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Memory, Transfer, & Metacognition - Defining Learning

A few weeks ago, I wrote about the lost language of pedagogy and described an EdTechTeacher workshop during which I challenged participants to socially construct a definition for learning. To support that process, we explored the concepts of behaviorism, cognitivism, and constructivism examining how each framework presented a different definition of learning. However, as I study for my upcoming comprehensive exams, I have decided to revisit this idea of defining learning.

Commonalities Across Theories

Each of the aforementioned learning theories holds a few elements in common. First, learning must involve physical change in the learner's brain.  Neuroscientists, Willingham and Lloyd (2007) explain that an educational experience should initiate some form of cognitive processing which results in neural processing. Theoretically, that neural processing could be modelled or validated using different types of imaging tools like functional MRI or electrophysical measures. Over time, as the brain engages in learning, it forges new connections and increases the production of new cells. Hence, learning involves a change in the structure of the brain.

For this neural processing to occur, the learner has to attend to the learning. From a neuroscience perspective, when in attention, more neurons fire synchronously, allowing the brain to build cognitive connections based on the neural responses. Donald Hebb famously described this concept by claiming, "neurons that fire together wire together."  This may seem completely obvious, but learning can therefore not occur without attention - whether it is attention to an environmental stimulus in order to produce a desired behavior (behaviorism), to build a new cognitive connection (cognitivism), or to construct new meaning based on experience (constructivism).

Next, all learning requires memory.  Though each of the major frameworks defines the relationship between working and long term memory differently, they also require that the learner leverage both components as they engage in the process of learning.  Finally, learning requires transfer. Again, there are some differences between the three frameworks such as how a behaviorist defines transfer as the ability to apply a desired behavior to a new context as compared to a constructivist who would view it as the completion of meaningful tasks based on a previously learned strategy. However, in every situation, learning can be defined based on the ability to generalize knowledge, behaviors, and/or experiences to new situations (Ertmer & Newby, 1993).

Constructing Learning

With the emergence of cognitive science in the 1950s, researchers began to use construction metaphors to describe learning. This was a fundamental shift in thinking as it broke the idea of learning as "transmission" from teacher to student and instead required active participation on the part of the learner (Ernest, 2010). Two schools of thought then emerged within this metaphor.

From a cognitive perspective, Schunk (2012) described learning as the acquisition of mental representations based on how the individual processed and encoded information as it passed between their working and long term memories.  As information enters into a person's working memory, that individual engages in a linear process of retrieval from their long term memory. Through top-down processing, previous knowledge and beliefs influence their perception of the environment and the processing of the new learning. On the other hand, the environment could relay new information into a person's working memory which might then be processed and stored in the long term memory. Though this is an oversimplification of Schunk's (2012) Information Processing Model, it shows how learning could be an individualistic experience.

On the contrary, other theorists argue that learning is socially constructed.  Bandura (1996) describes learning as a "dynamic interplay of inner forces" (p. 2) that includes the impact of the environment, cognitive or personal reactions within that environment, and the behaviors that ensue. Within this definition, learning may occur through direct experience or through vicarious observation. Vygotsky (1978) presented a similar argument and claimed that learners (and learning) are interconnected with the social world.

Learning as Process vs Performance

Students represent complex systems. As such, learning occurs as a series of dynamic feedback loops (Rodriguez, 2013) as students interact with each other and their immediate environment. Whether defining learning according to Schunk's (2012) information processing model or a social perspective such as that from Bandura (1986) or Vygotsky (1978), these processes occur within a broader system that includes the environment, concept to be learned, and temporal context (Alexander, Schallert, & Reynolds, 2009).

Learning represents a complex cognitive and neural process, and yet much of formal schooling defines it based on performance. State and federal policies reference student achievement and describe learning as a linear series of inputs and outputs based standards and assessments.  Because of this performance focus, too often we equate learning with output. Imagine the potential if we could shift the conversation away from standardized tests and towards discussions of memory, transfer, and metacognition.

References

Alexander, P. A., Schallert, D. L., & Reynolds, R. E. (2009). What Is Learning Anyway? A Topographical Perspective Considered. Educational Psychologist, 44(3), 176-192. doi:10.1080/00461520903029006

Bandura, A. (1986). Social foundations of thought and action. Englewood Cliffs: Prentice Hall.

Ernest, P. (2010). Preface to Part II Ernest's Reflections on Theories of Learning. In L. English (Ed.), Theories of Mathematics Education (pp. 35-38). Berlin, Heidelberg: Springer Berlin Heidelberg. doi:10.1007/978-3-642-00742-2_3

Ertmer, P. A., & Newby, T. J. (1993). Behaviorism, Cognitivism, Constructivism: Comparing Critical Features from an Instructional Design Perspective. Performance Improvement Quarterly, 6(4), 50-72. doi:10.1111/j.1937-8327.1993.tb00605.x

Rodriguez, V. (2013). The Potential of Systems Thinking in Teacher Reform as Theorized for the Teaching Brain Framework. Mind, Brain, and Education, 7(2), 77-85. doi:10.1111/mbe.12013

Schunk, D. H. (2012). Learning Theories. Pearson.

Willingham, D. T., & Lloyd, J. W. (2007). How educational theories can use neuroscientific data. Mind, Brain, and Education, 1(3), 140-149. 

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