Social Learning Theory (Bandura)

Social Learning Theory, theorized by Albert Bandura, posits that people learn from one another, via observation, imitation, and modeling. The theory has often been called a bridge between behaviorist and cognitive learning theories because it encompasses attention, memory, and motivation.




Contributors

  • Albert Bandura (1925 – Present)

Key Concepts

People learn through observing others’ behavior, attitudes, and outcomes of those behaviors[1]. “Most human behavior is learned observationally through modeling: from observing others, one forms an idea of how new behaviors are performed, and on later occasions this coded information serves as a guide for action.” (Bandura). Social learning theory explains human behavior in terms of continuous reciprocal interaction between cognitive, behavioral, and environmental influences.

Necessary conditions for effective modeling

Attention — various factors increase or decrease the amount of attention paid. Includes distinctiveness, affective valence, prevalence, complexity, functional value. One’s characteristics (e.g. sensory capacities, arousal level, perceptual set, past reinforcement) affect attention.

Retention — remembering what you paid attention to. Includes symbolic coding, mental images, cognitive organization, symbolic rehearsal, motor rehearsal

Reproduction — reproducing the image. Including physical capabilities, and self-observation of reproduction.

Motivation — having a good reason to imitate. Includes motives such as past (i.e. traditional behaviorism), promised (imagined incentives) and vicarious (seeing and recalling the reinforced model)

Reciprocal Determinism

Bandura believed in “reciprocal determinism”, that is, the world and a person’s behavior cause each other, while behaviorism essentially states that one’s environment causes one’s behavior[2], Bandura, who was studying adolescent aggression, found this too simplistic, and so in addition he suggested that behavior causes environment as well[3]. Later, Bandura soon considered personality as an interaction between three components: the environment, behavior, and one’s psychological processes (one’s ability to entertain images in minds and language).

Social learning theory has sometimes been called a bridge between behaviorist and cognitive learning theories because it encompasses attention, memory, and motivation. The theory is related to Vygotsky’s Social Development Theory and Lave’s Situated Learning, which also emphasize the importance of social learning.


Additional Resources and References

Resources

References

  1. Bandura, A. (1977). Social Learning Theory. New York: General Learning Press.
  2. Bandura, A. (1986). Social Foundations of Thought and Action. Englewood Cliffs, NJ: Prentice-Hall.
  3. Bandura, A. (1973). Aggression: A Social Learning Analysis. Englewood Cliffs, NJ: Prentice-Hall.
  4. Bandura, A. (1997). Self-efficacy: The exercise of control. New York: W.H. Freeman.
  5. Bandura, A. (1969). Principles of Behavior Modification. New York: Holt, Rinehart & Winston.
  6. Bandura, A. & Walters, R. (1963). Social Learning and Personality Development. New York: Holt, Rinehart & Winston.

Metacognition (Flavell)

Metacognition is defined in simplest terms as “thinking about your own thinking.” The root “meta” means “beyond,” so the term refers to “beyond thinking.” Specifically, this means that it encompasses the processes of planning, tracking, and assessing your own understanding or performance.

The phrase was termed by American developmental psychologist John H. Flavell in 1979, and the theory developed throughout the 1980s among researchers working with young children in early cognitive stages.

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Situated Cognition (Brown, Collins, & Duguid)

Summary: Situated cognition is the theory that people’s knowledge is embedded in the activity, context, and culture in which it was learned. It is also referred to as “situated learning.”

Originators & proponents: John Seely Brown, Allan Collins, Paul Duguid

Keywords: activity, authentic domain activity, authentic learning, cognitive apprenticeship, content-specific learning, context, culture, everyday learning, knowledge, legitimate peripheral participation, socio-cultural learning, social construction of knowledge, social interaction, teaching methods

Situated cognition (Brown, Collins, & Duguid)

Situated cognition is a theory which emphasizes that people’s knowledge is constructed within and linked to the activity, context, and culture in which it was learned[1][2].

Learning is social and not isolated, as people learn while interacting with each other through shared activities and through language, as they discuss, share knowledge, and problem-solve during these tasks.

For example, while language learners can study a dictionary to increase their vocabulary, this often solitary work only teaches basic parts of learning a language; when language learners talk with someone who is a native speaker of the language, they will learn important aspects of how these words are used in the native speaker’s home culture and how the words are used in everyday social interactions.

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Also check out:

Albert Bandura Biography

In 2014, Canadian psychologist Albert Bandura was ranked number one atop a list of the Top 100 Eminent Psychologists of the Modern Era, published in the Archives of Scientific Psychology. [7] . Former president of the American Psychological Association, winner of numerous awards and more than sixteen honorary degrees and widely held as one of the most influential psychologists alive today, Albert Bandura is among the most prolific psychologists in history.

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Expertise Theory (Ericsson, Gladwell)

Expertise theory specifies how talent develops across specified fields or domains, focusing on cognitive task analysis (to map the domain), instruction and practice, and clearly specified learning outcomes against which one can objectively measure the development of expertise.

