THE BRAIN IS THE SEAT OF ALL LEARNING. Brain-based learning is derived from the physiological studies of how the brain best learns. This article discusses brain physiology, brain-based learning, and implications to instructional designers. A challenge is presented to the profession in the conclusion.

The brain is made up of billions of nerve cells called neurons. Information is passed from one neuron to the next by an electrochemical process. 

Neuronal Patterns

Neuron connections are flexible, webbed, overlapping, and redundant. Internal and external stimuli collaborate in the formation of pathways and patterns of excited neurons. 
The more frequently pathways or patterns of neurons are used the stronger the pathways and patterns become. The stronger they become the more likely they will be made again. Simultaneous excitation of multiple pathways and patterns create growth of new neuron connections, thus increasing the potential of the brain to learn.

Each brain is unique. Genetic and environmental factors influence learning and the connections between cells are created by an individual's unique experiences.
Like a symphony orchestra, the various parts of the brain are instruments that play collaboratively to provide meaningful learning. Learning is the music of the brain.
The brain seeks meaning innately. The brain learns best when it processes cognitive, affective, and psychomotor information simultaneously.
New learning that is relevant and meaningful to previous mental, emotional, and physical experiences strengthens memory. Instruction that is not relevant and meaningful is less likely to be remembered.
When the brain is challenged learning is enhanced. As an example, creative acts, that include thought, feeling, and physical energy, engage many parts of the brain simultaneously.
When the brain is threatened it reverts to a fight or flight mode and learning suffers. Threats may come from internal or external sources of information or a combination of both. An angry instructor, a stifling physical environment or bullying peer may be an example of an external source of stress. Negative emotions created by grading, testing, or parental pressures may be an example of internal sources. Focused attention is an important aspect of learning.

Learning is a natural function of the brain. The brain functions for its own survival. It is not naturally hardwired for formal, institutional, standardized, instruction. In light of brain-based studies, current theories and practices of instructional design, development, and delivery need to be reexamined for their compatibility with how the brain best learns.
Brain-based research validates that learning is individually specific. This implies that standardized materials, instruction, and practices may actually diminish or inhibit learning.
Learning is best achieved when multiple domains of instruction are simultaneously introduced. This implies that the efficacy of single domain instruction, e.g. only cognitive skills, needs to be reexamined. Instruction for cognitive skills and objectives without affective dimensions may be efficient but not effective.
New learning must be relevant to the learner. If the brain, consciously or unconsciously perceives instruction as irrelevant, it is irrelevant. If irrelevant the potential for learning is diminished.
Emotions are clearly a significant factor in learner motivation. The brain is naturally self-motivated to learn. Practice of internal self-motivation strengthens neuronal pathways and patterns ensuring they will be used again. Practice of external motivation strengthens neuronal pathways and patterns ensuring they will be used again. This implies that over emphasis of external motivation practices may cause atrophy of self-motivation.

The reader might conclude that instructional design based on physiological studies of the brain is impossible if not absurd. How can one provide a personalized curriculum and individually specific instruction? How can one develop instructional packages that include simultaneous cognitive, affective, and psychomotor goals and objectives? How can one evaluate learning or test for mastery or competency with so many variables? How would one assign grades? How can we teach if the student is not motivated to learn?
These questions are all legitimate. These and many others spell out the challenge for the profession and its practitioners. We might consider the disparity between natural learning and artificial learning as a systemic problem.
The challenge is to create a new paradigm for instruction that marries natural learning with leading edge technologies. We might begin by analyzing the discrepancies between actual instructional practices against optimal learning practices. It is not to answer why it can't be done but rather how it can be done.
In the near future we may be called upon to be professional learning designers rather than instructional designers.

Contributed by James R. Lawson, 2001