Dan Meyer

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I'm Dan and this is my blog. I'm a former high school math teacher and current head of teaching at Desmos. He / him. More here.

The Unengageables

Halfway through my curriculum design workshops, I ask teachers to share their “secret skepticisms.” These are the sort of objections to new ideas that often take the form, “That would never work in my class because …. ” They share them anonymously in a Google Form before lunch.

The secret skepticisms came back in Phoenix two weeks ago and these four were easy to group together:

This process assumes every student wants to learn or has the motivation to learn.

How do I get students to buy-in when they struggle with any problem solving skills at all?

What if my kids donโ€™t know enough math to be engaged?

This approach is very compelling but this lesson will have additional challenges with students who could care less about getting involved. It is difficult getting any engagement by students who have little interest.

These responses were troubling. They seemed to emerge simultaneously from a deficit model of student thinking (ie. students lack engagement in the things we think they should be engaged in) and a fixed model of student intelligence (ie. these students are unengageable and that’s just the way it is).

Neither idea is true, of course.

What is true is that after years and years of being asked questions every day, students may find it odd to be asked to pose their own. After years and years of associating “math class” with a narrow range of skills like computation, memorization, solution, they may find it odd when you try to expand that range to include estimation, abstraction, argumentation, criticism, formulation, or modeling. After years and years of acclimating themselves to their math teacher’s low expectations for their learning, they may find your high expectations odd.

They may even resist you. They signed their “didactic contract” years and years ago. They signed it. Their math teachers signed it. The agreement says that the teacher comes into class, tells them what they’re going to learn, and shows them three examples of it. In return, the students take what their teacher showed them and reproduce it twenty times before leaving class. Then they go home with an assignment to reproduce it twenty more times.

Then here you come, Ms. I-Just-Got-Back-From-A-Workshop, and you want to change the agreement? Yeah, you’ll hear from their attorney.

“But it’s tough to start something this new in April,” a participant said.

That’s true. For similar reasons, it’s tough to start something new in a student’s ninth year of school. That doesn’t mean we don’t try. Thousands of teachers successfully change their practice mid-year and mid-career. Luckily, there are also steps we can take to acclimate our students gradually to new ways of learning math.

Here are three of them:

  • Model curiosity. I asked some kind of miscellaneous question on every opener. The questions weren’t mathematical. (eg. How much does an average American wedding cost? What’s the highest recorded temperature in Alaska?) I pulled them from different published books of miscellaneous facts and figures. This cost me very little classroom time and bought me quite a lot. It benefited my classroom management but it also built general, all-purpose curiosity into our classroom routine. That helps enormously when it comes to mathematical modeling where we’re telling students that we welcome their curiosity.
  • Ask the question, “What questions do you have?” Show any image or video from the top ten of 101questions. At the longest, this will take you one minute. Then ask them to write down the first question that comes to their mind. Take another minute to poll the crowd for their responses. (I model one polling procedure in this video.) This will also help your students to become more inquisitive and it will demonstrate that you prize their inquisitiveness.
  • Make estimation part of your daily routine. Modeling takes place on a cycle that runs from the very concrete to the very abstract and back again. Typically, we drop students halfway into the cycle with all kinds of abstract representations (formulas, line drawings, graphs) already given. Give your students more experience with concrete aspects of modeling like estimation by taking an image or video from Andrew Stadel’s Estimation 180 project and showing it to your students at the end of class. Ask them to write down a guess. Poll their guesses. Find out who has the highest guess and the lowest guess. Then show the answer.

Your students will come to understand you prize curiosity in general and their curiosity in particular. They’ll understand that mathematics comprises more than the intellectual hard tack and gruel they’ve been served for years. At that point, you can help walk them through activities involving estimation, abstraction, argumentation, criticism, formulation, modeling, and more, aware that each of your students can be engaged in challenging mathematics, that none of them is unengageable.

