close to the starting position in front of the apparatus. Then, from the starting button, the participants were asked to successively knock down the first, second, and third barriers (thus releasing the microswitches) and finally hit the target in a clockwise motion as illustrated in Figure ​ Figure1. 1 . Each segment of the task had to be completed in an IT of 300 ms, for a TMT of 1200 ms. The movement pattern, ITs, and TMT were illustrated on a poster located directly in front of the apparatus during all of the experimental phases.

Experimental phases and procedure

The participants were randomly assigned to one of the three groups, each consisting of 30 participants (15 females per group): control (C), feedforward KR and observation (FW), and observation and feedback KR (FB). All groups performed four experimental phases, spread over 2 successive days.

All participants received verbal instructions regarding TMT and ITs before the first experimental phase. The first experimental phase was a pre-test, in which all participants performed 20 physical practice trials without knowledge of the results (KR) on the TMT and the ITs.

The second phase was an acquisition phase and consisted of 60 observation trials for the participants in the two observation groups (FW and FB). These participants individually watched a video presentation of two models physically performing the experimental task. For each observation trial, KR concerning the model's performance (both TMT and ITs) was presented in ms (see Figure ​ Figure1) 1 ) either before the demonstration for the FW group or after the demonstration for the FB group. The model was changed every five trials (i.e., model 1: trials 1–5 and model 2: trials 6–10, and so on), for a total of 30 trials performed by one model and 30 trials performed by the other model. For both the FW and FB groups, the two models, who participated in previous work from our laboratory, were chosen because for both models, we had six video clips that illustrated performances in each one of five subcategories. Thus, the participants in the FW and FB groups could not associate one particular model with either a better or a poorer performance. An expert performance corresponded to a root mean square error (RMSE; see data analysis section for computation details) ranging between 0 and 15 ms; advanced, intermediate, novice, and beginner performances corresponded to RMSEs of 30–45 ms, 60–75 ms, 90–105 ms and 120+ ms, respectively. The participants in the FW and FB groups were informed of the model's performance in ms; they were also informed of the level of performance to which it referred. The resulting 30 trials of each model (five levels of performance × six repetitions) were randomized so that the five levels of performance were presented once into each set of five trials. To avoid physical imitation of the sequence, which could interfere with the observational processes, we asked the participants in the FW and FB groups to keep their hands on their thighs during the acquisition phase and to not reproduce the movements while watching the model(s). It was the Experimenter's main task to ensure that the participants complied with these instructions. The participants' overt behavior suggests that they did. Finally, participants of the control group did not physically practice or observe anything during this phase. Instead, they read a provided newspaper or magazine for the same duration as the observation for the other groups (approximately 10 min).

The third and fourth experimental phases were 10-min and 24-h retention phases. In each phase, all participants physically performed 20 trials with no KR. The participants were asked to complete each segment of the task in 300 ms, for a TMT of 1200 ms.

Data analysis

The data from the pre-test and the two retention phases were regrouped into blocks of five trials. For each successive block of five trials (i.e., trials 1–5, 6–10, etc.), we computed the absolute value of each participant's constant error (|CE|, the constant error indicates whether a participant undershot [negative value] or overshot [positive value] the total movement time) and variable error of the total movement time (VE or within-participant variability) to determine the accuracy and consistency of TMT, respectively. For intermediate times, we computed a RMSE, which indicates how much each participant deviated from the prescribed relative timing pattern in a single score. For each trial,

where ITi represents the intermediate time for segment “i,” and target represents the goal movement time for each segment of the task (i.e., 300 ms).

Because the data were not normally distributed (RMSE and time data are positively skewed), each dependent variable underwent a logarithmic transformation (ln). The transformed data for each dependent variable were independently submitted to an ANOVA contrasting three groups (C, FW, and FB) × three phases (pre-test, 10-min retention, 24-h retention) × four blocks of trials (1–5, 6–10, 11–15, and 16–20), with repeated measures on the last two factors. All of the significant main effects and simple main effects involving more than two means were broken down using Bonferroni's adjustment. For all comparisons, an effect was deemed significant if p < 0.05. Partial eta square ( η p 2 ) is the effect size reported for all significant effects (Cohen, 1988 ).

Total movement time

The ANOVA computed on |CE| (Figure ​ (Figure2, 2 , upper panel) revealed significant main effects for the variable group, F (2, 87) = 5.04, p = 0.08, η p 2 = 0.10, and phase, F (2, 174) = 5.16, p = 0.007, η p 2 = 0.06, as well as a significant phase × group interaction, F (4, 174) = 4.93, p = 0.001, η p 2 = 0.10. The breakdown of this interaction did not reveal any significant group differences in the pre-test ( F < 1). In the 10-min retention test, F (2, 87) = 10.12, p < 0.001, η p 2 = 0.19, the post-hoc comparisons revealed that the control group had a significantly larger | CE | than both the FW and the FB groups ( p < 0.05 in both cases), which did not differ significantly from one another ( p = 0.19). In the 24-h retention test, F (2, 87) = 4.34, p = 0.016, η p 2 = 0.09, the FW group had a significantly smaller |CE| than the control group ( p = 0.012) 1 .

Absolute constant error of TMT and root mean square error of relative timing as a function of the experimental phases and experimental groups (Experiment 1) . * p < 0.05. Error bars indicate standard error of the mean.

