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.

contact engagement

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

maRk GuzDiaL
to get 10,000 high
school cs teachers
in five years,
“we desperately
need to involve
people who know
how to prepare and
develop teachers—
faculty in schools
or colleges
of education across
the country.”

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.” http://cacm.acm.org/ blogs/blog-cacm/100067
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 the country.

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 technology.