What Happened at the AEI Debate on AI in Education This Week

AI is certainly neat, but it is not a school improvement plan.

Hey there - this is where I write on special Wednesdays about edtech and math education. Today that means:

• Letting you know how the AI + education debate in Washington, D.C. went on Monday a/k/a 🤓 nerd fight night 🥊.

• Sharing two of the fantastic ideas for teaching slope you all shared in response to last week’s newsletter.

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On Monday, four of us—

1. Shanika Hope, Google

2. Alex Kotran, AI Education Project

3. Jake Tawney, Great Hearts Academies

4. Me

—argued about the motion, “Maximizing School Improvement by 2035 Means Integrating AI into Classrooms Today,” in Washington, DC, at an event hosted by the American Enterprise Institute. We all had three minutes for our opening remarks. Here is what I prepared.

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Look—I’m not made of stone. I love the motion and wish it were true, this idea that we made a massive technological breakthrough three years ago and now we can improve schools like never before. I wish it were true. There are a few reasons why I don’t think it is.

The first is the work we have asked schools to do in 2025. We have asked schools to help kids read, write, do math, and be nice to each other all at a time when hormones are flying around the room like pinballs, in a country that has some of the highest child poverty rates of the developed world, at a time when kids are walking to school scared that they or their friends or their loved ones are going to get jumped out on by some dude in a mask dragging them to God knows where. It’s a hard job at a hard time. I tried it last week. I tried to teach slope of a line to eighth graders in East Oakland, wonderful kids in the Fruitvale neighborhood. Ask me how well that went. Kids have a lot more on their mind than math right now.

The second is to understand the tight resources we have given schools to do that job. Financial resources are tight, obviously, but I’m talking also about time. We give schools 180 days to turn 3rd graders into 4th graders. We give schools four days for teachers to get out of class, get together, and learn something new. And perhaps most importantly, administrators have limited reserves of social capital. You can’t go to your school board, your parent community, ten times a year and say, “Okay, we’re going to try something new, something big, everybody get on board.” You can do that once, maybe. Opportunity costs are high. Saying yes to one thing means saying no to ten other things by definition. So that one thing needs to have absolutely bulletproof evidence that it’ll help your school help kids learn to read, write, do math, and be nice.

So my third reason is that in 2025, after three years of trying, the evidence that AI can help schools do that work is extremely weak. I know you have seen the same happy headlines I have or the profiles of schools doing something novel with AI. But scratch even a millimeter beneath the surface of those studies and stories and you’ll find some very weak evidence. You’ll find weak controls, where the control group gets nothing, as it should, and the experimental group gets AI, as it should. But they also get something extra—extra time, extra tutoring, extra rich parents. Elsewhere, you’ll find positive results for AI but they’re in a basket full of point solutions that don’t congeal in any obvious way into a school improvement plan. Still other studies run the other direction, like the MIT study this summer, where kids who used AI to support their essay writing were effectively de-skilled, experiencing diminished cognitive activity and unable to recall the arguments they’d made, compared to students who didn’t use AI.

For those reasons—hard job, limited resources, high opportunity costs, weak evidence in favor of AI, my recommendation is we wait. We take a beat. We take the next bus. We wait for stronger evidence and then move. For now, if you want to maximize school improvement, it’s an easy call to wait rather than integrate AI.

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My comrade Jake Tawney argued that these tools would inhibit the formation of novice learners and novice teachers alike. In their arguments for the motion, Alex Kotran and Shanika Hope argued that:

• Kids will need AI skills for full US economic participation

• AI is being used outside of school, often poorly, and schools need to help kids learn to use it well

• AI will enable teachers to do better work than ever before, planning, differentiating, personalizing, preventing burnout, etc.

The debate was decided by a vote from the audience before and after the debate. The winner was whichever side most increased their share of the vote.

We won, which was fun of course, and the conversation kept everyone dancing, trying to stay on message, trying to answer the question we wished we’d been asked without seeming too obvious about it.

Jake and I counter-argued that many of the claims about the value AI offers teachers or students were dreams about the future rather than descriptions of the present. It is also a particularly unfortunate time to suggest that “we know what kids will need for economic participation in ten years,” given we are in the weakest labor market that software development has ever seen, ten years after telling every 12 year-old they needed to learn to code. That effort has gifted the private sector an oversupply of software developers who now have double the unemployment rate of art history majors.

If I had to guess what persuaded the audience to join us against the motion, it was our focus on “maximizing school improvement today.” In my closing argument, I said there were a bunch of motions I thought we’d all agree on, including the need for responsible experimentation, the need for dreaming expansively about what technology might offer kids. But maximizing school improvement today means taking seriously what a school most wants to improve, which is a kid’s ability to read, write, do math, and be nice, and applying the research we know works today. I suspect that approach gave some audience members permission to think AI is quite neat but also that 2025 is not the year that AI comes off the bench to maximize school improvement.

Mathematical Mailbag

I expressed difficulty last week keeping students thinking on a conceptual level about slope when the operations (“subtract, subtract, divide”) are so close at hand. Here are a couple of your very interesting responses.

Linda, offering an anchor activity that students can refer back to time and again as they try to make sense of new, related ideas:

1. I asked [students] if they realized that if you build stairs in your house that are too steep, it would be “illegal” because it could be dangerous. And that less steep stairs can be inefficient because they might take up too much space in a house.

2. I then gave each pair of students 12 identical Lego bricks.

3. I asked them to make 3 stair cases, using 4 bricks each, of different steepness.

4. After checking their stairs, I had them lay the 3 cases sideways on paper and had them trace it.

5. I then had them determine and record the rise and run of each of the stair cases. I checked those too.

6. Finally, they were to connect the top to the bottom and draw that line with a ruler. At that point, I asked them to record, “What do you notice about the lines you just drew and the slopes of the stairs?” We had conversations including the fact that some people’s stairs sloped downward to the right and others up. So, we also made that connection to positive and negative slope. Some noticed that larger slopes signified steeper stairs (and lines). In following days, when students were working on slope we would refer back to our “Lego stairs” to conceptualize what was going on.

Michael Hayashida, via email, illustrating how to help students understand the need for the measure known as slope:

Here’s something that seems to work in my freshman (somewhat remedial) math classes. All the kids have portable whiteboards.

“Draw me a set of axes and then draw a line that’s really steep.”

“Hold up the whiteboards - anyone have a line with the same steepness as someone else?”

“Ok, draw me a line that’s only medium steep.” They compare again.

“Ok, for mathematicians, this is a problem. They want precision - so that everyone draws a line with the same steepness when I give the instruction. To do that, you need to be able to put a number on steepness. Like... if I call for a line with a steepness of 5, then everyone draws a line with the same steepness. For the next minute, talk to your partner and see if you can come up with a way to measure steepness with a number.”

We share out. Sometimes kids will come up with an angle measurement method - kinda cool.

“Ok, this is actually a solved problem - mathematicians have already agreed on a way to measure steepness. Check this out - everyone put your marker on a lattice point - doesn’t matter which one. Now go over 1 and up 2 and put a point there. Do it again. Do it again. Connect the points. Hold them up - does everyone have lines with the same steepness? Ok, mathematicians call this a steepness of 2.

<Do the same thing, but with a slope of 0.5. Then 2.5.>

“This is how mathematicians decided to measure steepness - it’s what the y is changing by as x goes up by 1. They use a different word than steepness though - they call it slope”.