The ANOVA computed on VE (not shown) revealed significant main effects for the variable phase, F (2, 174) = 13.12, p < 0.001, η p 2 = 0.13, and block, F (3, 261) = 48.79, p < 0.001, η p 2 = 0.36. Post-hoc comparisons of the phase effect revealed a larger VE of total time in the pre-test than in both the 10-min and the 24-h retention tests ( p < 0.002 in both cases), which did not differ significantly from one another ( p = 0.68). The block main effect resulted from a significantly larger VE of total time for the first than for the three remaining blocks of trials ( p < 0.001 in all cases), which did not differ significantly from one another ( p >0.05 in all cases).

Relative timing

The ANOVA computed on the RMSE of relative timing revealed significant main effects for the variable group, F (2, 87) = 21.49, p < 0.001, η p 2 = 0.33, phase, F (2, 174) = 39.98, p < 0.001, η p 2 = 0.31 and block, F (3, 261) = 14.77, p < 0.001, η p 2 = 0.14, as well as a significant phase × group interaction, F (4, 174) = 12.81, p < 0.001, η p 2 = 0.23. The block main effect resulted from a significantly larger RMSE of relative timing for the first than for the three remaining blocks of trials ( p < 0.001 in all cases), which did not differ significantly from one another ( p >0.3 in all cases). More interestingly, the breakdown of the phase × group interaction (Figure ​ (Figure2, 2 , lower panel) did not reveal any significant group differences in the pre-test ( F < 1). In the 10-min, F (2, 87) = 14.85, p < 0.001, η p 2 = 0.34, and the 24-h retention tests, F (2, 87) = 23.23, p < 0.001, η p 2 = 0.35, although the FB group significantly outperformed the control group ( p = 0.001 in both cases), the FB group was, in turn, significantly outperformed by the FW group ( p = 0.001 and p = 0.02, respectively) 2 .

The present experiment was designed to extend our knowledge of the observation conditions that optimize learning of a new relative timing pattern. In this learning situation, two observation groups, which observed a variety of demonstrations, were provided KR either before or after each trial during the acquisition phase. Specifically, we wanted to assess whether learning would be enhanced when the learners know the “quality” or characteristics of a demonstration before they observe the demonstration. The results are straightforward.

First, as illustrated in Figure ​ Figure2, 2 , both the FW and the FB groups outperformed the control group on the retention tests. This was true for the learning of both the TMT and the relative timing. This expected result confirms previous findings that indicated that observation enables one to learn a new motor skill (see McCullagh et al., 1989 ; Hodges et al., 2007 ; Vogt and Thomaschke, 2007 ; Ste-Marie et al., 2012 ; Lago-Rodríguez et al., 2014 , for reviews on observational learning) and, notably, a new relative timing pattern (Rohbanfard and Proteau, 2011 ; Andrieux and Proteau, 2013 , 2014 ).

The most important finding of the present study is that the FB group was outperformed by the FW group in the retention tests. Although the two groups observed the same demonstrations, the results revealed that learning is optimized when one is given advance knowledge of the quality or characteristics of the witnessed demonstration. This finding fits well with previous reports from our laboratory (Rohbanfard and Proteau, 2011 ; Andrieux and Proteau, 2013 ) showing that a mixed observation regimen, in which the observers know who is the expert model and who is the novice model, favors learning of a new relative timing pattern better than either expert or novice observation alone.

Having advance knowledge that a less than perfect demonstration will be shown may be critical, considering that it has been reported that novice participants, such as in the present study, are not good at evaluating the quality of a demonstration. For example, Aglioti et al. ( 2008 ) had novice and expert basketball players observe video clips showing free-throw shots, and the video clips were stopped at different times before or immediately after the ball release. Expert basketball players and coaches/specialized journalists were better and quicker at predicting the fate of the shot (successful or not) than were novices (for similar results see also Wright et al., 2010 ; Abreu et al., 2012 ; Tomeo et al., 2013 ; Balser et al., 2014 ; Candidi et al., 2014 ; Renden et al., 2014 ).

The advantage of the FW over the FB protocol is important and, as far as we know, a similar finding has not been reported thus far. Therefore, a replication of this finding appeared important. In addition, we wondered whether the advantage noted for the FW protocol occurred only after a limited amount of observation. Finally, we were curious to see whether alternating the FW and the FB protocol would result in additive effects. We conducted Experiment 2 to address these questions.

Experiment 2

The 60 participants who volunteered for this experiment were drawn from the same population as that of Experiment 1 (36 males and 24 females; mean age = 22.7 years; SD = 4.9 years). The participants were naive concerning the purpose of this study and had no prior experience with the task. They completed and signed individual consent forms before participation. The Health Sciences Research Ethics Committee of the Université de Montréal approved this experiment.

Apparatus, task, experimental phases, procedure, and data analysis

We used the same task, apparatus, and procedures as in Experiment 1. The major difference between the present experiment and Experiment 1 is that participants performed two acquisition sessions, which led to a total of five experimental phases: pre-test, acquisition 1, immediate retention test, acquisition 2, and 24-h retention test.

