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SXSWedu 2013 – Bill Gates & Jessie Woolley-Wilson

BG: With that now I’m going to sit down and ask some of the CEO entrepreneurs to come out. And I want to start with Jessie Woolley-Wilson who is the CEO of Dreambox and doing amazing things. So let’s welcome Jessie. Welcome

JWW: Thanks.

BG: Well, Dreambox is off to a great start and tell us about how- what’s been the secret for your success?

JWW: Well, Dreambox is an intelligent adaptive learning technology that seamlessly integrates instruction with assessment to deliver millions of individualized learning paths for students, and right now our curriculum is focused on mathematics, elementary school mathematics. I think the secret sauce is that it delivers continuous real-time data that is relevant and actionable to both the student and the learning guardian be it a parent or a teacher.

So now we have an opportunity for technologies that were kind of on periphery of instruction kind of the rearview mirror, what happened yesterday, what do we need to do better tomorrow, to technologies that impact learning at the point of instruction when is the most important time to give that continuous feedback to learners.

The other piece of the secret sauce I think is that we are not just focusing on data around does the student get something right or does the student get something wrong. It’s much more about the thinking process, and the doing process. So in our technology we were actually capturing the strategies that students were using to solve problems, not just that they get it right or wrong but the strategies. So I’ll give you an example, let’s say that you and I are second graders and let’s say you’re really bright and I’m less bright, but promising. And Dreambox might- we have series of Virtual Manipulatives that we used so that students can show what they do. And Dreambox might ask us to build a number by using a math rack, so build the number 37, so you understand groupings and you recognize 10s, and you very quickly throw across three 10’s, and a 5 and two 1’s as one group. You don’t ask for help, you don’t hesitate, your mouse doesn’t hesitate over it. You do it immediately and ready for the next. I, on the other hand, am not as confident, and maybe I don’t understand grouping strategies. But I do know my 1’s. So I singly move over 37 beads. Now you got 37 and I got 37, and maybe in a traditional learning environment we will both go to the next lesson. But should we?

So in the Dreambox learning environment, you might be given an exercise around subtraction. Why didn’t you go to 40 and minus? In the Dreambox environment for me, they might take me earlier into the curriculum to reintroduce me to grouping strategies, so that I get exactly what I need in a very supportive environment. I don’t feel stupid sitting next to you. I feel inspired. It’s a gaming environment and we both get what we need when we need it. And I think that’s the last piece of the secret sauce, which is that we’re not a gaming company but we’ve leveraged gaming protocols to keep kids motivated, so that they persist through challenge. Because if the kids persist then they progress, if they progress, it’s their best shot at proficiency.

So I think these technologies are creating a new paradigm of learning where it actually doesn’t matter what zip code you come from, it doesn’t matter where you start, it just matters that you continue to evolve, demonstrate your thinking, and in doing so you get a comprehensive understanding of the topic and that’s transferable skills and, you know, it’s fun. I think learning can be and should be fun again.

BG: Well, adaption is always a big challenge. To what degree have you used research studies or clever techniques to lower the barrier to entry to foster increasing adaption on the product?

JWW: I will tell you one of our biggest challenges is de-risking the move to adaptive. People are confused by adaptive, a lot of people hear this term “Adaptive” but people don’t really understand what it is. And honestly in this- particularly in the public school system, there isn’t a lot of leeway for experimentation as you just said there are so many new technologies, there are so many new solutions. How is a teacher or an educator to pick? So I think one of the things that we tried to do is de-risk it. So we allow teachers and really parents to try it for free. And we found that when they are able to generate their own specific data about their kids in their classroom in their context, and they see the enthusiasms students have and they see the progression that often times they find waste to leverage federal money, or their operating budgets, the find ways to pay for what works.

BG: And so do you see the volumes going up quite substantially, this point?

JWW: So we started focusing on schools. We’ve been selling to schools for about two years and we’re in 48 states and the District of Columbia, but we really wanted to make principals and teachers heroes. And what happened was, we did that and then district resources took a look at it, and they decided to do a district-wide implementation. So we started with schools. It’s a much shorter sale cycle, that helps us, and we have a lot of parents who saw the kind of magic Dreambox in their kitchen, and they wanted to make sure that their students have it in their classroom as well.

It’s still a challenge, and it will continue to be a challenge as long as it is- there is no reward for innovation and experimentation. So the tough thing about this is if you experiment, then sometimes experiments are not successful, still good for you to know why they are not successful, but they are not successful, but in education context, you know, who wants their child to be on the experiment that doesn’t work.

BG: And are there teachers who’ve been resistant to using the approach and other teachers who’ve been more aggressive, I mean, you know, if somebody does a school or district-wide adaption, they are basically asking all the teachers to jump in and so how do you get them all on board?

JWW: We made a decision early on at Dreambox to bring teachers in. We took master teachers out of the classroom. People who understood classroom practice, understood mathematics deeply, and we sat them down next to software engineers, and we said collaborate. Talk about benevolent friction. But what resulted was a technology that these teachers wanted to use in their classroom. They have their thumb print on it. So we find that because we have these Virtual Manipulatives, a math rack, a number line, teachers are familiar with that. They use them already in their classrooms, so they don’t feel that the technology is overwhelming. They don’t feel stupid using the technology. They feel supported. They actually- a teacher told us, “It feels like I have a teaching assistant for every child in my classroom, even though my district can’t afford them anymore.” So this is a technology that is at the same time it’s student driven, it’s supported by teachers, and again a lot of relevant real-time data to teachers so that they can get unique insights about it individual learner, groups of learners, or whole classroom or district, and they can take action on that and modify their instructional practice so that teacher in that example saw that neither you or I understood grouping strategies. She could take that data and modify her instruction, and give another live instruction that’s better and more effective.

BG: And finally where do you see company going? You’ve done math you’ve done like all of K-5, what’s the future look like?

JWW: So we built this intelligence adaptive learning engine to be grade, age, and really content agnostic as long as we can get quality curriculum that can feed our adaptive engine, we don’t see that there is any limitation to what subjects we can cover. So if you, for example, divide the reading industry into learn-to-read, if you need like awareness in letter recognition, versus read-to-learn, there are a lot of applications of adaptive technology that are very promising, but one thing we will continue to do is focus on the thinking, focus on the strategies that student is not good enough to throw more data into teachers and into schools. They have a lot of data. They just don’t have the data that’s actionable, that’s relevant, and that’s easy to metabolize. And we are excited about we’ve been able to do so far.