Related

Featured Comment

Kate Nowak:

Corny as it sounds, don’t give up. The first and second and tenth attempt at -whatever it is that’s a very different approach in your class – a 3Act, a project, a whatever it is — is probably going to either fall flat or fail spectacularly. The kids might get mad and weirdly uncooperative. Things might happen that you didn’t anticipate and don’t have the skills to handle. You aren’t going to get good at planning them until you get some experience planning them. You’re going to suck at this for a while. [..] You need to keep stretching the rubber band over and over until it loosens up and doesn’t snap back all the way.

Makeover Monday: Introduction

2013 Jun 26. See every edition of Makeover Monday.

Here is a “high-leverage teaching practice,” according to Deborah Ball:

Teachers appraise and modify curriculum materials to determine their appropriateness for helping particular students work towards specific learning goals. This involves considering students’ needs and assessing what questions and ideas particular materials will raise and the ways in which they are likely to challenge students. Teachers choose and modify materials accordingly, sometimes deciding to use parts of a text or activity and not others, for example, or to combine material from more than one source.

So every Monday this summer, I’ll post a problem from a textbook and start a conversation about how we could modify it. The details of that makeover may take the form of a loose sketch or something more formal. In either case, I’m going to be explicit about the goal of the makeover.

Fawn Nguyen, who’s been on an absolute tear lately, illustrated this process recently. She took this task:

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And then she showed how she implemented it with her students. Her goal wasn’t something formless along the lines of, “Well this sucks and I want to make it more engaging.” In the title of her post, she says explicitly she wanted students to have some personal, creative input on the constraints of the problem. So she had her students start by drawing their own golf course. She set a high bar for the rest of us.

You should play along. You can feel free to e-mail me a textbook task you’d like us to consider. Include the name of the textbook it came from. Or, if you have a blog, post your own makeover and send me a link. I’ll feature it in my own weekly installment. I’m at dan@mrmeyer.com.

The Do You Know Blue Student Prizewinner

Rebecca Christainsen had the highest score of any student on our Do You Know Blue machine learning activity. Yesterday was her last day of school at Terman Middle School in Palo Alto, CA, so Evan Weinberg, Dave Major, and I sent her math class a pizza party in her honor.

Because we’re keeping the activity available for you and your students to use as they study inequalities, we aren’t going to go into much depth on all the different rules contestants used. But I asked Rebecca how she came to her final, game-winning rule, and she told all:

My teacher first showed me the website, and I decided to try it out. My first attempt scored me only around 18%, but since hardly anyone had tried it out yet, I was ranked 33rd. After that, I was encouraged to try more equations, and suddenly thought of all the different types of equations that I could use, and moved to squared terms. One of the first equations that I came up with was b2>r2+g2. I simply used trial and error to come up with new equations, and I recorded each equation that I used and the percentage. I combined different equations together, and a few different combinations even had the same percentage.

Nobody beat that.

Extra Credit: How many of the Standards of Mathematical Practice does Rebecca evoke in that quote?

Great Moments In Mathematical Invention

I was in Australia this last week, working with some teachers at MYSA on You Pour, I Choose. It’s a task that asks which of two glasses has more soda and involves, among other skills, a fairly straightforward application of volume.

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A teacher in the workshop called me over. “I’m not a math teacher,” she told me, and then pointed to the person next to her who had calculated the formula for volume of a cylinder.

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“But that seems like more work than you need to do,” she said. “We don’t care about the exact amount. We care which one has more. With both glasses, we multiply by pi and square the radius. So all you really need to do is multiply the radius by the height for both glasses and compare the result. That’ll tell you which one has more.”

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This was a rather stunning suggestion, made all the more impressive by the fact that this woman doesn’t immerse herself in numbers and variables for a living like the rest of us.

I have two questions:

  • Is she right? She’s certainly right in this case. Both the volume formula and her shortcut indicate the left glass has more soda.
  • As her teacher, what do you do next?

I’ll update this post tomorrow.

2013 May 29. I knew just telling her, “That’s wrong.” would be unsatisfying because, explicitly, she said, “Am I wrong?” but, implicitly, she was saying, “If I’m wrong, then make me believe it.” I knew the current problem wasn’t helping me out because her shortcut actually worked.

