Here Is What It Takes to Make Effective Education Technology

Technologists need to understand that teachers are making ~1,000 decisions every minute.

Here is what it takes to make effective education technology:

The technologists on your team need to understand the nature of learning in schools and the educators need to understand how software gets made.

Neither group will become an expert in the other’s domain. But once they cross a certain threshold of empathy and understanding, they can start to make truly wild stuff together.

The technologists who once assumed learning is something like performing write operations on a database now understand that those write operations are contingent on circumstances like teacher skill, the social environment of the classroom, the school calendar, etc. The teachers who at one point might have made new feature requests for every new day of the year now understand that constraints are liberating, that the constraints of a platform’s architecture and user interface free its users to start using a platform rather than learning it. 

At that point of empathy and understanding, the educators and technologists start to make products that are multiplicative of their skills, not just additive.

A major conceptual leap for the technologists on an edtech team is to understand Ed Begle’s maxim, that “... education is much more complicated than you expected, even though you expected it to be more complicated than you expected.”

Technologists need to understand that the experiences they have learning in front of their laptops during their workdays—typing questions into Stack Overflow; watching explanatory YouTube videos; perhaps even riffing with some AI chatbot—while powerful and legitimate have very little in common with the work of learning in schools.

Here is one of ∞ examples of what I mean:

This is Jalah Bryant of Evergreen Public Schools in Vancouver, WA, shared with permission. She makes maybe a dozen key instructional decisions in the span of 44 seconds, some of which include:

1. Offering some direct instruction about one student’s work.

2. Noticing another student’s head is down while she’s concluding that first instructional moment.

3. Speculating on why that student’s head is down.

4. Making a plan for intervention.

5. Asking the student about their situation.

6. Suggesting a solution.

7. Reiterating high expectations for mathematical work.

8. Realizing the implications of that move on the student’s deskmate.

9. Suggesting a solution for that student.

The way she’s still wrapping up one interaction while planning her next one reminds me of the professional basketball players who have a complete and current inventory of all ten players on the court at all times, looking one direction while whipping a pass through traffic in another. It’s incredible.

That interaction between the teacher and student both precedes and determines any learning about the day’s subject! Their interaction isn’t about math per se. But the teacher’s conduct within it—is she inquisitive or presumptuous? is she empathetic or punitive? does she get what’s actually going on?–is highly predictive of how much math the student will learn.

Students are learning constantly in classrooms. It’s just that what they’re learning isn’t always explicitly about the subject matter. They’re learning about the world, about grownups, about power, and about themselves. When education technologists misunderstand or are oblivious to that complexity, they lower the odds dramatically that they’ll successfully build a product that makes a difference in a teacher’s teaching or a kid’s learning. When education technologists appreciate and learn to work within the complexity of classroom teaching, when educators and technologists enlist one another in partnership, well, okay, the odds are still very long but I like them a lot better.

BTW

• Come work with us!

• Here’s a recently released study about our curriculum: “The Effect of Desmos Math Curriculum on Middle School Mathematics Achievement in Nine States”

• FWIW I think Bryant offers a useful illustration of Deborah Ball’s concept of “discretionary spaces,” which you can watch more about in this keynote.

• Here’s a recording of a webinar I gave last week called “What Amazing Math Looks Like.”