What I learned in 2011

Two Thousand Eleven was a whirlwind of a year. A year ago at this time I thought I was headed to CU-Boulder to begin a PhD. A couple weeks later, a friend let me know about a job as a Math Coach for New Tech Network of schools. Soon after, I was hired and waved goodbye to my PhD aspirations for the time. I probably would have learned a lot in a PhD program, but I submit to you that I’ve learned a lot more in gross as an instructional and curriculum coach than I would have as a PhD student with classes and all.

Since I was hired, I had the opportunity to travel, meeting with teachers, administrators, students, and the occasional maintenance staff. I joined twitter, started this blog, rethought everything I thought I knew about Math education, read some books, and hopefully did some good in the process.

While I’ve learned a lot, mostly what I’ve learned is that I have a lot more to learn.

And since I’ve been preaching that students need time to reflect on their own learning, it’s only fair that I do it myself. Here are some things I learned in 2011.


I’ve learned to not trust anyone that uses the word “silver bullet” in regards to education unless it’s preceded by “there’s no such thing as a”.

I’ve learned that a science-minded person teaching a math class can be a beautiful thing.

I’ve learned that in general, teachers who blog or tweet are exceptional at their job.

I’ve learned that Angry Birds is going to be the dominant universal cultural zeitgeist of the next 10 years, and that it plays incredibly well with science and math instruction.

I’ve learned that United lets you board earlier if you book a window seat.

I’ve learned that Calumet High School in Gary, Indiana is a beautiful place.

I’ve learned that Chicago O’Hare might be my least favorite place in the world.

I’ve learned that having someone challenge what you believe is a great thing.

I’ve learned that people who say that you don’t need a college degree to get through life probably don’t know anyone who’s currently unemployed.

I’ve learned the difference between dressing up a problem to make it look good and a good problem.

I’ve learned that maybe the true value of Project Based Learning is to get you to tear apart your curriculum and rethink your own own teaching practices from scratch.

I’ve learned that maybe Mark Cuban was right to complain about NBA officiating.

Meanwhile, I’ve learned the Timberwolves aren’t.

I’ve learned there’s tremendous value in struggling through a math problem.

I’ve learned that most problems designed around cell phones need to be taken out into a field and beaten with hammers.

I’ve learned that teaching matters a lot more than the SES-is-everything folks think.

I’ve learned that the lack of a “data analysis” course in most high schools’ required four year math program is borderline criminal.

I’ve learned how to invoke cloture on an educational rant filibuster.

I’ve learned if you let testing be your excuse for poor teaching, it will sink you.

I’ve learned that this exists.

I’ve learned that crowd-sourcing is pretty much the way to go when it comes to generating curriculum.

I’ve learned that students like the problem solving, collaborative nature of mathematics. It’s a shame we don’t give them more of that.

I’ve learned to back off a lot on the “relevance” stuff.

I’ve learned I should not enter the Pizza Casbah pizza eating challenge.


What did you learn in 2011?


And lastly, I’d like to give a shoutout to my favorite problem of the year. The First EmergentMath Problem of the Year goes to…. (drumroll please)… Mr. Honner’s Equilateral Triangle Problem! First and foremost, it’s the problem that helped me invoke cloture during the aforementioned educational filibuster. I just sketched it out real quick while the filibusterer was going on and then asked him (or her) to tell me what he (or she) thought about it. For that alone, I’m eternally grateful to Mr. Honner. More than that though, it’s everything that I look for in a good math problem to pose to students: it gets right to the point, there are several routes toward a solution, there isn’t a clear one-size-fits-all solution, any student can access it on some level. I think it’s a near perfect Math problem, if there’s such a thing.


Here’s to a great 2011, and to a better 2012. After all, 2012 has an extra day so we should learn an extra 24 hours worth of material, right?

Attention Math Teachers: Slate has graciously discovered your next project

Slate.com’s always entertaining “The Explainer” segment runs an always-even-more entertaining year-end segment on the Unanswered Questions of the Year in which readers are prompted to vote on the question to be answered (aside: say, that’s a pretty awesome activity for a classroom. Students in the middle of a Problem vote on the question the teacher answers.)

This years’ edition contains burning questions such as “When you urinate in a toilet and there’s splashback, is that urine or toilet water?” and “Why do dogs like having their bellies rubbed?”

The one that I’m interested in is the following.


13. When parking in a nearly full parking lot, is it quicker to a) park in the first open space you see and walk, or b) drive a few laps around the lot and grab the closest possible spot? In my experience the two ways are about even, since the extra time spent driving for “b)” means a quicker exit when you leave. Please settle this using statistics as my wife has refused to argue anymore regarding this issue.

Tell me this isn’t a dilemma you play out in your head on a near daily basis.

I suppose you could use statistics, but this would make a super modeling project as well. Moreover, I have no idea what “level” of math a problem such as this requires and that’s a good thing. This could be a middle school project or an Algebra 2 project. This could be attempted by your high-flying AP Calculus-bound students as well as your remediated Algebra 1B students who probably hate the subject you’re teaching them.

So how do we pose this problem to students? A video of you driving around looking for a parking spot with your friend/spouse imploring you to “just park and we’ll walk!” might work. A few simple diagrams might work:

Does your school have parking issues? Particularly in the afternoon? Grab some footage. Or shoot, even the simple question posed in The Explainer may be interesting enough as is.

Guiding Questions

  • Does the size of the parking lot have anything to do with the decision to Park and Walk or to Keep Searching?
  • Do the number of parking spaces have anything to do with our decision?
  • How fast do people walk through parking lots?
  • How often are cars vacating their parking spots?

This is a good example of a problem that A) could potentially be immediately interesting to students (or at least could be posed in an interesting way), B) doesn’t necessarily have a correct solution, C) offers multiple routes through the problem, and D) can be accessed regardless of prior mathematics expertise.

What are some potential “next steps” students could take to engage in the problem? What are some potential mathematical routes to a solution? This is something to think about over the break, and as you’re vigorously searching for a parking space at the mall to buy that last-minute gift you’ve been putting off.

Update to previous post on weather: holy cow, WolframAlpha is amazing!

Previously, I tossed out a weekly local temperature plot and asked if you could tell when it started snowing. I also posited that it might be an interesting take periodic motion and/or sine curves.

The problem is, not every locale has a nice cache of temperature and dewpoint data.

Or do they?

Enter WolframAlpha. It’s praises have been sung elsewhere, but allow me: it’s temperature (and other weather) data and plots are fantastic. Whether it’s recent local temperature or geologic, global temperature, it’s there and easily digestible.

So what are your students interested in weather wise? Hurricane wind-speed? Climate change? The angle of the sun? You can quickly find data for these topics and more at WolframAlpha. Have fun!

How else can we leverage WolframAlpha’s awesome weather and climate-related data aggregation in the math classroom?