Anders Ericsson, a professor at Florida State University, is the leading figure in the field of expertise theory. However, many others are associated with it as well: Robert Sternberg (Cornell University), Richard Clark (University of Southern California), Benjamin Bloom (late of the University of Chicago), Herbert Simon (late of Carnegie Mellon University), and Mihaly Csikszentmihalyi (Claremont Graduate University). Another notable figure is Malcolm Gladwell, whose work has served to popularize the theory.

Keywords: expertise, practice, instruction, cognitive task analysis

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Cognitive Tools Theory (Egan)

Summary: There exist five kinds of understanding (or cognitive tools) that individuals usually master in a particular order during the course of their development; these have important educational implications.

Originator: Kieran Egan, a Professor at Simon Fraser University, proposed his theory of cognitive tools as part of a sustained program of writing and research on the role of imagination in learning, teaching, and curriculum.

Keywords: Cognitive, Stages, Imagination, Ironic, Literacy, Memes

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E-Learning Theory (Mayer, Sweller, Moreno)

E-learning theory consists of cognitive science principles that describe how electronic educational technology can be used and designed to promote effective learning.


History

The researchers started from an understanding of cognitive load theory to establish the set of principles that compose e-learning theory. Cognitive load theory refers to the amount of mental effort involved in working memory, and these amounts are categorized into three categories: germane, intrinsic, and extraneous[1].

Germane cognitive load describes the effort involved in understanding a task and accessing it or storing it in long-term memory (for example, seeing an essay topic and understanding what you are being asked to write about). Intrinsic cognitive load refers to effort involved in performing the task itself (actually writing the essay). Extraneous cognitive load is any effort imposed by the way that the task is delivered (having to find the correct essay topic on a page full of essay topics).


Key Concepts

Mayer, Moreno, Sweller, and their colleagues established e-learning design principles that are focused on minimizing extraneous cognitive load and introducing germane and intrinsic loads at user-appropriate levels[2][3][4][5][6]. These include the following empirically established principles:

Multimedia principle (also called the Multimedia Effect)

Using any two out of the combination of audio, visuals, and text promote deeper learning than using just one or all three.

Modality principle

Learning is more effective when visuals are accompanied by audio narration versus onscreen text. There are exceptions for when the learner is familiar with the content, is not a native speaker of the narration language, or when printed words are the only things presented on screen. Another exception to this is when the learner needs to use the material as reference and will be going back to the presentation repeatedly.

Coherence principle

The less that learners know about the presentation content, the more they will be distracted by unrelated content. Irrelevant video, music, graphics, etc. should be cut out to reduce cognitive load that might happen through learning unnecessary content. Learners with some prior knowledge, however, might have increased motivation and interest with unrelated content.

    Contiguity principle

    Learning is more effective when relevant information is presented closely together. Relevant text should be placed close to graphics, and feedback and responses should come closely to any answers that the learner gives.

    Segmenting principle

    More effective learning happens when learning is segmented into smaller chunks. Breaking down long lessons and passages into shorter ones helps promote deeper learning.

    Signaling principle

    Using arrows or circles, highlighting, and pausing in speech are all effective methods of signaling important aspects of the lesson. It is also effective to end a lesson segment after releasing important information.

    Learner control principle

    For most learners, being able to control the rate at which they learn helps them learn more effectively. Having just play and pause buttons can help more than having an array of controls (back, forward, play, pause). Advanced learners may benefit from having the lesson play automatically with the ability to pause when they choose.

    Personalization principle

    A tone that is more informal and conversational, conveying more of a social presence, helps promote deeper learning. Beginning learners may benefit from a more polite tone of voice, while learners with prior knowledge may benefit from a more direct tone of voice. Computer characters can help reinforce content by narrating the lesson, pointing out important features, or illustrating examples for the learner.

    Pre-training principle

    Introducing key content concepts and vocabulary before the lesson can aid deeper learning. This principle seems to apply more to low prior knowledge learners versus high prior knowledge learners.

    Redundancy principle

    Having graphics explained by both audio narration and on-screen text creates redundancy. The most effective method is to use either audio narration or on-screen text to accompany visuals.

    Expertise effect

    Instructional methods that are helpful to low prior knowledge learners may not be helpful at all, or may even be detrimental, to high prior knowledge learners.


Additional Resources and References

Resources

References

  1. Mayer, R. E., & Moreno, R. (2003). Nine ways to reduce cognitive load in multimedia learning. Educational psychologist, 38(1), 43-52.
  2. Mayer, R. E. (1997). Multimedia learning: Are we asking the right questions?.Educational psychologist, 32(1), 1-19.
  3. Moreno, R., & Mayer, R. (2007). Interactive multimodal learning environments. Educational Psychology Review, 19(3), 309-326.
  4. Low, R., & Sweller, J. (2005). The modality principle in multimedia learning.The Cambridge handbook of multimedia learning, 147, 158.
  5. Mayer, R. E. (2003). Elements of a science of e-learning. Journal of Educational Computing Research, 29(3), 297-313.
  6. Clark, R. C., & Mayer, R. E. (2016). E-learning and the science of instruction: Proven guidelines for consumers and designers of multimedia learning. John Wiley & Sons.