TITLE: Science Students Should Learn How to Program, and Do Research
AUTHOR: Eugene Wallingford
DATE: August 23, 2015 10:12 AM
DESC: 
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BODY:
Physicist, science blogger, and pop science author Chad Orzel
offered
<A HREF="http://www.forbes.com/sites/chadorzel/2015/08/17/planning-to-study-science-in-college-heres-some-advice/">
   some advice for prospective science students</A>
in a post on his Forbes blog last week.  Among other things,
he suggests that science students <B>learn to program</B>.
Orzel is among many physics profs who integrate computer
simulations into their introductory courses, using the
<A HREF="http://matterandinteractions.org/">
   Matter and Interactions</A>
curriculum (which you may recall reading about here in
<A HREF="http://www.cs.uni.edu/~wallingf/blog/archives/monthly/2007-11.html#e2007-11-20T13_28_03.htm">
   a post from 2007</A>).

I like the way Orzel explains the approach to his students:

<BLOCKQUOTE><EM>
 When we start doing programming, I tell students that this
 matters because there are only about a dozen problems in
 physics that you can readily solve exactly with pencil and
 paper, and many of them are not that interesting.  And that
 goes double, maybe triple for engineering, where you can't
 get away with the simplifying spherical-cow approximations
 we're so fond of in physics.  Any really interesting problem
 in any technical field is going to require some numerical
 simulation, and the sooner you learn to do that, the better.
</EM></BLOCKQUOTE>

This advice complements
<A HREF="http://www.cs.uni.edu/~wallingf/blog/archives/monthly/2008-04.html#e2008-04-03T16_39_46.htm">
   Astrachan's Law</A>
and
<A HREF="http://www.cs.uni.edu/~wallingf/blog/archives/monthly/2009-12.html#e2009-12-01T21_51_01.htm">
   its variants</A>,
which assert that we should not ask students to write a program
if they can do the task by hand.  Conversely, if they can't
solve their problems by hand, then they should get comfortable
writing programs that can.  (Actually, that's the contrapositive
of Astrachan, but "contrapositively" doesn't sound as good.)
Programming is a medium for scientists, just as math is, and it
becomes more important as they try to solve more challenging
problems.

Orzel and Astrachan both know that the best way to learn to
program is to have a problem you need a computer to solve.
Curricula such as Matter and Interactions draw on this motivation
and integrate computing directly into science courses.  This is
good news for us in computer science.  Some of the students who
learn how to program in their science courses find that they like
it and want to learn more.  We have just the courses they need to
go deeper.

I concur with all five of Orzel's suggestions for prospective
science students.  They apply as well to computer science
students as to those interested in the physical sciences.  When
I meet with prospective CS students and their families, I
emphasize especially that students should <B>get involved in
research</B>.  Here is Orzel's take:

<BLOCKQUOTE><EM>
 While you might think you love science based on your
 experience in classes, classwork is a pale imitation of
 actual science.  One of my colleagues at Williams used a
 phrase that I love, and quote all the time, saying that
 "the hardest thing to teach new research students is that
 this is not a three-hour lab."
</EM></BLOCKQUOTE>

CS students can get involved in empirical research, but they
also have the ability to write their own programs to explore
their own ideas and interests.  The world of open source
software enables them to engage the discipline in ways that
preceding generations could only have dreamed of.  By doing
empirical CS research with a professor or working on substantial
programs that have users other than the creators, students can
find out what computer science is really about -- and find out
what they want to devote their lives to.

As Orzel points out, this is one of the ways in which small
colleges are great for science students: undergrads can more
readily become involved in research with their professors.
This advantage extends to smaller public universities, too.
In the past year, we have had undergrads do some challenging
work on bioinformatics algorithms, motion virtual manipulatives,
and system security.  These students are having a qualitatively
different learning experience than students who are only taking
courses, and it is an experience that is open to all undergrad
students in CS and the other sciences here.
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