By Diane Levitt
I joined Cornell Tech five years ago with a master’s degree in early childhood education and a career that mostly centered on education and philanthropy. I knew very little about computer science. I thought Java was coffee, Scratch was for itching, Python was a snake, and Basic was, well, basic. I came to Cornell Tech to explore what was possible in K-12 computing. Through this exploration, I’ve developed a set of values—a creed of sorts—that guides our work here at Cornell Tech.
Students thrive when we teach at the intersection of rigor and joy. In computer science, it’s fun to play with the real thing. But sometimes we water it down until it’s too easy—and kids know it. Struggle itself will not turn kids away from computer science. They want relevant learning experiences that lead to building things that matter to them. “I can do hard things!” is one of the most powerful thoughts a student can have.
Teachers matter. We can’t prepare students without preparing teachers. There is no online platform as effective as a skilled, caring human being in the room.
Great computer science teachers take many different paths to the classroom. On my team, we have four gifted master teachers from four backgrounds: special ed, social studies, tech, and design. There’s no traditional route to teaching K-12 computer science today. This is a shift from the recruitment of computer science teachers in the past and has an impact on how we recruit and prepare teachers. It also adds a wonderful dimension of diversity to our community.
Getting teachers prepared to teach computer science takes time and consistency. A few days of professional development here and there is not enough to get teachers ready for computer science. They need training and support over time. This was the thinking behind Cornell Tech’s Teacher in Residence program: we’re investigating whether putting a highly skilled computer science coach in a school for a year or longer helps teachers deliver instruction more competently and confidently.
The biggest lever we have is the one we aren’t using enough yet: preservice education for new teachers. The sooner we start teaching computer science education alongside the teaching of math and reading, during teachers’ professional preparation programs, the sooner we get to scale. It’s expensive and time-consuming to continually retool our workforce. Eventually, if every teacher enters the classroom prepared to include computer science, every student will be prepared for the digital world in which they live. This is what we mean by equity: equal access for every student, regardless of geography, gender, income, ability, or, frankly, interest.
We need to know more about how and what to teach. We have a little research and some survey data. We’ve transferred some research from other subjects. Some assumptions have been set in stone. This is an imperfect and difficult-to-navigate set of guidelines for educators. Because our curriculum comes from many sources, each with its own set of questions and reasons to research, we have a very fractured picture. We would learn a lot if, as a community, we agreed on a set of metrics for the next five years and were transparent about our findings.
Integrating computer science into other subjects is hard. There’s only so much time in the school day, and in response, there’s a serious effort to embed computer science into other disciplines as our best hope to reach every student. But can we bring computer science into a math lesson and do both subjects justice? I’ve seen some great examples that argue yes—and more that show one subject losing ground to the other. Better understanding the benefits and costs of integrating computer science is a high priority for our field.
It’s not (only) about jobs. When we focus on teaching computer science solely to fill open jobs in technology it changes what and how we teach. We sacrifice deep learning for short-term gains. We teach material that may be obsolete before our students enter the workforce. Our job is to prepare students for the world so they can seize all opportunities, personal or professional, that come their way. We need to let pedagogy — the practice of teaching based on the science of learning — lead the way.
We have to start planning for success. We can’t continue to offer introductory lessons to students who are on their way to mastery or we will bore them out of computing. We need to be ready for them with fresh curriculum that builds on their skills.
I’m more confident than ever that we can take a highly complex subject and translate it for every student. We can teach rigorous, joyful computer science to kids of all abilities from all backgrounds. We can prepare teachers from diverse backgrounds, grades, and subjects to understand and teach computer science. But we will have to do it intentionally, and commit time and money. There is still so much to learn. We need to know more to do better. But I’ve seen students with special needs, emerging bilingual students, students of color—all underrepresented in tech— navigate computing with dexterity and purpose. So I know it’s possible because it’s already happening for some. And now that we know it’s possible, we must make it happen for all.
This blog is the first in a series of posts called Ground Truth, which is a term from multiple fields describing information provided by direct observation as opposed to inference. Over the course of the year, I’m going to share conversations with some of the people whose leadership I’ve had the opportunity to observe and learn from. Observe with me and share your ground truth on Twitter (@diane_levitt).