I knew this woman had dropped me off deep in the woods of “constructing and critiquing arguments” but I didn’t know yet what I was going to do about it.

“Whoa,” I said. “Does that work? If that works that’s going to save us a lot of time going forward. Let me bring your idea to the group and see what everybody thinks.”

In the meantime I stewed over a counterexample. It took me more than a minute to think of one because a) I was kind of adrenalized by the whole exchange, and b) I don’t do this on a daily basis anymore so my counterexample-finding muscle has become doughy and underused.

I posed her shortcut to the group and said, “What do you think? Does this work?” I gave them time to think and debate about it. Someone came back and said, “No, it doesn’t work. Imagine two cylinders with different heights and a radius of one.”

Awesome, right? This particular counterexample doesn’t disprove the rule. The square of one is also one so her rule works here also.

Eventually someone suggested two examples where the product of the radius and height were the same but where the radius and the height were different in each cylinder. The shortcut says they should have the volume. The formula for volume says they’re different.

Final note: students are often asked to prove conjectures that are either a) totally obvious (“the sum of two even numbers is even” in high school) or b) totally abstract (“prove the slopes of two perpendicular lines are negative reciprocals” in middle school). It’s rare to find a conjecture that is both easily understood by the class and not obviously correct or incorrect. I’m filing this one away.

Great Lessons: Evan Weinberg’s “Do You Know Blue?”

If you and I have had a conversation about math education in the last month, it’s likely I’ve taken you by the collar, stared straight at you, and said, “Can I tell you about the math lesson that has me most excited right now?”

There was probably some spittle involved.

Evan Weinberg posted “(Students) Thinking Like Computer Scientists” a month ago and the lesson idea haunted me since. It realizes the promise of digital, networked math curricula as well as anything else I can point to. If math textbooks have a digital future, you’re looking at a piece of it in Evan’s post.

Evan’s idea basically demanded a full-scale Internetization so I spent the next month conspiring with Evan and Dave Major to put the lesson online where anybody could use it.

That’s Do You Know Blue?

Five Reasons To Love This Lesson

It’s so easy to start. While most modeling lessons begin by throwing information and formulas and dense blocks of text at students, Evan’s task begins with the concise, enticing, intuitive question “Is this blue?” That’s the power of a digital math curriculum. The abstraction can just wait a minute. We’ll eventually arrive at all those equations and tables and data but we don’t have to start with them.

Students embed their own data in the problem. By judging ten colors at the start of the task, students are supplying the data they’ll try to model later. That’s fun.

It’s a bridge from math to computer science. Students get a chance to write algorithms in a language understood by both mathematicians and the computer scientists. It’s analogous to the Netflix Prize for grown-up computer scientists.

It’s scaffolded. I won’t say we got the scaffolds exactly right, but we asked students to try two tasks in between voting on “blueness” and constructing a rule.

  1. They try to create a target color from RGB values. We didn’t want to assume students were all familiar with the decomposition of colors into red, green, and blue values. So we gave them something to play with.
  2. They guess, based on RGB values, if a color will be blue. This was instructive for me. It was obvious to me that a big number for blue and and little numbers for red and green would result in a blue color. I learned some other, more subtle combinations on this particular scaffold.

This is the modeling cycle. Modeling is often a cycle. You take the world, turn it into math, then you check the math against the world. In that validation step, if the world disagrees with your model, you cycle back and formulate a new model.

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My three-act tasks rarely invoke the cycle, in contrast to Evan’s task. You model once, you see the answer, and then you discuss sources of error. But Evan’s activity requires the full cycle. You submit your first rule and it matches only 40% of the test data, so you cycle back, peer harder at the data, make a sharper observation, and then try a new model.

The contest is running for another five days. The top-ranked student, Rebecca Christainsen, has a rule that correctly predicts the blueness of 2,309 out of 2,594 colors for an overall accuracy of 89%. That’s awesome but not untouchable. Get on it. Get your students on it.