research laboratories. Yes, members
of many product groups read research
papers, but an abstract idea, even with
supporting experimental data, is rarely
the catalyst for uptake of a new idea. A
well-written paper does, however, provide the technical details needed when
an idea is ultimately adopted.
Demonstrations. These are the “
science fair” instantiations of ideas, the
early instances that are little more than
mockups of the idea. They work on limited data, are constructed using laboratory rather than product components,
and they are unreliable at best. However, their virtue is in allowing non-researchers to see and experience the
idea in concrete form. Often, seeing really is believing, and a prototype can be
convincing in ways that a paper is not.
Prototypes. Prototypes are the next
stage, where the demonstration is sufficiently robust that it can be used routinely by individuals and groups other
than the creators. The robustness allows product groups and developers
to test the idea in more realistic conditions and contexts, and see how it fares
relative to existing technologies.
Near Products. Near products are
products in all but name, suitable for
shipment with little more than cosmetic changes. Creating a near product can
be effective if the product team is interested and willing but understaffed, or
if they lack the specific technical skills
needed to create a product-quality instance of the idea.
Papers, demonstrations, prototypes,
and near products help, and they may
sometimes be sufficient to transfer
an idea into a product. However, they
are pale shadows of the true contact
sports, either direct embedding with
the product team or long-term engagement and partnership. In the
embedding model, researchers become members of the product team,
working side by side on the product
in the same environment as the product developers. Because the utility of
so many new ideas depend on culture
and context—things rarely written
down—as well as personal trust and
connections, contact engagement is
often the most successful approach.
Remember, game plans, no matter how elaborate, rarely work without
to get 10,000 high
school cs teachers
in five years,
need to involve
people who know
how to prepare and
faculty in schools
of education across
modification. The players on the field
innovate and adapt. Technology transfer is a contact sport. It can be contentious at times, but the rewards for successful transfers are enormous, both
in a sense of personal accomplishment
and pride and in the long-term success
of the companies involved.
mark Guzdial “computer science needs education schools. Desperately.”
october 13, 2010
In the new National Science Foundation (NSF) “Computing Education in
the 21st Century (CE21)” program solic-itation, proposers are explicitly asked
to “design, develop, and evaluate the
impact of pre-service and in-service efforts and strategies that enhance K– 14
teaching expertise in computing.” In
Education-speak, “pre-service” means
(mostly) undergraduate teacher education programs and “in-service”
means professional development for
teachers in the classroom. The solici-tation points to the “CS 10K” goal: To
have 10,000 high school teachers capable of teaching the new Advanced
Placement (AP) exam in computer
science (CS) by 2015. Today, we have
about 2,000 AP CS teachers in the U.S.
How are we going to get to 10,000
high school CS teachers in five years?
Here’s a quick answer: We’re not going
to get there alone. We desperately need
to involve people who know how to prepare and develop teachers—faculty in
schools or colleges of education across
Let’s quickly set aside the idea of
computer science faculty teaching all
those 10,000 future high school teachers ourselves. What do we know about
preparing lifelong career teachers?
There are employers in IT who argue
that we are not particularly good at
producing our existing graduates for
today’s software development careers.
High schools are a completely new
kind of employer, with new kinds of
stakeholders, and new kinds of jobs.
Yes, we know computer science. They
know the rest. We need a partnership.
How do we convince the schools of
education that they want to work with
us? That’s a harder problem. Budgets
are tight. Education schools are not eager to develop new teacher education
programs. The just-released “Running
on Empty” report shows that few states
are teaching anything about computing, so there has to be a parallel effort
to create demand for new computer
science teachers. From the education schools’ perspective, they already
teach STEM teachers, and they probably already teach pre-service courses
about “technology,” although often
that means “How to teach a class how
to use Excel.” Why should they branch
out into computer science?
There is a good, mercenary answer:
There’s money in it. Besides the new
NSF CE21 program, the current U.S.
administration is funding more efforts
in STEM education. The Department
of Education and the White House
have said clearly that computer science
is part of STEM, but little of the STEM
education funding is aimed at computer science. That’s an opportunity with
little competition right now. The time
is ripe to form partnerships between
CS and education to improve computing education in high schools.
Daniel Reed is vice president of technology strategy &
policy and the eXtreme computing group at Microsoft.
Mark Guzdial is a professor at the georgia institute of