Dexter Perkins, Dept. of Geology and Geological Engineering, University of North Dakota
I started college teaching in 1981 and, like most new professors, knew little about teaching other than what I had experienced as a student. I soon realized that I was in trouble – or, that my students were in trouble – because I had no idea what I was doing. I prepared “great” lectures and delivered them, only to find at exam time that students hadn’t absorbed what I was saying. So, after a few years of frustration, I began to read to find out what experts had to say about teaching and learning.
I read about active learning, learner-centered classrooms, instructional alignment, and many other things. One of the most influential books I read was Experiential Learning by David Kolb (1984). I enjoyed Kolb’s thoughts about Skinner, Dewey, Piaget and others, and about some of the pioneers of learning science and related fields. I was especially intrigued by Kolb’s ideas about what (subsequently) has been called deep learning or significant learning, and learning cycles.
Everything I read sounded reasonable, but something was missing. In retrospect, I think the main problem was that most of what I read was based on behaviorism. The implication was that the best teaching focuses only on improving students’ learning habits and behaviors by using the correct pedagogies and developing the best learning environment. Little consideration was given to physiological factors and what actually happens in students’ brains as they learn. Just as plate tectonics was not accepted as a theory until sea-floor spreading was discovered, I needed a mechanism to explain why the behaviorist approach was valid.
In 2000, the National Research Council published How People Learn (Bransford et al. 2000). In many ways, the NRC publication reinforced what I had read previously. Key points in the first part of the report included:
- Students are not empty vessels – they arrive in our classrooms with mental models, preconceptions and habits that may hinder or promote learning. Consideration of students’ preexisting knowledge is essential.
- Learning is not significant without real understanding; it is simply memorization. Lacking significant learning, students cannot use what they learn in one class to solve other kinds of problems.
- Significant learning will not occur if students are not actively engaged. Perhaps more important, to be successful learners, students must develop metacognitve skill to monitor their own progress.
As before, these points made sense, but I was still uncertain WHY they were important and, perhaps more puzzling, what to do about it. Then I read Chapter 5 (“Mind and the Brain”), a short chapter that, in the space of 20 minutes, answered many of my questions and fundamentally changed the way I thought about teaching and learning.
The brain is a constantly evolving organic machine that changes as it reacts to information it processes. Learning is a process of wiring and rewiring that machine. That’s it; that was my epiphany.
So, what is really going on in our brains? My summary, below, is based on many books and articles, most significantly the books listed in the references at the end.
The gray matter of our brains consists of a zillion neurons. At birth we may have 150-200 billion neuron cells, but many disappear (are pruned) due to lack of use. The actual number that remains is uncertain and may vary from individual to individual. Zeul (2002) places the number at around 100 billion, Jensen (2005) says 30-50 billion.
Typical individual neuron cells have a main cell body (the soma) surrounded by many raggedly leaf-like branches (called dendrites) that protrude in all directions. The cells also have a single longer branch sticking out called an axon that may extend far from the main cell body (Figure 1). Axons have a smooth surface and are surrounded by a protecting sheath of white matter (myelin) made of protein and fat. When the axons from one cell are close enough to dendrites from another, connections (called synapses) can develop.
Human thinking consists of remembering and comparing information (analysis), and evaluating or making connections (synthesis). Both processes occur because of our neuronal networks. Neurons are connected via a very complex network, and neuronal cells exchange information much like wiring circuits move electrons. When our brain processes information, perhaps visual, aural, or other sensory information from external sources, or maybe just thoughts, signals move at a blistering pace from one neuron to another. Information/signals get picked up by the dendrites, travel to the soma, shuffle down an axon, cross a synapse, and go on and on through the network. Synapses, which can develop in many places on a single dendrite, come and go throughout our lives, so our brains are constantly being rewired. At each synapse, chemical processes excite or inhibit activity in a neuron dendrite, so synapses may be either strengthened or weakened.
The brain’s neuronal network has sometimes been compared with a river drainage network, or to a tree or bush with many branches, but is really more complicated than these simple analogies suggest. Each neuron may have 10,000 or more connections to others, and there are on the order of a million miles of wiring in our brains. When born, we only have a fraction of all the synapses we will later develop, but they develop quickly (synaptogenesis) – the largest number within the first year or so; then the total decreases for the rest of our lives as unused connections are pruned and new ones develop. At the same time, the brain can produce new neurons that contribute to memory and thinking.
