TITLE: Workshop Intro: Teaching Science and Computing
AUTHOR: Eugene Wallingford
DATE: November 15, 2007 6:59 PM
[A transcript of the
SECANT 2007 workshop:
Table of Contents]
I am spending today and tomorrow at an NSF Workshop on Science
Education in Computational Thinking put on by
a group at Purdue University funded by a grant from NSF's
Pathways to Revitalized Undergraduate Computing Education
(CPATH) program. SECANT's goals are to build a community that is
asking and answering questions such as these:
The goal of this workshop is to begin building a community, to share
ideas and to make connections. I'll share in my next few entries
some of the ideas I encounter here, as well as some of the thoughts
I have along the way. This entry is mostly about the background
of the workshop and a few miscellaneous impressions.
First, I am impressed with the wide range of attendees. Folks come
from big state schools such as Ohio State, Purdue, and Iowa, from
private research schools such as Princeton and Notre Dame, and from
small liberal arts schools such as Wartburg and Kalamazoo.
We started with introduction from the workshop organizers at
Purdue and the NSF itself. Joseph Urban from NSF spoke a bit about
the challenges addressed by the CPATH program. I think its most
interesting goal is to move "beyond curriculum revision" to
"institution transformation models" -- avoiding the curse of
incremental change. This reminded me of something that Guy
Kawasaki said in his talk
The Art of Innovation:
Revolution, then evolution. To completely change how
we teach sciences and intro computer science -- revolution first,
or evolution? Given the deep strain of
that dominates most colleges and universities, this raises an
interesting question about which approach will work best. From
what I've seen here today, different schools are trying each,
with various levels of success.
The introductory remarks by Jeff Vitter, dean of the College of
Sciences -- and a computer scientist by training -- included a
comment that is a theme underlying this workshop and driving
the scientists who are here to explore computer science more
deeply: Computing is now a fundamental component in the cycle
of science: theory followed by experimentation. For many
scientists, building models is the next step after experiment,
or even a hand-in-hand partner to experiment. For many
scientists, visualizing the results of experiments is essential
-- we cannot understand them otherwise.
The workshop made a few personal connections for me. Also in
attendance are neighbors of mine,
from Iowa and
from Wartburg College.
But there are connections to my past, too. Another attendee is
an old grad school colleague of mine,
who is now at Notre Dame.
FInally, from Urban's NSF presentation I learned that one of the
big CPATH awards was
made to a team at Michigan State
my old advisor.
I'm not too surprised that his professional interests have evolved
in this direction, though he might be.
Some here expressed surprise that so many folks are already doing
interesting work in this arena. I wasn't, because there's been a
lot of buzz in the last couple of years, but I was interested to
see the diversity of new courses and new programs already in
place. That is, of course, one of the great benefits of attending
workshops such as this one.
- What should science majors know about computing?
- How can computer science be used to teach science?
- Can we integrate computer science effectively into other majors?
- What will the implications of answers to these questions be for
how we teach computer science and engineering themselves?