The old notion that brains are fixed, with learning potential already wired in the brain, is being replaced with the theory that the brain is flexible. This article presents information on the concept of brain-based learning. Technological advances have allowed researchers to identify actual physical changes in the brain when learning occurs. This research has come to be known as brain-based learning, or neuroplasiticity. Understanding what is happening in the brain during the learning process can help educators tailor classroom instruction to facilitate increased learning.
Keywords Adrenaline; Amygdala; Axon; Brain Based Learning; Dendrites; Hippocampus; Neurons; Neuroplasticity; Neuroscientific Research; Synapse; Whole Brain Learning
Educational Psychology: Brain-Based Learning
Since the late twentieth century, learning has most often been studied using a social cognition frame. This frame has three specific dynamics—environmental factors, behavioral factors, and personal perceptions—which have been believed to interrelate with each other in ways that create the context in which learning takes place (see Figure 1).
Figure 1 Triadic Interplay in Reciprocal Determinism (Pajares, 2002)
Although social cognition theory has been instrumental in describing the social construction of knowledge and the very individualized task of learning, it does not seem to go far enough in examining the role of the personal perception dynamic. Learning is not just about the perceptions and attentiveness of each person: it is also affected by physiological changes in the person. The majority of this physiological activity is happening in the brain—learning actually creates physical changes to the brain. Technological gains have allowed scientists to examine the changes that occur in the brain during the learning process and to speculate on improved methods of teaching (Zull, 2004).
Physiological Activity in the Brain
Technology has provided the means for researchers to learn what is happening in the brain during the learning process and supports the theories that:
• When a person practices something, the neurons in the related area of the brain fire more frequently and dendrite growth increases—in fact the dendrites may grow enough to begin to interconnect (creating new potential paths for cognitive connections);
• When a person is learning, synapses work to organize neurons into a cohesive network that draws in some of the more isolated neurons—the networks are the physical equivalent of knowledge;
• Changes in the synaptic connections occur when learning is taking place;
• Synaptic activity is greatly enhanced when the brain is flooded with emotion chemicals (i.e., adrenalin, dopamine, and serotonin); and
• Exposure to new experiences and complex thinking actually increases synaptic connections and density between neurons in specific parts of the brain and also increases dendrite growth and connections within the brain (Draganski, 2004; Healy, 1990; Trachtenburg, 2002; Zull, 2004).
These findings lead to the conclusion that learning may be enhanced through practice and by engaging emotion into the process.
Technology has also allowed researchers to refute the notions that the brain is hard-wired for learning and that learning ability decelerates with age (Schwartz & Begley, 2002). It also calls for a reconsideration of how teaching translates into a learning experience for both adults and children in classrooms. An examination of these new advances in neuron-scientific research opens the door for creating new, more effective types of learning experiences in the classroom.
The old notion that brains are fixed, with learning potential already wired in the brain, is being replaced with the theory that the brain is flexible. It is always rewiring itself and will continue to do so as long as there is new information for it to accumulate and store.
However, how educators approach learning (and therefore teaching) needs to be critically analyzed in light of the new findings in the area of neuroscience. Caine and Caine (1990) formulated a list of what has been learned from research on brain-based learning. This list includes the following hypotheses:
The brain is a complex adaptive system that builds upon what already exists.
Complex adaptive systems are able to recognize and organize patterns from a given set of complex examples (Leshno, Moller, & Ein-Dor, 2003). The brain will assimilate new knowledge based upon what it has already stored. What a person will learn is moderated by the already existing bank of knowledge possessed by that person and the level of complexity in the learning situation. The brain is not able to make neural connections if the paths do not already exist (Caine & Caine, 1990; Zull, 2004).
People who describe themselves as working from intuition (or a gut-feeling) are often reacting to subtle physiological changes of which they are largely unaware. In these cases, the paths existed and learning has occurred that alters a person's behavior although the person has yet to find the ability to articulate that which has been learned. (Schwartz & Begley, 2002).
The brain is social.
This idea is often referred to as the social brain hypothesis. It suggests that, via evolution, humans developed larger, more complex brains (primarily in the neocortex—which constitutes five-sixths of the human brain—and in the limbic system) and this development is attributed to the complex relationships humans created by living in bonded social groups. The complexities present in successfully navigating such complex social groups required a new need for the development of language (both written and spoken), logical thinking skills, and the ability to plan for the future. These are all social skills that are known to develop in the neocortex. Additionally, people living in social groups are relying on basic memory, emotion charged memories linked to both attachment and tradition, expression of emotions, and love (i.e., a sense of belonging). These are all social skills that are known to develop in the limbic system. Some social group indices that correlate positively with brain size include:
• Social group size,
• The frequency of social play, and
• The frequency of tactical deception (Caine & Caine, 1990; Dunbar, 2003; Lewis, 2001).
This refutes the long-standing theory that larger human brains were the direct result of early humans learning to craft tools and strategies needed to develop individual hunting skills to survive.
The search for meaning is innate and that search occurs through patterning. Emotions are critical to patterning.
A review of how human brains function suggests the brain is hard-wired to make meaning of one's external environment. This can be understood using the Triune model, which describes the brain in three layers. The most primitive layer lies buried in the more recently evolved portions of the brain (See Figure 2). First, the reptilian complex is the most primitive portion of the brain. It is comprised of the brain stem and the cerebellum. These portions of the brain are responsible for the automatic body functions that work to maintain homeostasis in the body such as balance, digestion, circulation, sleep regulation, breathing, and the fight or flight response to danger. These maintenance activities are primarily performed without conscious control or sensation. It is this area of the brain that encourages territorial and dominant behaviors that were once meant to increase one's chances for survival.
Figure 2 Illustration: The Triune Brain (Caine & Caine, 1990)
The limbic system links emotion with behavior and promotes interpersonal attachments. It is comprised of the amygdala, which works to associate events with emotion, and the hippocampus, which works to create long-term memory and memory recall. The hippocampus uses special nerve networks of neurons and dendrite paths to enhance memory storage from both lived experiences and academic studying. When the brain is flooded with emotion hormones, memory recall (and, thus, learning) is enhanced by the interaction of the hippocampus and the amygdala.
The cerebrum contains all of the centers that receive and interpret external information; it is covered with the neocortex. It also analyzes...
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