Observational Learning

Observational Learning

Observational Learning

Discussion Observational Learning

Discussion Observational Learning

I’m trying to study for my Psychology course and I need some help to understand this question.

Consider a behavior that you would like to teach someone. This could be a friend, a child, a co-worker, etc. Describe the behavior and select one of the learning theories we learned about this week (i.e. observational learning, operant conditioning, etc.) as the framework for how you would teach the person that behavior. Although in real life you may use more than one of these theories to teach behavior, for the purposes of this academic exercise choose ONLY ONE theory. Explain how you would ensure they have learned the behavior and why you felt that approach would work best for the particular behavior and setting. What challenges do you encounter to the learning process using your planned approach?

observational learning, method of learning that consists of observing and modeling another individual’s behavior, attitudes, or emotional expressions. Although it is commonly believed that the observer will copy the model, American psychologist Albert Bandura stressed that individuals may simply learn from the behavior rather than imitate it. Observational learning is a major component of Bandura’s social learning theory. He also emphasized that four conditions were necessary in any form of observing and modeling behavior: attention, retention, reproduction, and motivation.

Conditions for observational learning
Attention
If an organism is going to learn anything from a model, he or she must be paying attention to it and the behavior it exhibits. Many conditions can affect the observer’s attention. For instance, if the observer is sleepy, ill, or distracted, he or she will be less likely to learn the modeled behavior and imitate it at a later date. In addition, the characteristics of the model have an influence on the observer’s attention. Bandura and others have shown that humans pay more attention to models that are attractive, similar to them, or prestigious and are rewarded for their behaviors. This explains the appeal that athletes have on the behavior of young children and that successful adults have on college students. Unfortunately, this aspect of modeling can also be used in detrimental ways. For example, if young children witness gang members gaining status or money, they may imitate those behaviors in an effort to gain similar rewards.

Sigmund Freud
READ MORE ON THIS TOPIC
motivation: Observational learning
In the third type of learning technique, observational learning, or modeling, a new behaviour is learned simply by watching…
Retention
The second requirement of observational learning is being able to remember the behavior that was witnessed. If the human or animal does not remember the behavior, there is a less than probable chance that they will imitate it.

Discussion Observational LearningReproduction
This requisite of behavior concerns the physical and mental ability of the individual to copy the behavior he or she observed. For instance, a young child may observe a college basketball player dunk a ball. Later, when the child has a basketball, he or she may attempt to dunk a ball just like the college player. However, the young child is not nearly as physically developed as the older college player and, no matter how many times he or she tries, will not be able to reach the basket to dunk the ball. An older child or an adult might be able to dunk the ball but likely only after quite a bit of practice. Similarly, a young colt observes another horse in the herd jump over the creek while running in the pasture. After observing the model’s jumping behavior, the colt attempts to do the same only to land in the middle of the creek. He simply was not big enough or did not have long enough legs to clear the water. He could, however, after physical growth and some practice, eventually be able to replicate the other horse’s jump.

Motivation
Perhaps the most important aspect of observational learning involves motivation. If the human or animal does not have a reason for imitating the behavior, then no amount of attention, retention, or reproduction will overcome the lack of motivation. Bandura identified several motivating factors for imitation. These include knowing that the model was previously reinforced for the behavior, being offered an incentive to perform, or observing the model receiving reinforcement for the behavior. These factors can also be negative motivations. For instance, if the observer knew that the model was punished for the behavior, was threatened for exhibiting the behavior, or observed the model being punished for the behavior, then the probability of mimicking the behavior is less.

Applications of observational learning
Modeling has been used successfully in many therapeutic conditions. Many therapists have used forms of modeling to assist their patients to overcome phobias. For example, adults with claustrophobia may observe a model in a video as they move closer and closer to an enclosed area before entering it. Once the model reaches the enclosed area, for instance a closet, he or she will open the door, enter it, and then close the door. The observer will be taught relaxation techniques and be told to practice them anytime he or she becomes anxious while watching the film. The end result is to continue observing the model until the person can enter the closet himself or herself.

Bandura’s findings in the Bobo doll experiments have greatly influenced children’s television programming. Bandura filmed his students physically attacking the Bobo doll, an inflatable doll with a rounded bottom that pops back up when knocked down. A student was placed in the room with the Bobo doll. The student punched the doll, yelled “sockeroo” at it, kicked it, hit it with hammers, and sat on it. Bandura then showed this film to young children. Their behavior was taped when in the room with the doll. The children imitated the behaviors of the student and at times even became more aggressive toward the doll than what they had observed. Another group of young children observed a student being nice to the doll. Ironically, this group of children did not imitate the positive interaction of the model. Bandura conducted a large number of varied scenarios of this study and found similar events even when the doll was a live clown. These findings have prompted many parents to monitor the television shows their children watch and the friends or peers with which they associate. Unfortunately, the parental saying “Do as I say, not as I do” does not hold true for children. Children are more likely to imitate the behaviors versus the instructions of their parents.

