Nothing that is worth knowing can be taught. — Oscar Wilde
Let’s imagine a conversation at the close of the 19th century. You and a team of designers are considering elements of the internal combustion engine that will, if successful, trigger a revolution in personal transportation and change the course of history. In a conversation with team members, you are presented with a series of challenging questions regarding the use of a sparkplug.
“How do we know that’s the right design? Where has this worked before?”
You are flummoxed because there is precious little evidence that you are on the right path. You understand the principles of fuel and ignition, but you cannot demonstrate how the automobile will transform social structures and economies. You are engaged in the new, and must resort to principles within known science rather than case studies. You cannot predict how your creation will emerge and co-evolve in a new world, but in order to begin, you first establish some predictive rationale that lets you begin on a road that has the highest probability of success.
We who believe in systemic transformation for education are confronted with this challenge. We cannot point to complete system exemplars, because the system we are encouraging does not yet exist. We instead develop principles of design that respect known science to the degree possible.
Let us take one of those principles, problematically titled “personalized learning.” How do we know this is important? Why the emphasis on learning, rather than instruction? And why should the learning experience be tailored to the individual? The first consideration when pondering how to help children learn should be to explore how they learn. Fortunately, advances in neuroscience help us reconsider our approach to young minds, and answer some fundamental questions: Are we born with a vessel into which knowledge is poured? Or do we create our own mind?
Reviewing the science, we find that all learning is personalized. Neuroscience, cognitive science, sociology, psychology, and philosophy agree – we create representations of our world based on individual experience. No amount of instructional method can ensure an “accurate” uptake of information. This is because you are designed to predict events in a complex world. You do this by developing a consistent sense of the world around you, the memory of input patterns experienced from birth. The infant brain is incredibly plastic, meaning it can change and rewire itself based on the type of inputs flowing into it.
When patterns appear familiar, you recall previous similar patterns and form a sense of the future based on them. An intelligent human develops the ability to predict events in their environment, so that they may adapt themselves or elements of that environment to suit their interests and goals.“The cortex is still dividing itself into task-specific functional areas long into childhood, based purely on experience. The human brain has an incredible capacity to learn and adapt to thousands of environments that didn’t exist until recently. This argues for an extremely flexible system, not one with a thousand solutions for thousand problems.” (Hawkins, p.54)
As the world is not a predictable machine, this means we do not develop complicated decision trees and Spock-like logic methods. Instead, we explore, experiment, fail and learn about our world in physical and temporal context. These learnings are shaped by individual experience, and are inherently intimate. Our brains constantly create new structures with every new experience or piece of information – these structures are more specific to our individual humanity than our fingerprints or iris patterns.
You are designed to work with incomplete information. The way you understand your world is through a combination of real inputs and memory. You resolve ambiguity by continually filling in logical gaps based on learned patterns over time. In conversation, not every word you hear is understandable out of context, rather, you predict the meaning of phonemes you hear based on the conversation itself. This same principle applies when reading handwritten words – by themselves perhaps ambiguous, we resolve this by interpreting the context and resolving the meaning based on learned patterns. How does this work?“Memories are stored in a form that captures the essence of relationships, not the details of the moment. When you see, feel, or hear something, the cortex takes the detailed, highly specific input and converts it to an invariant form. It is the invariant form that is stored in memory, and it is the invariant form of each new input pattern that it gets compared to. Memory storage, memory recall, and memory recognition occur at the level of invariant forms.” (Hawkins, p.82)
You resolve ambiguous input data based on how you believe the world works. This is due to our memory structures, which provide for “invariant form memory,” a memory of input patterns allow for partial patterns to recall whole ones. This is what occurs when you see a friend in the mall – catching just a glimpse is enough for you to ‘recognize’ her. This is termed ‘invariance.’ If you see someone at a bus stop partially obscured by a sign, you ‘assume’ the rest of her based on previous patterns that assume whole humans. This ‘filling in’ of details occurs at the most detailed sensory input, where the blind spot we all have near the center of our eye is accommodated by previous cognitive patterns. At the top of the cognitive hierarchy, where higher order pattern matching occurs, you experience the same ‘filling in’ for missing details.
This is true from the simplest form – we don’t notice the blind spot in every human eye, but rather complete the image based on surrounding context – to the most complex, including how we make decisions. One author, discussing the reality of intuitive or ‘recognitial’ decision-making, notes: “The basic aspect of recognitional decision making is that people with experience can size up the situation and judge it as familiar or typical. Usually this assessment happens so quickly and automatically that we are not aware of it.” (Klein, p.89)
As a student is not passively absorbing what is provided, but rather continuously storing patterns and comparing them against a unique collection of invariant form memories – we see the student is already in control of the learning experience. This is not new age fluffy thinking, this reflects the reality that embedded experience frames and shapes how we understand our world.
Preparing children to succeed involves acknowledging each child’s centrality to the learning experience. We can choose to continue methods that are convenient to the adult, mass lectures or student ‘tracking,’ or we can provide a system that adapts to the individual minds in our care at every stage. The science leaves us no option here – ‘personalized learning,’ by whatever name, is a central design principle for a transformed education system.
Deacon, T. W. (1997). The Symbolic Species: The Co-Evolution of Language and the Brain. New York, NY: W.W. Norton & Company.
Goffman, E. (1974). Frame Analysis: An Essay on the Organization of Experience. Boston, MA: Northeastern University Press.
Hawkins, J., & Blakeslee, S. (2004). On Intelligence. New York, NY: Henry Holt and Company, LLC.
Klein, G. (1998). Sources of Power: How People Make Decisions. London, UK: The MIT Press.