The participants were randomly assigned to one of the three groups, each consisting of 20 participants (8 females per group): feedforward KR and observation during both acquisition 1 and 2 (FW1-2); feedforward observation and KR during acquisition 1 but observation and feedback KR during acquisition 2 (FW/FB); and observation and KR feedback during both acquisition 1 and 2 (FB1-2). We used the same video and models as in Experiment 1; however, the order of video presentation was different in acquisition 2 from that in acquisition 1. All participants were also informed that they would perform the same task after each acquisition phase, but with no KR concerning their own performance.

We used the same dependent variables and data transformation as in Experiment 1. For each dependent variable, we conducted a two-way ANOVA contrasting the three groups (FW1-2, FW/FB and FB1-2) × three experimental phases (pre-test, immediate retention, and 24-h retention). All of the significant main effects and simple main effects involving more than two means were broken down using Bonferroni's adjustment. For all comparisons, an effect was deemed significant if p < 0.05. Partial eta square ( η p 2 ) is the effect size reported for all significant effects (Cohen, 1988 ).

The ANOVA computed for the |CE| of movement time (Figure ​ (Figure3) 3 ) revealed significant main effects for the variable group, F (2, 57) = 8.13, p = 0.001, η p 2 = 0.22, and phase, F (2, 114) = 21.13, p < 0.001, η p 2 = 0.27, as well as a significant group × phase interaction, F (4, 114) = 2.57, p = 0.042, η p 2 = 0.08. The breakdown of this interaction did not reveal any significant group differences in the pre-test ( F < 1). In the immediate retention test, F (2, 57) = 10.27, p < 0.002, η p 2 = 0.27, the FB1-2 group had a significantly larger | CE | than both the FW1-2 and the FW/FB groups ( p < 0.001 in both cases), which did not differ significantly from one another ( p >0.20). In the 24-h retention test, F (2, 57) = 3.19, p = 0.049, η p 2 = 0.10, the FW1-2 group had a slightly smaller |CE| than the FB1-2 group ( p = 0.079) 3 .

Absolute constant error of TMT as a function of the experimental phases and experimental groups (Experiment 2) . * p < 0.05. Error bars indicate standard error of the mean.

The ANOVA computed on VE (not shown) revealed significant main effects for the variable group, F (2, 57) = 7.82, p = 0.001, η p 2 = 0.21, and phase, F (2, 114) = 21.10, p < 0.001, η p 2 = 0.27, as well as a significant group × phase interaction, F (4, 114) = 4.38, p = 0.002, η p 2 = 0.13. The breakdown of this interaction did not reveal any significant group differences in the pre-test ( F < 1) and in the 24-h retention test, F (2, 57) = 1.26, p >0.20. In the immediate retention test, F (2, 57) = 10.26, p < 0.002, η p 2 = 0.27, the FB1-2 group (62.7 ms) had a significantly larger VE than both the FW1-2 (51.1 ms) and the FW/FB (53.4 ms) groups ( p < 0.001 in both cases), which did not differ significantly from one another ( p >0.20) 4 .

The ANOVA computed for the RMSE of relative timing revealed significant main effects for the variable group, F (2, 57) = 4.86, p = 0.01, η p 2 = 0.15, and phase, F (2, 114) = 78.21, p < 0.001, η p 2 = 0.58. There was a significantly larger RMSE of relative timing in the pre-test than in both the immediate retention test and the 24-h retention test ( p < 0.001 in both cases; see Figure ​ Figure4, 4 , right panel), which did not differ significantly from one another ( p >0.20). Finally, the FW1-2 and the FW/FB groups outperformed the FB1-2 group ( p = 0.01 and p = 0.07; see Figure ​ Figure4, 4 , left panel) but did not significantly differ from one another ( p >0.20).

Root mean square error of relative timing (Experiment 2) as a function of the experimental groups (left panel) and experimental phases (right panel) . * p < 0.05. Error bars indicate standard error of the mean.

As expected, the decrease in error noted when going from pre-test to the retention tests supports previous findings indicating that observation aids learning of a new relative timing pattern (Blandin et al., 1999 ; Rohbanfard and Proteau, 2011 ; Andrieux and Proteau, 2013 , 2014 ). More importantly, the results of Experiment 2 replicated those of Experiment 1, in that the FW1-2 group outperformed the FB1-2 group. Therefore, it can be safely concluded that learning to change the relative timing pattern that naturally emerges from the task's constraints to a new, imposed relative timing through observation is favored when one is informed of the model's performance prior to rather than after observation. Finally, the results also showed that what has been learned in a FB protocol does not add up to what can be learned in a FW protocol.

General discussion

The main goal of the present study was to determine when in an observation protocol should KR concerning the model performance be provided, i.e., before or after each demonstration. The results of the two experiments of the present study clearly indicated that being informed of the model's performance before each demonstration favored learning of a new relative timing pattern better than when the observer was informed of the model's performance after each demonstration. Moreover, the results of Experiment 2 suggest that the advantage of the FW over the FB protocol remained significant even when the number of observation trials was doubled. Concerning this last point, we do not argue that a FW protocol should be favored in all cases and with all levels of expertise of the observers. Rather, we underline that the effect is reliable when novice observers are considered.