One of the most famous instances of observational learning in animals involves the blue tit, a small European bird. During the 1920s and through the 1940s, many people reported that the cream from the top of the milk being delivered to their homes was being stolen. The cream-stealing incidents spread all over Great Britain. After much speculation about the missing cream, it was discovered that the blue tit was the culprit. Specifically, one bird had learned to peck through the foil top of the milk container and suck the cream out of the bottle. It did not take long before other blue tit birds imitated the behavior and spread it through the country.

perceptual learning, process by which the ability of sensory systems to respond to stimuli is improved through experience. Perceptual learning occurs through sensory interaction with the environment as well as through practice in performing specific sensory tasks. The changes that take place in sensory and perceptual systems as a result of perceptual learning occur at the levels of behaviour and physiology. Examples of perceptual learning include developing an ability to distinguish between different odours or musical pitches and an ability to discriminate between different shades of colours.

Views of perceptual learning in humans
Perceptual learning in humans was once assumed to be a phenomenon restricted to the early stages of human development or attributable to changes in high-level cognitive processes. In the case of development, a great deal of neural tuning and reorganization takes place during early childhood, and many experiments have shown that perceptual experience (or lack thereof) during that time can play a large role in permanently shaping the properties of neural mechanisms. It was traditionally assumed that after that critical period of perceptual development had passed, neural mechanisms at the earliest stages of information processing were no longer plastic and thus could not be modified through experience with the world. In the case of perceptual learning in adults, it was generally assumed that changes in high-level cognitive processes, such as decision making, were responsible for improvements in perceptual performance with practice.

In the latter part of the 20th century, researchers demonstrated that human adult perceptual systems are in fact highly mutable. (For more information on the ability of neural pathways to change with learning, see neuroplasticity.) The discovery suggested that the properties of low-level cognitive processes, which involve areas of the brain that are the first to receive sensory information, could be reshaped by perceptual learning. Although it did not rule out the involvement of high-level cognitive processes in perceptual learning, the discovery prompted researchers to focus on simple sensory tasks and stimuli, which provide basic information about the changes that are occurring within a perceptual system as learning is taking place.

Various approaches, based largely on techniques in psychophysics and computational modeling, have been used in the study of perceptual learning. Psychophysics, which focuses on relationships between physical and sensory stimuli and mental processes, has provided especially useful insights into perceptual learning. Psychophysical techniques are designed to allow one to make inferences about the inner workings of a perceptual system by observing the responses that the system as a whole makes to carefully constructed stimuli. Psychophysical techniques have been used extensively to try to identify the kinds of cognitive processing changes that take place with practice in a wide variety of perceptual tasks.

Perceptual learning: vernier acuity
Many of the tasks that are used in psychophysics investigations involve relatively basic perceptual mechanisms. An example is vernier acuity, in which the viewer attempts to discern the alignment of two segments of a broken line. The amount of displacement that can be perceived between two lines in a vernier acuity test is less than the diameter of a single photoreceptor in the human eye. The level of acuity actually exceeds the physical capabilities of human photoreceptors and thus is an example of hyperacuity. Hyperacuity is associated with altered activity in the visual cortex of the brain, which helps explain why performance in vernier acuity can improve with practice.

In general, visual acuity training exhibits several unique characteristics. For example, depending on the type of training, enhanced acuity may be orientation specific, such that people who have been extensively trained with horizontal lines may not be able to transfer their learning to tests with vertical lines and vice versa. Initial performance with vertical lines may be only marginally better than initial performance with horizontal lines but can be improved to the same level that was achieved with horizontal lines. Also, depending on the type of acuity training undertaken, there sometimes is a similar degree of specificity for the position of training (e.g., training in the left visual field does not transfer to the right visual field) and the eye of training (e.g., training in the left eye does not transfer to training in the right eye).

In addition, similar to training for certain other sensory modalities, explicit accuracy feedback is not necessarily required for visual learning to take place, although the learning process is more gradual without feedback. There also are multiple phases to the learning process—an initial fast learning phase and a subsequent slower learning phase. The learning effects tend to be relatively long-lasting, with performance maintained for weeks or even months after initial training.

Discussion Observational LearningMechanisms of perceptual learning
Although in some instances there is clear evidence that perceptual learning is associated with changes in cognitive processing, the mechanisms behind perceptual learning have been difficult to identify. It was thought, for example, that visual learning could not transfer across orientations, positions, or eyes. Hence, rather than occurring as a result of a generalized high-level learning process, visual learning was attributed to changes in neural processing that tuned acuity to a narrow range of orientations and a particular region of the visual field on the basis of input from one eye. As a result, the physiological locus of learning in a vernier acuity task was thought to lie in the primary visual cortex, where the first stages of visual cortical processing are carried out.

