To create a modern theory of learning, we need to understand how learning takes place in the brain. This probably seems obvious, but I doubt that many (if any) of you had “brain science” as part your teacher certification. Learning about the brain is fascinating and confusing, and something that everyone in the education field should do. My background is in the liberal arts and it is certainly more than a little strange (and frustrating) to sit in an ed school and attempt to teach myself about things they are learning over in the neuro and cognitive science departments, but it’s worth the struggle. Discovering the overlap of philosophy, pedagogy, and neuroscience is absolutely incredible, and even if I only understand a quarter of what I read, it’s progress.
Here is my attempt to pass on some of what I’ve learned and perhaps spark your interest in learning more about the brain…
Knowledge can not be localized to any single region of the brain. Our brain is not a filing cabinet; information is distributed across neurons (HNK 46). This is definitely a concept I’m still wrapping my head around: information is distributed across neurons. Information doesn’t exactly sit somewhere in our heads, but rather it is accessed when an input triggers a series of neurons transmitting signals to one another. As Patricia Churchland explained in her article How Do Neurons Know?, everything we know depends on our neurons and their connections with other neurons.
Neurons “are instruments of communication; they receive, integrate and send signals”—they are the basic elements of the brain (NP 48). Key parts of a neuron are the cell body (soma), dendrites, axon, myelin sheath, and axon terminals. The human brain weighs about three pounds and contains 10^(12) –10^(14) neurons (the count is an estimate) (NP 36). As PMC explains in Neurophilosophy, “neurons and their modus operandi are essentially the same in all nervous systems—our neurons and the neurons of slugs, worms, and spiders share a fundamental similarity” (NP 36). Cool, huh?
An important attribute of neurons is their plasticity, which is “essential to their functioning as information-processing units” (NP 35). Plasticity means that our neurons are constantly undergoing many structural changes: “new branches can sprout, existing branches can extend, and new receptor sites for neurochemical signals can come into being” (HNK 46). Furthermore, “pruning could decrease branches” or “the whole cell might die, taking with it all the synapses it formally supported” (HNK 46). This is to say that neural networks are functionally modifiable–they can change. In fact, they start changing before we are born and they continue to change throughout our entire lives. While genetics do play an important role in these changes, our experiences can in many cases play a more critical role.
Learning hinges on our neurons processing inputs. The long-term facts, skills, etc. that we learn are represented by synaptic connections and prototype vectors (ER 6). Synaptic modifications “come in several different forms, suitable for the acquisition of different cognitive skills, perhaps, or for training distinct networks within the brain as a whole” (ER 254). A synapse is the point of connection between a neuron’s axon terminals and another neuron’s dendrites; essentially neurons transmit information to one another through a synapse (see diagram). As inputs continue to activate certain neurons that then transmit information to other neurons the synaptic connection between these neurons is strengthened.
All inputs have the potential to reinforce neuron pathways, forge new paths and additionally help to create prototype vectors. The “synapses that are more successful at activating their target cells” are more likely to survive in the long term (Aamodt & Wang, 2011). As our brain receives inputs, we begin to develop recurrent network pathways that “sustain a rudimentary form of short-term memory. They make our immediate cognitive past continually available to us for processing together with incoming sensory information about the present” (ER 100). Networks of activation that reoccur eventually create a limit cycle, which represents “a direct extension of an idea already familiar to you” (ER 102). The limit cycles in a neuronal network enable us to build upon knowledge we have previously acquired and strengthen existing synaptic connections.
As we learn connection strengths between neurons can increase or decrease, and sometimes, especially when we are younger new connections are formed. As mentioned before, the adjustment of these values is partially due to genetics, but mostly affected by “the unique experience that each child encounters (one’s nurture)”—our daily inputs, including what we experience at school, work, etc. (ER 5-6). As babies and young children many of the most important neural networks are created automatically by our genes. As Aamodt and Wang note in Welcome to Your Child’s Brain: How the Mind Grows from Conception to College, it would take a lot for parents and/or guardians to screw up their children’s initial brain development. That isn’t to say that parenting and nurture isn’t important, just that the brain is very advanced and capable of developing quite extensively on its own.
As inputs of any kind continue to trigger a particular series of activation in our brain, synaptic connections are strengthened, giving us better access to skills and/or information—the more experiences we have that reinforce the connection, the stronger it becomes. These strong connections can be represented by prototype vectors. Prototype vectors represent something that we have learned. As we continue to receive inputs we continually update our prototype vectors and use the state spaces defined by them as a means to further learning.
Key take away for now? Learning depends on the inputs our brain receives (whether they are from our genes or our experiences) and it is represented by the creation, pruning, and strengthening of synaptic connections.
Why is this important?
As one my astute neuroscientist friends point out it’s fairly obvious…Learning depends on inputs, duh. He makes a good point. I suppose I see value in knowing what’s actually going on inside my brain when I’m learning or what’s going on inside students’ brains when I’m teaching. Suddenly my question becomes not “how do I teach “x”?” but instead, “how am I going to strengthen synaptic connections?” The difference may be trivial and just semantics, but I believe it represents an important shift in how we think about the act of teaching.
Leslie Hart, author of Human Brain and Human Learning, argues “that teaching without an awareness of how the brain learns is like designing a glove with no sense of what a hand looks like–its shape, how it moves” (Hart 1983). He believes that “if classrooms are to be places of learning, then “the organ of learning,” the brain, must be understood and accommodated”:
All around us are hand-compatible tools and machines and keyboards, designed to fit the hand. We are not apt to think of them in that light, because it does not occur to us that anyone would bring out some device to be used by human hands without being sure that the nature of hands was considered. A keyboard machine or musical instrument that called for eight fingers on each hand would draw instant ridicule. Yet we force millions of children into schools that have never seriously studied the nature and shape of the human brain, and which not surprisingly prove actively brain-antagonistic. (Hart 1983)
Hart makes a great point. New “ideas” are constantly being rolled out in education. How many times a year have you been introduced to the next panacea? The new great curriculum, workbook, or computer program that is going to bring all your students up to grade-level and beyond? And how many times have you thought about whatever new learning gimmick you’ve been handed and thought, “this is a terrible idea” or “these people have no idea how to teach children”? In education, people regularly roll out “keyboard machines” that call for eight fingers on each hand, so to speak.
You might be reading this and thinking that it’s really the “reformers” and politicians (the people who advocate and implement learning “fixes” that don’t fit the brain) that need to learn about how the brain works, and you’re right. If they took the time to I don’t think such a high premium would be placed on rote memorization, standardized testing, or many other horrific education methods that get shoved down our throats.
The truth is, I really doubt that they will take the time to do this on their own. The best option is for us to lead by example. What we need to remember is that ultimately as teachers or parents or anyone who works with learners, we control the inputs. The more we learn about the brain, the better experiences (inputs) we can provide no matter what environment we are forced to work in. Brain science is truly on our side, and it’s time to leverage it to bring back more progressive classrooms and create genuine learning.
Aamodt S. & Wang, S. (2011) Welcome to Your Child’s Brain: How the Mind Grows from Conception to College. USA: Bloomsbury.
ER. Churchland, Paul M. (1995). The Engine of Reason, the Seat of the Soul. Cambridge: MIT Press.
Hart, Leslie. (1983). Human Brain and Human Learning. Longman Publishing Group. More info at: http://www.brainconnection.com/topics/?main=fa/brain-based
HNK. Churchland, Patricia S. (2004). “How do neurons know?” Daedalus 133: p. 42-50.
NP. Churchland, Patricia S. (1986). Neurophilosophy: Towards a Unified Science of the Mind Brain. Cambridge: MIT Press.