Our results may indicate that a feedforward observation protocol prepares the observer to engage specifically in either imitation processes when an expert or advanced performance is shown or in error detection processes when a beginner or novice performance is presented. This idea fits well with previous work from Decety et al. ( 1997 ), which stated that the patterns of brain activation during action observation depend on both the nature of the required executive processing and the extrinsic properties of the action presented. Specifically, these authors demonstrated that different areas of the brain become more active when one observes to recognize, which could be the case when observing a novice model or a poor or intermediate performance, and when one observes to imitate, which is likely to be the case when observing an expert model.

An alternative explanation of our findings could be that a FW protocol results in a “deactivation” of the AON when the participants were explicitly informed that a poor demonstration would follow. For instance, in an object-lifting task, it has been shown that the modulation of motor evoked potential (MEP) by transcranial magnetic stimulation (TMS) during observation of the lifting action is scaled to the force required to perform the grasping and lifting action (Alaerts et al., 2010a ). It was also shown that when visual cues suggested that the object was heavier than in really was, the MEP modulation depended primarily on the observed kinematic profile rather than on the apparent weight of the object (Alaerts et al., 2010b ; Senot et al., 2011 ). However, in a study by Senot et al. ( 2011 ), false explicit information concerning the weight of the object was provided in one experimental condition. This resulted in a conflict between the expected kinematic profile given the announced weight and the actual kinematic profile of the grasping and lifting action, leading to a “general inhibition of the corticospinal system.” Stated differently, at least a portion of the AON had been turned off. Therefore, it could be that the participants in our study turned off the AON when poor performance of the model was expected, leaving the AON active only for good trials.

This proposition is difficult to reconcile, however, with recent reports from our laboratory showing that observing both an expert and a novice model resulted in better learning of a new relative timing pattern than observing either a novice model or an expert model alone. If one could turn off the AON when informed that a poor demonstration will be shown (i.e., a novice model), then learning of the mixed observation group would have matched and not surpassed that of the expert observation group. Rather, going back to our first proposition, we suggest that a FW protocol helps novice performers detect and quantify errors in the model's performance, something they usually do poorly (Aglioti et al., 2008 ; Wright et al., 2010 ; Abreu et al., 2012 ; Tomeo et al., 2013 ; Balser et al., 2014 ; Candidi et al., 2014 ; Renden et al., 2014 ). In turn, the better detection and quantification of the model's performance may favor the development of inverse (Jordan, 1996 ) and forward models (Wolpert and Miall, 1996 ) of motor control.

In conclusion, observation is a powerful learning tool that is available to anyone and requires only minimal equipment to be used. It is now well-demonstrated that the benefits of observation for modifying the relative timing (i.e., tempo) of motor skill are enhanced when one has access to a variety of performances ranging from novices to experts either through variable or mixed observation schedules. The results of the present study suggest that those benefits are optimized if the observer knows beforehand the quality of the performance that she or he is about to observe during the first observation session. This could be very important in a classroom context in which a teacher/trainer would use a video observation protocol. For example, if the intention of the observer is to learn a specific aspect of a golf swing, it is likely that the result of the swing (i.e., the ball flight) will not be shown on the video. Therefore, the observer would not be able to “guess” the expertise of the model from the result of the swing and, as we have shown in the present study, learn better if he or she was informed in advance of the quality of what he or she is about to observe.

Author contributions

All authors listed, have made substantial, direct and intellectual contribution to the work, and approved it for publication.

This work was supported by a Discovery Grant (LP) provided by the Natural Sciences and Engineering Research Council of Canada (grant no. 111280-2013).

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

1 To ascertain that the differences noted in the two retention tests between the control group and the FW and FB groups resulted from a significant decrease in the |CE| of total movement time, in a supplementary analysis we decomposed the group × phase interaction reported in the main text by computing a separate ANOVA for each group. The results revealed that for the control and the FB groups, the |CE| of total movement time did not significantly differ across the phases, [ F (2, 86) = 1.58, p = 0.21, η p 2 = 0.04, and F (2, 86) < 1, p = 0.37, η p 2 = 0 . 02 ], respectively. On the contrary, for the FW groups, there was a significant main effect of the phases, F (2, 86) = 11.60, p < 0.01, η p 2 = 0 . 1 , that revealed a significant decrease in the |CE| of total movement time going from the pre-test to the two retention tests ( p < 0.01), which did not differ significantly from one another ( p >0.10).

2 As we did for the |CE| of total movement time, in a supplementary analysis we decomposed the group × phase interaction reported in the main text for the RMSE of relative timing by computing a separate ANOVA for each group. The results revealed that for the control group, the RMSE of relative timing did not significantly differ across the phases, F (2, 86) = 0.32, p = 0.72, η p 2 = 0 . 01 . On the contrary, for both the FB and the FW groups, there was a significant main effect of the phases [FB: F (2, 86) = 11.82, p < 0.001, η p 2 = 0 . 22 ; FW: F (2, 86) = 35.62, p < 0.001, η p 2 = 0 . 45 ] that revealed a significant decrease in the RMSE of relative timing going from the pre-test to the two retention tests ( p < 0.01), which did not differ significantly from one another ( p > 0.10).