However, research conducted in the late 1990s and early 2000s indicated that perceptual learning can in some instances transfer between different visual tasks. The transfer of learning from one task to another depends on some degree of overlap in neural processing pathways as well as on the complexity of the visual training tasks involved. Scientists have presented various ideas on the mechanisms behind perceptual learning for visual tasks. Some of those ideas can be understood from the perspective of computational models. Examples of such models include representation modification and reweighting (or read-out modification). In representation modification, learning is associated with changes in the properties of neurons in the early stages of visual processing. Reweighting, on the other hand, suggests that learning is associated with changes in the strength of connections between cortical sensory representations and mid- or high-level brain areas. Still other models are based on different mechanisms, such as the modification by perceptual learning of neural connections in a single visual area or of cortical top-down connections that feed into early-stage processing areas from high-level areas.

In addition to visual acuity processing, psychophysical experiments have been applied to a wide array of tasks and stimuli involving other sensory modalities. Each of those applications is designed to uncover the underlying neural changes that take place with practice within a particular kind of perceptual processing. Examples of perceptual processes that have been investigated include visual motion detection, tactile spatial discrimination, and auditory frequency discrimination. Similar to vernier acuity, for other sensory modalities there tends to be a high degree of specificity of learning with regard to task and stimulus, though there are important exceptions to that trend.

Changes in neural processing
Underlying the various models of perceptual learning mechanisms are the particular neural changes that take place, which appear to reflect the specific kind of code used by the brain to represent percepts (mental impressions derived from perception with the senses) in a given task. One such change is an increase in the size of the neural representation. With that kind of change, the number of neurons that respond to a stimulus in a given brain region increases as performance in a behavioral task improves. Such changes have been found for a number of tactile discrimination tasks (e.g., two-point discrimination), where learning can produce marked increases in the amount of somatosensory cortex devoted to encoding a particular region of the body (e.g., a finger). Similar changes have also been found in the auditory cortex for auditory discrimination tasks (e.g., frequency discrimination) and in the motor cortex for motor learning tasks (e.g., reaching and grabbing). That kind of change in neural representation most likely reflects a computational code that relies on summing across a large number of neural responses in order to increase the statistical reliability of an eventual decision.

A second kind of neural change often seen with practice is a sharpening of neuronal “tuning functions.” A tuning function describes the relative sensitivity of a neuron to variations along a particular stimulus dimension (e.g., orientation, frequency). Neurons situated at early stages of perceptual processing generally respond best to a limited range of stimulus attributes, and learning in some cases can serve to narrow the focus of that range. The result of that kind of change is that neighbouring neurons will have tuning functions that have less overlap in their responses to stimuli after learning has taken place. Such changes have been detected in the visual, auditory, and motor cortex and likely reflect a code where each neuron produces a response that is as different as possible along a particular stimulus dimension or dimensions (often called decorrelation). In some cases those kinds of changes are also accompanied by a reduction in the size of the neural representation. That shrinkage in representation takes place presumably because the narrowing of tuning functions effectively increases the distance between neurons along the dimension that has been trained, thus reducing the total number of neurons that respond to a given stimulus.

A third kind of code that is used by perceptual systems to represent learned information is a change in the relative timing of responses made by a set of neurons. In particular, several studies involving tactile and auditory learning have found that practice discriminating stimuli that vary in their temporal characteristics can produce an increase in the synchronicity of firing across the ensemble of neurons that normally respond to the stimuli. Increased synchrony of neuronal firing has also been found in olfactory learning tasks in which the stimuli are not temporally varying, indicating that the use of temporal coding strategies by perceptual systems is not restricted to temporally varying stimuli.

play, in zoology, behaviour performed in the absence of normal stimuli or behaviour elicited by normal stimuli but not followed to the completion of the ritualized behaviour pattern. Play has been documented only among mammals and birds. Play is common among immature animals, apparently part of the process of learning adult behaviour. Much of the play of kittens and other young predators serves to develop hunting skills. The movements of a kitten following a ball or string prepare the animal for stalking prey; likewise leaping and jumping in play are preparation for springing after a bird in flight.

Adult animals also engage in play. Horses, cattle, and other hooved mammals sometimes run, chase each other, and kick up their heels for no obvious reason. Dogs have postural signals of mock aggression used to entice others into play fighting. In play all the elements of ritualized behaviour may be present, but they do not follow the pattern or sequence necessary to communicate serious intent.