A
Model for the Creation of
Meaningful Community College Learning Experiences
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Why should educators study
brain research?
Pat
Wolf and Ron Brandt (1998), in an article about interpreting brain research
for the classroom, point out that, "we have learned more about
the brain in the past five years than in the past 100 years. Nearly
90 percent of all the neuroscientists who have ever lived are alive
today. Nearly every major university now has interdisciplinary brain
research teams." They caution teachers about oversimplifying the
connections between the science of how the brain learns and the use
of this information in the classroom, urging teachers not to use neuroscience
findings to promote "pet" programs or to adopt policies. (To
read PBS articles about the challenges of applying brain research to
education policy, click here. ) Instead, Wolf and Brandt urge educators
to "develop a functional understanding of the brain and its processes"
so that they won't be vulnerable to "pseudoscientific fads, inappropriate
generalizations, and dubious programs." However, they also remind
us that educators, with their solid background in teaching and learning
based on experience, educational research, and cognitive science, are
in a good position to figure out how research "does or does not
supplement, explain, or validate current practices."
The
constructivist view of learning is supported by what researchers are
learning about the physical processes in the brain. Learning is active,
not passive. As we suggest with our theoretical model for teaching in
the community college, each unique learner, in an environment, constructs
individual meaning. Or, as Abbott and Ryan (1999) put it, "Constructivist
learning is the dynamic interaction between the environment and the
individual brain." Constructivism and "brain-based" learning,
however, have their share of naysayers. First, tension exists between
advances in brain research and existing paradigms in cognitive psychology
and other fields. Ron Brandt, in "Educators Need to Know About
the Human Brain" describes one area of tension: the old nature
vs. nurture debate. Researchers who don't agree with constructivist
ideas have built much of their work on the idea that the brain's capabilities
are built in. These researchers believe the brain's adaptations occur
through natural selection rather than by rewiring in response to experience.
Other
researchers (think of Marian Diamond's work with rats and enriched environments)
are intrigued with the "plasticity" of the brain and contend
that the environment helps shape the individual brain (Brandt, 1999).
Educators can see how these two views are complementary rather than
opposing by considering the idea that we have an "evolved, modular"
brain. Richard Restak, a neurologist, explains the modular brain like
this: lots of modules linked together, with no one module in charge
of the others, and with no overall supervisory center to which all areas
report (Brandt, 1999). This modular system, evolved over millions of
years, is hardwired for certain tasks (and therefore those capabilities
are not necessarily acquired through experience). However, experience
(environment) fine tunes the living system.
The
metaphor for the brain that once seemed so appropriate (the brain as
a computer) now seems too simplistic. The brain is more than a processor.
It's a flexible, self-adjusting, unique living system (Abbott &
Ryan, 1999). Like an ecosystem, the brain is made up of parts functioning
as a whole. Also, just like in an ecosystem, one small incident can
create changes in the system. For example, an experience that generates
strong emotions can effect change in the brain. The resilient brain
protects itself and adapts to its environment.
Renate
and Geoffrey Caine (1994) in Making Connections, Teaching and the
Human Brain, use the metaphor of the brain as a living city:
By
the time of birth there is a definite organization to the human brain.
We arrive with some of the basic equipment that allows us to interact
with the world around us . . . The developed areas of the brain are
largely survival oriented. They control basic functions such as eating,
eliminating, breathing, the maintenance of body temperature, and sleep.
In addition, we appear to have some basic capacities that already
allow us to look for patterns.
The
Caines contend that "at least as important as genetically programmed
brain development is what has been called "brain plasticity . .
. the physical structure of the brain changes as the result of experience."
So, where does all of this leave us as educators? Ron Brandt (1999)
gives us good common sense advice: we can combine what we are learning
about brain science with what we can draw from other fields (cognitive
psychology, social sciences, anthropology), with education research,
and with our own experience in the classroom to "illuminate our
understanding."
As
Khaki, Annette, and I designed our own theoretical model for the creation
of learning experiences in the community college, we found ourselves
squarely in the constructivist camp, but we continue to wrestle with
the idea of "brain-based" learning, and we acknowledge the
gap between current brain research and practical application in the
classroom. However, we also believe that as educators, we are in a unique
position to help close the gap between education theory and current
research in brain science. One approach is to ask scientists to take
a look at what we want them to study. For example, as Lisa was reading
How the Brain Learns, by David Sousa, she became intrigued with
the idea of how nutrition might help us strengthen the myelin sheath.