3 As we did in Experiment 1, in a supplementary analysis we decomposed the group × phase interaction reported in the main text by computing a separate ANOVA for each group. The results revealed that for the FB1-2 group, the |CE| of total movement time did not significantly differ across the phases, F (2, 56) < 1, p = 0.45, η p 2 = 0 . 03 . On the contrary, for both the FW1-2 and FW-FB groups, there was a significant main effect of the phases, [FW1-2: F (2, 56) = 8.20, p = 0.001, η p 2 = 0 . 23 ; FW-FB: F (2, 56) = 13.76, p < 0.001, η p 2 = 0 . 33 ] that, for both groups, revealed a significant decrease in the |CE| of total movement time going from the pre-test to the two retention tests ( p < 0.01), which did not differ significantly from one another ( p >0.10).

4 For the VE of total movement time, the breakdown of the group × phase interaction revealed a significant main effect of phases for all three groups [FW1-2: F (2, 56) = 10.27, p < 0.001, η p 2 = 0 . 27 ; FW-FB: F (2, 56) = 4.71, p = 0.013, η p 2 = 0 . 14 ; FB1-2: F (2, 56) = 7.38, p = 0.001, η p 2 = 0 . 21 ]. For the FW1-2 and the FB1-2 groups, pos-hoc comparisons revealed a significantly larger VE in pre-test than in both retention tests ( p < 0.01), which did not differ significantly from one another ( p >0.30). For the FW-FB group, the VE of total movement time was significantly larger in the pre-test than in the 24-h retention test ( p < 0.01).