The neurons and synapses we use, stick around; others are pruned. So they are gained by experience, and lost if not used. Consequently, what a person does, sees, hears and thinks about lead to changes in the brain. Rewiring is an ongoing process and connections are made and broken in just seconds or minutes. Reinforcing those connections takes longer times, and much reinforcement is done while we are sleeping at night. Firmly connecting new circuits to old ones may take days or longer, but eventually circuits and connections that are fired the most may become “hard wired” and semi permanent. Specific skills such as driving or dancing, or knowledge of a particular subject – all are wired in the same way. Such connections are difficult to develop and perhaps, more difficult to eliminate. (Think about this the next time you encounter someone who is stubbornly wrong about something!) So, the brain adapts as needed and growth is different for different people depending on their experiences. Researchers, who have actually been able to “see” (image, using several different techniques) brain connections form, find that different parts of the brain develop and respond to different kinds of stimuli. Brains of musicians are wired differently than brains of figure skaters, for example, and different people respond to stimuli in different ways.
One key component in all this is the myelin that forms the protecting layer around axons. Myelin, essentially, can change a local road to a super highway. The better myelinated an axon is, the better and faster the signal transmission. At birth, few axons are myelinated. Myelin develops in different parts of our brain at different times, making us better and better thinkers and firmly cementing some bits of knowledge or skill in our minds. Coyle (2009) suggests that myelin may be the most important thing in our head. Studies reveal that expert athletes, musicians, or scholars all have different parts of the brains that are especially well myelinated.
What’s It Mean?
So, students are not empty vessels. They come to our classrooms completely wired. They have knowledge, mental models, and habits that are built in. This prior knowledge consists of real, physical brain circuits. Unfortunately, those circuits may be poorly or inappropriately developed, and a student’s knowledge and ways of thinking may hinder learning or make it difficult for them to understand what we are trying to teach. When students fail one of my exams, it may not be that I am a bad teacher, or that they are bad or lazy students. It may simply be that they do not have the brain circuits necessary to succeed. When students tell me that they are “bad at science,” it really means that they do not have the requisite neuronal networks to succeed, or at least to believe they can succeed, at science. So, we teachers need to help students develop new mental models and to eliminate old ones – a physical process involving changing the structure of their brains.
Many authors, including the ones referenced in this article, have talked about the importance of deep/significant learning. Consideration of the brain’s dynamics explains what this really means. When superficial leaning occurs, students may temporarily absorb some information for short term recall. They may learn how to do something, but the new skill won’t be long-lasting. In contrast, when significant learning occurs, physical changes occur in their heads. The learning experience has been strong enough to develop new synaptic connections between neurons. New knowledge, new ideas, new ways of thinking become semipermanent fixtures as neuronal networks are modified. Coyle (2009) argues convincingly that significant learning cannot be obtained without what he terms “deep practice” because deep practice is necessary to promote myelinization. Call it what you want, deep practice, targeted practice, focused practice – the key is that all practice is not the same. If we want to promote significant learning, we have to teach in a way that promotes meaningful, significant, practice and thinking.
Thinking about the brain as a living, evolving, organism makes it clear why students must be actively engaged if they are to learn. Engagement means that they are really using their brains, and the exercise promotes the physical changes necessary for real learning. In Teaching With the Brain in Mind, Jensen (2005) says that promoting engagement requires us to teach in a way that is focused and relevant. We need to deliver information, or assign tasks, in absorbable chunks, and reinforce what we do. Repetition, perhaps involving previewing, reviewing, revising and other things students can do, is key. These activities promote physical changes at the synapses (termed long-term potentiation) that strengthen the synapses and make them especially receptive to future similar inputs. Metacgonition is also important because, as students monitor what they are learning and evaluate outcomes, the connections that manifest learning are strengthened and reinforced.
Understanding the physiological basis of learning is one thing; using this knowledge to revise instruction is another. There are many paths that could be followed and no one way is best. For some practical examples, check out Teaching With the Brain in Mind (Jensen 2005), the New York Times Best Seller Brain Rules (Medina 2008), or the recent and very engaging Talent Code (Coyle 2009). There are many other good references, but these three are both informative and a fun to read.
Bransford, J.D., Brown, A.L., and Cocking, R.R. (2000) How People Learn: Brain, Mind, Experience, and School. Nat. Acad. Press, Washington. 374 p.
Coyle, D. (2009) The Talent Code: Greatness Isn’t Born. It’s Grown. Here’s How. Bantam Books, New York. 246 p.
Jensen, E. (2005) Teaching With the Brain In Mind. Assoc. Superv. Curric. Develop., Alexandria. 187 p.
Kolb, D.A. (1984) Experiential Learning: Experiences as the Source of Learning and Development. Prentice Hall, Englewood Cliffs. 364 p.
Medina, J. (2008) Brain Rules: 12 Principles for Surviving and Thriving at Work, Home, and School. Pear Press, Seattle. 301 p.
Zull, J.E. (2002) The Art of Changing the Brain: Enriching the Practice of Teaching by Exploring the Biology of Learning. Stylus Pub., Sterling. 263 p.