The Digital Promise Initiative

On Friday, U.S. Secretary of Education Arne Duncan announced the Digital Promise Initiative, a high-profile research effort “to advance breakthrough technologies that transform teaching and learning in and out of the classroom, while creating a business environment that rewards innovation and entrepreneurship”.* The reason why classrooms and business innovation are in the same sentence is the belief that new education technology requires “a more efficient market” and support for software developers to reach customers “on an economically valuable scale.”

I’m excited that school reform and technology is receiving such attention. We have a long history where the promise of educational technology never delivers any real change. I’m sure that some of my education colleagues will be skeptical about the private sector involvement in the initiative; today’s Wall Street Journal article was co-authored by Duncan and Netflix CEO Reed Hastings, and the program’s board includes John Morgridge, chairman emeritus of Cisco, and Irwin Jacobs, co-founder of Qualcomm. But to the contrary, I welcome the participation of leaders in information technology. After all, we’ll never have effective learning technologies in schools unless there are companies willing to invest in developing and marketing products to schools.

The key will be to get serious learning scientists involved with the initiative. Computers are wasted if their introduction to the classroom is not based on serious, substantial research about how children learn, both alone and in groups. Learning scientists are working to change that. The National Science Foundation is providing the Federal seed money (see their press release) of $15 million through its Cyberlearning program, and their web site shows that Janet Kolodner is the Program Officer; that’s promising, because Kolodner has been involved with learning sciences since its foundation, and was the editor of the field’s journal from 1991 to 2009. (And she was on the advisory board of a book I edited, The Cambridge Handbook of the Learning Sciences.)

Because of a history of failure, some skepticism about computers and schools is justified. But when systems are designed that are based in the sciences of how people learn, children learn better. The cutting edge of educational software doesn’t replace the teacher; it’s designed to facilitate more effective teaching. And in particular, the potential is that hybrid teacher-software curricula could align with what we know about how people learn deeper and more creatively: delivering connected knowledge, targeted to each learners’ developmental level, and bringing learners together through networked technologies to foster collaboration and communication.

As Duncan and Hastings say in today’s WSJ article, “this will happen. The only question is: Will the U.S. lead the effort or will we follow other countries?”

*Duncan and Hastings, “A Digital Promise to Our Nation’s Children.” WSJ Monday September 19, 2011, p. A15.

The Netflix Prize

Netflix announced its $1 million challenge in October 2006.  And the contest has now been won.  The big news is that collaboration was the key.

The Netflix web site has an automatic program that recommends movies that it thinks you will like, based on the number of stars you give to movies you’ve already rented.  They call this automatic program Cinematch.  Netflix can measure how well Cinematch works, by comparing the predictions it makes about how much you’ll like a movie, with the number of stars you actually give it after you watch it.  They have a bunch of very smart computer scientists who developed Cinematch, and in 2006 it was already very good.  So the Netflix challenge was going to be hard to beat: If you can develop your own prediction program and you can make it 10 percent better than Cinematch, you get one million dollars.

On Sunday July 26, two different teams both announced they had crossed the 10 percent better threshold.  Netflix is now comparing the two and will announce the winner in September.

The biggest lesson learned, according to members of the two top teams, was the power of collaboration. It was not a single insight, algorithm, or concept that allowed both teams to surpass the goal…Instead, they say, the formula for success was to bring together people with complementary skills and combine different methods of problem solving.*

The first team to win, BellKor, was a seven-member group.  None of the runners-up were solitary individuals; every solid contender, it turns out, was a team working collaboratively.  Contest rules then kicked in a 30-day period for any other entrants to give it their last best shot. What happened was that all of the leading teams merged together to combine their best ideas; a global team of about 30 members raced to beat the 30-day clock.  They called themselves The Ensemble.  As of July 26, The Ensemble seemed to be marginally better at predicting than BellKor: one-hundredth of a percentage point.  But those measures are submitted by the teams, and Netflix itself is going to take a couple of months making the official calculations…so, no winner will be announced until September.

David Weiss, a doctoral student in computer science at the University of Pennsylvania, and a member of The Ensemble, concluded:

The contest was almost a race to agglomerate as many teams as possible. The surprise was that the collaborative approach works so well.*

*Steve Lohr, “Learning the Power of Teamwork In a Netflix Race for $1 Million,” New York Times, Tuesday, July 28, 2009, pp. B1, B7.