• Abreu A. M., Macaluso E., Azevedo R. T. (2012). Action anticipation beyond the action observation network: a functional magnetic resonance imaging study in expert basketball players . Eur. J. Neurosci. 35 , 1646–1654. 10.1111/j.1460-9568.2012.08104.x [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Aglioti S. M., Cesari P., Romani M., Urgesi C. (2008). Action anticipation and motor resonance in elite basketball players . Nat. Neurosci. 11 , 1109–1116. 10.1038/nn.2182 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Al-Abood S. A., Davids K. F., Bennett S. J. (2001). Specificity of task constraints and effects of visual demonstrations and verbal instructions in directing learners' search during skill acquisition . J. Mot. Behav. 33 , 295–305. 10.1080/00222890109601915 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Alaerts K., Senot P., Swinnen S. P., Craighero L., Wenderoth N., Fadiga L. (2010a). Force requirements of observed object lifting are encoded by the observer's motor system: a TMS study . Eur. J. Neurosci. 31 , 1144–1153. 10.1111/j.1460-9568.2010.07124.x [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Alaerts K., Swinnen S. P., Wenderoth N. (2010b). Observing how others lift light or heavy objects: which visual cues mediate the encoding of muscular force in the primary motor cortex? Neuropsychologia 48 , 2082–2090. 10.1016/j.neuropsychologia.2010.03.029 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Andrieux M., Proteau L. (2013). Observation learning of a motor task: who and when? Exp. Brain Res. 229 , 125–137. 10.1007/s00221-013-3598-x [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Andrieux M., Proteau L. (2014). Mixed observation favors motor learning through better estimation of the model's performance . Exp. Brain Res. 232 , 3121–3132. 10.1007/s00221-014-4000-3 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Badets A., Blandin Y. (2004). The role of knowledge of results frequency in learning through observation . J. Mot. Behav. 36 , 62–70. 10.3200/JMBR.36.1.62-70 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Badets A., Blandin Y. (2005). Observational learning: effects of bandwidth knowledge of results . J. Mot. Behav. 37 , 211–216. 10.3200/JMBR.37.3.211-216 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Badets A., Blandin Y., Wright D. L., Shea C. H. (2006). Error detection processes during observational learning . Res. Q. Exerc. Sport 77 , 177–184. 10.1080/02701367.2006.10599352 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Balser N., Lorey B., Pilgramm S., Naumann T., Kindermann S., Stark R., et al.. (2014). The influence of expertise on brain activation of the action observation network during anticipation of tennis and volleyball serves . Front. Hum. Neurosci. 8 : 568 . 10.3389/fnhum.2014.00568 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Bird G., Heyes C. (2005). Effector-dependent learning by observation of a finger movement sequence . J. Exp. Psychol. Hum. Percept. Perform. 31 , 262–275. 10.1037/0096-1523.31.2.262 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Black C. B., Wright D. L. (2000). Can observational practice facilitate error recognition and movement production? Res. Q. Exerc. Sport 71 , 331–339. 10.1080/02701367.2000.10608916 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Blandin Y. (1994). Processus Cognitifs Impliqués Lors de L'apprentissage de Tâches de Synchronisation Spatio-Temporelle Sous Différentes Conditions de Pratique et D'observation D'un Sujet Modèle, Thèse De Doctorat Inédite . [ Cognitive Processes pu into Play during the Learning of A Spatiotemporal Timing Task throught Different Regimens of Practice or Observation , Unpublished doctoral dissertation], Université de Montréal.
• Blandin Y., Lhuisset L., Proteau L. (1999). Cognitive processes underlying observational learning of motor skills . Q. J. Exp. Psychol. 52 , 957–979. 10.1080/713755856 [ CrossRef ] [ Google Scholar ]
• Blandin Y., Proteau L., Alain C. (1994). On the cognitive processes underlying contextual interference and observational learning . J. Mot. Behav. 26 , 18–26. 10.1080/00222895.1994.9941657 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Buccino G., Binkofski F., Fink G. R., Fadiga L., Fogassi L., Gallese V., et al.. (2001). Action observation activates premotor and parietal areas in a somatotopic manner: an fMRI study . Eur. J. Neurosci. 13 , 400–404. 10.1046/j.1460-9568.2001.01385.x [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Buchanan J. J., Dean N. J. (2010). Specificity in practice benefits learning in novice models and variability in demonstration benefits observational practice . Psychol. Res. 74 , 313–326. 10.1007/s00426-009-0254-y [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Buchanan J. J., Ryu Y. U., Zihlman K., Wright D. L. (2008). Observational practice of relative but not absolute motion features in a single-limb multi-joint coordination task . Exp. Brain Res. 191 , 157–169. 10.1007/s00221-008-1512-8 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Candidi M., Sacheli L. M., Mega I., Aglioti S. M. (2014). Somatotopic mapping of piano fingering errors in sensorimotor experts: TMS studies in pianists and visually trained musically naives . Cereb. Cortex 24 , 435–443. 10.1093/cercor/bhs325 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Carroll W. R., Bandura A. (1990). Representational guidance of action production in observational learning: a causal analysis . J. Mot. Behav. 22 , 85–97. 10.1080/00222895.1990.10735503 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Cisek P., Kalaska J. F. (2004). Neural correlates of mental rehearsal in dorsal premotor cortex . Nature 431 , 993–996. 10.1038/nature03005 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Cohen J. (1988). Statistical Power Analysis for the Behavioral Sciences . Hillsdale, NJ: Lawrence Erlbaum. [ Google Scholar ]
• Collier G. L., Wright C. E. (1995). Temporal rescaling of sample and complex rations in rhythmic tapping . J. Exp. Psychol. Hum. Percept. Perform. 21 , 602–627. 10.1037/0096-1523.21.3.602 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Cross E. S., Kraemer D. J. M., Hamilton A. F. D., Kelley W. M., Grafton S. T. (2009). Sensitivity of the action observation network to physical and observational learning . Cereb. Cortex 19 , 315–326. 10.1093/cercor/bhn083 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Decety J., Grèzes J., Costes N., Perani D., Jeannerod M., Procyk E., et al.. (1997). Brain activity during observation of actions - influence of action content and subject's strategy . Brain 120 , 1763–1777. 10.1093/brain/120.10.1763 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Dushanova J., Donoghue J. (2010). Neurons in primary motor cortex engaged during action observation . Eur. J. Neurosci. 31 , 386–398. 10.1111/j.1460-9568.2009.07067.x [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Frey S. H., Gerry V. E. (2006). Modulation of neural activity during observational learning of actions and their sequential orders . J. Neurosci. 26 , 13194–13201. 10.1523/JNEUROSCI.3914-06.2006 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Gallese V., Fadiga L., Fogassi L., Rizzolatti G. (2002). Action representation and the inferior parietal lobule , in Common Mechanisms in Perception and Action: Attention and Performance, Vol. XIX , eds Prinz W., Hommel B. (Oxford: Oxford University Press; ), 247–266. [ Google Scholar ]
• Grafton S. T., Fadiga L., Arbib M. A., Rizzolatti G. (1997). Promotor cortex activation during observation and naming of familiar tools . Neuroimage 6 , 231–236. 10.1006/nimg.1997.0293 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Hayes S. J., Elliott D., Bennett S. J. (2010). General motor representations are developed during action-observation . Exp. Brain Res. 204 , 199–206. 10.1007/s00221-010-2303-6 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Heyes C. M., Foster C. L. (2002). Motor learning by observation: evidence from a serial reaction time task . Q. J. Exp. Psychol. 55 , 593–607. 10.1080/02724980143000389 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Hodges N. J., Chua R., Franks I. M. (2003). The role of video in facilitating perception and action of a novel coordination movement . J. Mot. Behav. 35 , 247–260. 10.1080/00222890309602138 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Hodges N. J., Williams A. M., Hayes S. J., Breslin G. (2007). What is modelled during observational learning? J. Sports Sci. 25 , 531–545. 10.1080/02640410600946860 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Jordan M. I. (1996). Computational aspects of motor control and motor learning , in Handbook of Perception and Action: Vol. 2, Motor Skills , eds Heuer H., Keele S. W. (New York, NY: Academic Press; ), 71–120. [ Google Scholar ]
• Kilner J. M., Neal A., Weiskopf N., Friston K. J., Frith C. D. (2009). Evidence of mirror neurons in human inferior frontal gyrus . J. Neurosci. 29 , 10153–10159. 10.1523/JNEUROSCI.2668-09.2009 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Lago-Rodríguez A., Cheeran B., Koch G. (2014). The role of mirror neurons in observational motor learning: an integrative review . Eur. J. Human Mov. 32 , 82–103. [ Google Scholar ]
• Lee T. D., Swinnen S. P., Serrien D. J. (1994). Cognitive effort and motor learning . Quest 46 , 328–344. 10.1080/00336297.1994.10484130 [ CrossRef ] [ Google Scholar ]
• Lee T. D., White M. A. (1990). Influence of an unskilled models practice schedule on observational motor learning . Hum. Mov. Sci. 9 , 349–367. 10.1016/0167-9457(90)90008-2 [ CrossRef ] [ Google Scholar ]
• Martens R., Burwitz L., Zuckerman J. (1976). Modeling effects on motor-performance . Res. Q. 47 , 277–291. [ PubMed ] [ Google Scholar ]
• McCullagh P., Caird J. K. (1990). Correct and learning models and the use of model knowledge of results in the acquisition and retention of a motor skill . J. Human Mov. Stud. 18 , 107–116. [ Google Scholar ]
• McCullagh P., Meyer K. N. (1997). Learning versus correct models: influence of model type on the learning of a free-weight squat lift . Res. Q. Exerc. Sport 68 , 56–61. 10.1080/02701367.1997.10608866 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• McCullagh P., Weiss M. R., Ross D. (1989). Modeling considerations in motor skill acquisition and performance: an integrated approach . Exerc. Sport Sci. Rev. 17 , 475–513. [ PubMed ] [ Google Scholar ]
• Oosterhof N. N., Wiggett A. J., Diedrichsen J., Tipper S. P., Downing P. E. (2010). Surface-based information mapping reveals crossmodal vision-action representations in human parietal and occipitotemporal cortex . J. Neurophysiol. 104 , 1077–1089. 10.1152/jn.00326.2010 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Pollock B. J., Lee T. D. (1992). Effects of the model's skill level on observational motor learning . Res. Q. Exerc. Sport 63 , 25–29. 10.1080/02701367.1992.10607553 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Renden P. G., Kerstens S., Oudejans R. R. D., Cañal-Bruland R. (2014). Foul or dive? Motor contributions to judging ambiguous foul situations in football . Eur. J. Sport Sci. 14 ( Suppl. 1 ), S221–S227. 10.1080/17461391.2012.683813 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Rizzolatti G., Cattaneo L., Fabbri-Destro M., Rozzi S. (2014). Cortical mechanisms underlying the organization of goal-directed actions and mirror neuron-based action understanding . Physiol. Rev. 94 , 655–706. 10.1152/physrev.00009.2013 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Rizzolatti G., Fogassi L. (2014). The mirror mechanism: recent findings and perspectives . Philos. Trans. R. Soc. Lond. Ser. B Biol. Sci. 369 :20130420. 10.1098/rstb.2013.0420 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Rohbanfard H., Proteau L. (2011). Learning through observation: a combination of expert and novice models favors learning . Exp. Brain Res. 215 , 183–197. 10.1007/s00221-011-2882-x [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Senot P., D'Ausilio A., Franca M., Caselli L., Craighero L., Fadiga L. (2011). Effect of weight-related labels on corticospinal excitability during observation of grasping: a TMS study . Exp. Brain Res. 211 , 161–167. 10.1007/s00221-011-2635-x [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Ste-Marie D. M., Law B., Rymal A. M., Jenny O., Hall C., McCullagh P. (2012). Observation interventions for motor skill learning and performance: an applied model for the use of observation . Int. Rev. Sport Exerc. Psychol. 5 , 145–176. 10.1080/1750984X.2012.665076 [ CrossRef ] [ Google Scholar ]
• Tomeo E., Cesari P., Aglioti S. M., Urgesi C. (2013). Fooling the kickers but not the goalkeepers: behavioral and neurophysiological correlates of fake action detection in soccer . Cereb. Cortex 23 , 2765–2778. 10.1093/cercor/bhs279 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Vogt S., Thomaschke R. (2007). From visuo-motor interactions to imitation learning: behavioural and brain imaging studies . J. Sports Sci. 25 , 497–517. 10.1080/02640410600946779 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Wolpert D. M., Miall R. C. (1996). Forward models for physiological motor control . Neural Netw. 9 , 1265–1279. 10.1016/S0893-6080(96)00035-4 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Wright D. L., Li Y., Coady W. (1997). Cognitive processes related to contextual interference and observational learning: a replication of Blandin, Proteau and Alain (1994) . Res. Q. Exerc. Sport 68 , 106–109. 10.1080/02701367.1997.10608872 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Wright M. J., Bishop D. T., Jackson R. C., Abernethy B. (2010). Functional MRI reveals expert-novice differences during sport-related anticipation . Neuroreport 21 , 94–98. 10.1097/WNR.0b013e328333dff2 [ PubMed ] [ CrossRef ] [ Google Scholar ]