She could read more about this and ask the researchers about how this
connects to learning in the college classroom. We should work hand-in-hand
with researchers, helping them direct the research. We can help make
connections between our classroom experience, science research, and
social/psychological research. As Robert Sylwester argues:
We
ought to look at brain research as a way to simply explore ideas as
they come along and try them out. Teachers have this marvelous brain
laboratory in the classroom; they've got 30 brains floating around,
four of five feet off the ground, 100 pounds of brain tissue that
they can study all day long. They can look at these brains and engage
them in activities; they can try to find out how students feel, how
long they were able to stay attentive, and what they learned. That's
what I think teachers ought to do. (qtd. in DArcangelo, 1998)
Furthermore,
as Susan Fitspatrick (a neuroscientist at the McDonnell Foundation)
points out, what we are learning now is at such a simplistic level,
we may find out that we're wrong two years from now (Wolf & Brandt,
1998). Think about, for example, how the various "models"
illustrating our understanding of atomic structure changed as advances
in technology improved our ability to "see" the structure!
Ideally, we'd like to pin down exactly how the brain learns and how
we can use that information in our classrooms, but common sense reminds
us of the the gap between the research and the classroom. However, it's
important to remember that the purpose of neuroscience is not to tell
us what to do in the classroom. It's to study how the brain works. We
should develop our basic understanding of how the brain learns. Then
we can use our own knowledge about teaching and learning to figure out
how the science may inform our teaching. In addition, as educators
we should think about how we can help researchers shape their inquiries
into how the brain works. Again, we can ask the questions that will
help direct their research (Wolf & Brandt, 1998).
In
addition, understanding the physical world "behind" the abstractions
of teaching theory (and our theoretical model) will help us make sense
of the abstractions. Think about it this way: it's important for students
to understand abstractions such as algebra and writing as representations
of the physical world. For example, when we understand the physical
movement of an object, and that we might want to predict further movement,
we understand the purpose for algebraic functions. Similarly, learning
about the living system of the brain, and how the brain learns, will
help us understand teaching theory and create meaningful learning experiences
for our students.
Good
teachers know that people learn the best when they are engaged in experiences
that fascinate them. We all know, for example, that people engaged in
hobbies they love exhibit a love of learning that we'd love to see grow
in our students. Most of us also know young people who love video games
and can operate the various hardware systems and software and maneuver
complex games with incredible success. Think about what's happening
when an adolescent gets a new computer game. She uses prior knowledge,
adapts that to the new rules and structure of the new game, and can
predict future application of what she has learned. Playing the game
involves the whole mind/body including sensory stimulation, appropriate
level of challenge, and humor. And, although we've heard much concern
about video/computer game playing isolating young people, the fact is
the games are often played in groups, and the social interaction surrounding
the world of the gamers can be intense. Why are we surprised at how
quickly and efficiently these learners figure out game strategies, given
the learning experience? We're
not suggesting, of course, that video games become part of the curriculum
(although asking students to develop a video game that teaches MLA documentation,
for example, might be interesting). Rather, we're suggesting that we
carefully examine life experiences our students find engaging, and that
we examine what brain science tells us about WHY the brain finds these
experiences engaging, so that we can use this information in the classroom
to design meaningful learning experiences.
Educators
at the elementary and secondary levels have made significant strides
in applying current understanding of how the brain works in their settings,
but we have not found comparable efforts at the community college level.
Yet, since we've become involved in this work, we've come to believe
that taking what we know about the how the brain works and applying
it to community college level is not only beneficial but also essential.
Our
model consists of three parts: valuing the unique learner, creating
learning-centered environments and the constructing individual meaning.
It's artificial to break apart any discussion of how the brain works
to say that, for example, this process is related to what makes a learner
unique, this process is related to creating a learning-centered environment,
or that another process is related to the construction of meaning. Instead,
think of the three sections of our theoretical model as three lenses
through which to study learning, or as a living system for creating
meaningful learning experiences. I've used the word "living"
here to connote that our theoretical model is like tree we have grown
from our interest in learning. The seed is now a tree -- growing, changing,
needing pruning from time to time, interacting with its environment,
and, occasionally, blossoming!