Education: From CAnet - news:
Using Computational Science and Networks to Teach Basic Science
[With thanks to Bill St. Arnaud, whose words appear in brackets below, not mine ]:
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From: Bill St.Arnaud bill.st.arnaud at canarie.ca
Date: Mon Jul 4 14:16:03 EDT 2005
For more information on this item please visit the CANARIE CA*net 4 Optical
Internet program web site at canarie.ca
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[An excellent article and web site on how new computational tools and
networks can help open up the world of science to students and educators.
The new tools of computational science, service oriented architectures and
networks can open up avenues of exploration for students in the context of a
scientific model that is implemented on the computer. Distributed computing
projects like Quarknet, Planetary Quest and many others also allow students
to work with real data and even in some cases contribute to new scientific
discoveries. Some excerpts from HPCwire article -- BSA]
www.hpcwire.com
Let's Remember: The Noun is 'Science'......................
by Dr. Robert Panoff, Shodor Foundation
[....]
Dan Warner, a professor of mathematical sciences at Clemson University
and one of the co-founders of Shodor, a national resource in
computational science education, recently put the situation very
clearly. In considering the vast oceans of data that are being
generated by a variety of observational laboratories, he observed, "It
isn't whether we have more chips processing the data, but whether we
have more neurons. We need many more people engaged in the conduct of
science, and computational science is a wonderful way to bring people
into science."
Our challenge is to see that computational science education is a most
effective means for addressing a larger issue: quantitative reasoning.
In simple terms, we still have to ensure our children actually grow up
knowing how to compare quantities, even if it isn't being tested
anymore by the SAT! .....we have found that computational approaches to
science education (the effective use of computational tools and
visualization to teach the concepts of math and science) is as important
or more important to stress as education in "computational science"
education (teaching the process of building and testing a numerical
model).
....Our computational science
classes at Shodor for middle school and high school students
(<http://www.shodor.org/succeed>) are in full gear now, and the
students learn everything from systems dynamics to agent-based
modeling, data analysis, and visualization. But the focus is not the
computer, but what the computer can help one learn about the world.
Students want to focus more on content driven disciplines. And that is
the strength of computational science, because modern math and science
are more about pattern recognition and characterization than mere
symbol manipulation. The tools of computational science can open up
avenues of exploration for students in ways that even direct
observation can't. The observation is paramount, but the observation
is made in the context of a scientific model that is implemented on
the computer. The science is at the heart of computational science.
One approach to bring computational science to the masses is by
enlisting the help of many to assist in the task of analyzing the
overwhelming data being generated by a number of space and land-based
projects, from star surveys to earthquakes, from census data to
on-line archives of historical records. By incorporating the
exploration of real data -and there is so much of it yet to be
explored- as part of the learning of math and science starting in the
middle grades through high school and college, we can make education
an adventure for the whole human race. Unfortunately, we have many
math and science teachers at the elementary and middle school levels
who choose to be teachers at this level because they "don't do math!"
Significant work to incorporate models and computational tools into
the math education of many students has started to show its benefits,
by easing some of the math anxiety and showing how the math makes
sense. Some materials also show how to seamlessly incorporate these
tools into existing curricula in support of standards (see:
<http://www.shodor.org/interactivate>). For these approaches to become
more widespread, it will take a wholesale change in schools of
education in the pre-service preparation of math and science teachers,
which means a massive change in the attitudes of faculty in the
sciences and in education.
Computational science is both content and method. Students should know
the basics of the tools of computation, but also use computation to
learn the basics of chemistry, biology, physics, and engineering. So
many of the texts in use at all levels are wholly lacking. At the very
least, they fail to accurately communicate that much of what we know
in the sciences is from computational models as much as from direct
observation.
So, back to reality. If we keep thinking that computational science is
only for the biggest problems, then it affects only a few who would be
given limited access to limited resources concentrated in a few
national centers. If that is the only way that "real science" will get
done, we will never convince a doubting Congress the second time
around, let alone an administration that may not realize that only one
of the three R's actually begins with "R," of the relevance of
computational science. To justify an appropriate appropriation for a
long-range road map, we have to have a more wide-reaching goal of
computational science for everyone at all levels, and that means
developing an effective computational approach to science education as
well as an effective education in computational science.
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HPCwire contributor Dr. Robert M. Panoff is founder and Executive
Director of The Shodor Education Foundation, Inc., a non-profit
education and research corporation dedicated to reform and improvement
of mathematics and science education by appropriate incorporation of
computational and communication technologies.
He has been a consultant at several national laboratories and is a
frequent presenter at NSF-sponsored workshops on visualization,
supercomputing, and networking. He has served on the advisory panel
for Applications of Advanced Technology program at NSF, and is a
founding partner of NSF-affiliated Corporate and Foundation Alliance.
Dr. Panoff received his B.S. in physics from the University of Notre
Dame and his M.A. and Ph.D. in theoretical physics from Washington
University in St. Louis, undertaking both pre- and postdoctoral work
at the Courant Institute of Mathematical Sciences at New York
University.
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FAC
frank@fttx.org |