6.1 What Is Learning?

Instincts and reflexes are innate behaviors—they occur naturally and do not involve learning. In contrast, learning is a change in behavior or knowledge that results from experience. There are three main types of learning: classical conditioning, operant conditioning, and observational learning. Both classical and operant conditioning are forms of associative learning where associations are made between events that occur together. Observational learning is just as it sounds: learning by observing others.

6.2 Classical Conditioning

Pavlov’s pioneering work with dogs contributed greatly to what we know about learning. His experiments explored the type of associative learning we now call classical conditioning. In classical conditioning, organisms learn to associate events that repeatedly happen together, and researchers study how a reflexive response to a stimulus can be mapped to a different stimulus—by training an association between the two stimuli. Pavlov’s experiments show how stimulus-response bonds are formed. Watson, the founder of behaviorism, was greatly influenced by Pavlov’s work. He tested humans by conditioning fear in an infant known as Little Albert. His findings suggest that classical conditioning can explain how some fears develop.

6.3 Operant Conditioning

Operant conditioning is based on the work of B. F. Skinner. Operant conditioning is a form of learning in which the motivation for a behavior happens after the behavior is demonstrated. An animal or a human receives a consequence after performing a specific behavior. The consequence is either a reinforcer or a punisher. All reinforcement (positive or negative) increases the likelihood of a behavioral response. All punishment (positive or negative) decreases the likelihood of a behavioral response. Several types of reinforcement schedules are used to reward behavior depending on either a set or variable period of time.

6.4 Observational Learning (Modeling)

According to Bandura, learning can occur by watching others and then modeling what they do or say. This is known as observational learning. There are specific steps in the process of modeling that must be followed if learning is to be successful. These steps include attention, retention, reproduction, and motivation. Through modeling, Bandura has shown that children learn many things both good and bad simply by watching their parents, siblings, and others.

As an Amazon Associate we earn from qualifying purchases.

This book may not be used in the training of large language models or otherwise be ingested into large language models or generative AI offerings without OpenStax's permission.

Want to cite, share, or modify this book? This book uses the Creative Commons Attribution License and you must attribute OpenStax.

Access for free at https://openstax.org/books/psychology-2e/pages/1-introduction

• Authors: Rose M. Spielman, William J. Jenkins, Marilyn D. Lovett
• Publisher/website: OpenStax
• Book title: Psychology 2e
• Publication date: Apr 22, 2020
• Location: Houston, Texas
• Book URL: https://openstax.org/books/psychology-2e/pages/1-introduction
• Section URL: https://openstax.org/books/psychology-2e/pages/6-summary

© Jan 6, 2024 OpenStax. Textbook content produced by OpenStax is licensed under a Creative Commons Attribution License . The OpenStax name, OpenStax logo, OpenStax book covers, OpenStax CNX name, and OpenStax CNX logo are not subject to the Creative Commons license and may not be reproduced without the prior and express written consent of Rice University.

• Social Sciences

What is Observational Learning?

Format: Other

Academic level: College

Paper type: Essay (Any Type)

Downloads: 0

Observational learning involves a process of learning through observing others' behavior and attitudes (Borsa et al. 2019). According to Albert Bandura, a person's environment determines the behavior of people in society. In observational learning, a person watches others, retains the information, and imitates the behavior observed. This process of learning is essential as it helps children acquire positive behavioral traits and responses while observing others. This essay will discuss observational learning and explain the four methods that Bandura said were essential for observational learning. 

Albert Bandura aimed at explaining how children observe and imitate behaviors in social environments. In his explanation, he used four processes, that is, attentional, retentional, behavioral production, and motivational. The attentional process entails directing the mind to an object or a person one is intending to observe their behaviors. Retention, on the other hand, refers to internalizing information observed in memories. Behavior reproduction involves applying the learned traits and behavior into one's life whenever required. Finally, motivation entails the will to perform the learned or observed behavior. 

Delegate your assignment to our experts and they will do the rest.

Observational learning would be difficult in a situation where children observe and imitate negative behaviors from their parents. Based on the processes as mentioned earlier of observational learning, a child notices a negative behavior from the parents, internalizes the traits, and imitates the characteristics in their life experiences. This results in setbacks and obstacles toward children's growth. 

Learners may facilitate observational learning in schools. This happens when learners observe the behavior of others and apply it in their own life experiences. Observational learning can be more natural when attention, retention, behavior reproduction, and motivation are involved. Learners will quickly grasp information and use it to change their own lives. 

Borsa, D., Heess, N., Piot, B., Liu, S., Hasenclever, L., Munos, R., & Pietquin, O. (2019, May). Observational learning by reinforcement learning. In  Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems  (pp. 1117-1124). International Foundation for Autonomous Agents and Multiagent Systems. 

• The Effects of Post-Traumatic Stress Disorder
• Abnormal Child Psychology: Definition, Symptoms, and Treatment

Select style:

StudyBounty. (2023, September 15). What is Observational Learning? . https://studybounty.com/what-is-observational-learning-essay

Hire an expert to write you a 100% unique paper aligned to your needs.

Related essays

We post free essay examples for college on a regular basis. Stay in the know!

How to Do a SWOT Analysis for Your Business

Letter of consent for research study, mental representations and the mind-brain relationship.

Words: 1796

Building a Healthy Marriage

Words: 1266

Devastating Impacts of Domestic Violence

Words: 2437

How Emotions Affect Marketing and Sales

Words: 1113

Running out of time ?

Entrust your assignment to proficient writers and receive TOP-quality paper before the deadline is over.

Observational Learning Essays

Social learning theory, popular essay topics.

• American Dream
• Artificial Intelligence
• Black Lives Matter
• Bullying Essay
• Career Goals Essay
• Causes of the Civil War
• Child Abusing
• Civil Rights Movement
• Community Service
• Cultural Identity
• Cyber Bullying
• Death Penalty
• Depression Essay
• Domestic Violence
• Freedom of Speech
• Global Warming
• Gun Control
• Human Trafficking
• I Believe Essay
• Immigration
• Importance of Education
• Israel and Palestine Conflict
• Leadership Essay
• Legalizing Marijuanas
• Mental Health
• National Honor Society
• Police Brutality
• Pollution Essay
• Racism Essay
• Romeo and Juliet
• Same Sex Marriages
• Social Media
• The Great Gatsby
• The Yellow Wallpaper
• Time Management
• To Kill a Mockingbird
• Violent Video Games
• What Makes You Unique
• Why I Want to Be a Nurse
• Send us an e-mail