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Mo Jebara, the founder of Mathspace, has responded to my concerns about adaptive math software in general and his in particular. Feel free to read his entire comment. I believe he has articulated several misconceptions about math education and about feedback that are prevalent in his field. I’ll excerpt those misconceptions and respond below.

Computer & Mouse v. Paper & Pencil

Jebara:

Just like learning Math requires persistence and struggle, so too is learning a new interface.

I think Mathspace has made a poor business decision to blame their user (the daughter of an earlier commenter) for misunderstanding their user interface. Business isn’t my business, though. I’ll note instead that adaptive math software here again requires students to learn a new language (computers) before they find out if they’re able to speak the language they’re trying to learn (math).

For example, here is a tutorial screen from software developed by Kenneth Tilton, a frequent commenter here who has requested feedback on his designs:

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Writing that same expression with paper and pencil instead is more intuitive by an order of magnitude. Paper and pencil is an interface that is omnipresent and easily learned, one that costs a bare fraction of the computer Mathspace’s interface requires, one that never needs to be plugged into a wall.

None of this means we should reject adaptive math software, especially not Mathspace, the interface of which allows handwriting. But these user interface issues pile high in the “cost” column, which means the software cannot skimp on the benefits.

Misunderstanding the Status Quo

Jebara:

Does a teacher have time to sit side by side with 30 students in a classroom for every math question they attempt?

[..]

But teachers can’t watch while every student completes 10,000 lines of Math on their way to failing Algebra.

[..]

I talk to teachers every single day and they are crying out for [instant feedback software].

Existing classroom practice has its own cost and benefit columns and Jebara makes the case that classroom costs are exorbitant.

Without adaptive feedback software, to hear Jebara tell it, students are wandering in the dark from problem to problem, completely uncertain if they’re doing anything right. Teachers are beleaguered and unsure how they’ll manage to review every student’s work on every assigned problem. Thirty different students will reveal thirty unique misconceptions for each one of thirty problems. That’s 27,000 unique responses teachers have to make in a 45 minute period. That’s ten responses per second! No wonder all these teachers are crying.

This is all Dickens-level bleak and misunderstands, I believe, the possible sources of feedback in a classroom.

There is the textbook’s answer key, of course. Some teachers make regular practice of posting all the answers in advance of an exercise set, also, so students have a sense that they’re heading in the right direction and focus on process not product.

Commenter Matt Bury also notes that a student’s classmates are a useful source of feedback. Since I recommended Classkick last week, several readers have tried it out in their classes. Amy Roediger writes about the feature that allows students to help other students:

… the best part was how my students embraced collaborating with each other. As the problems got progressively more challenging, they became more and more willing to pitch in and help each other.

All of these forms of feedback exist within their own webs of costs and benefits too, but the idea that without adaptive math software the teacher is the only source of feedback just isn’t accurate.

Immediate v. Delayed Feedback

Most companies in this space make the same set of assumptions:

  1. Any feedback is better than no feedback.
  2. Immediate feedback is better than delayed feedback.

Tilton has written here, “Feedback a day later is not feedback. Feedback is immediate.”

In fact, Kluger & DeNisi found in their meta-analysis of feedback interventions that feedback reduced performance in more than one third of studies. What evidence do we have that adaptive math software vendors offer students the right kind of feedback?

The immediate kind of feedback isn’t without complication either. With immediate feedback, we may find students trying answer after answer, looking for the red x change to a green check mark, learning little more than systematic guessing.

Immediate feedback risks underdeveloping a student’s own answer-checking capabilities also. If I get 37 as my answer to 14 + 22, immediate feedback doesn’t give me any time to reflect on my knowledge that the sum of two even numbers is always even and make the correction myself. Along those lines, Cope and Simmons found that restricting feedback in a Logo-style environment led to better discussions and higher-level problem-solving strategies.

What Computers Do To Interesting Exercises

Jebara:

Can you imagine a teacher trying to provide feedback on 30 hand-drawn probability trees on their iPad in Classkick?

[..]

Can you imagine a teacher trying to provide feedback on 30 responses for a Geometric reasoning problem letting students know where they haven’t shown enough of a proof?

I can’t imagine it, but not because that’s too much grading. I can’t imagine assigning those problems because I don’t think they’re worth a class’ limited time and I don’t think they do justice to the interesting concepts they represent.

Bluntly, they’re boring. They’re boring, but that isn’t because the team at Mathspace is unimaginative or hates fun or anything. They’re boring because a) computers have a difficult time assessing interesting problems, and b) interesting problems are expensive to create.

Please don’t think I mean “interesting” week-long project-based units or something. (The costs there are enormous also.) I mean interesting exercises:

Pick any candy that has multiple colors. Now pick two candies from its bag. Create a probability tree for the candies you see in front of you. Now trade your tree with five students. Guess what candy their tree represents and then compute their probabilities.

The students are working five exercises there. But you won’t find that exercise or exercises like it on Mathspace or any other adaptive math platform for a very long time because a) they’re very hard to assess algorithmically and b) they’re more expensive to create than the kind of problem Jebara has shown us above.

I’m thinking Classkick’s student-sharing feature could be very helpful here, though.

Summary

Jebara:

So why don’t we try and automate the parts that can be automated and build great tools like Classkick to deal with the parts that can’t be automated?

My answer is pretty boring:

Because the costs outweigh the benefits.

In 2014, the benefits of that automation (students can find out instantly if they’re right or wrong) are dwarfed by the costs (see above).

That said, I can envision a future in which I use Mathspace, or some other adaptive math software. Better technology will resolve some of the problems I have outlined here. Judicious teacher use will resolve others. Math practice is important.

My concerns are with the 2014 implementations of the idea of adaptive math software and not with the idea itself. So I’m glad that Jebara and his team are tinkering at the edges of what’s possible with those ideas and willing, also, to debate them with this community of math educators.

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Mercy – all of them. Just read the thread if you want to be smarter.

Can Sports Save Math?

A Sports Illustrated editor emailed me last week:

I’d like to write a column re: how sports could be an effective tool to teach probability/fractions/ even behavioral economics to kids. Wonder if you have thoughts here….

My response, which will hopefully serve to illustrate my last post:

I tend to side with Daniel Willingham, a cognitive psychologist who wrote in his book Why Students Don’t Like School, “Trying to make the material relevant to students’ interests doesn’t work.” That’s because, with math, there are contexts like sports or shopping but then there’s the work students do in those contexts. The boredom of the work often overwhelms the interest of the context.

To give you an example, I could have my students take the NBA’s efficiency formula and calculate it for their five favorite players. But calculating – putting numbers into a formula and then working out the arithmetic – is boring work. Important but boring. The interesting work is in coming up with the formula, in asking ourselves, “If you had to take all the available stats out there, what would your formula use? Points? Steals? Turnovers? Playing time? Shoe size? How will you assemble those in a formula?” Realizing you need to subtract turnovers from points instead of adding them is the interesting work. Actually doing the subtraction isn’t all that interesting.

So using sports as a context for math could surely increase student interest in math but only if the work they’re doing in that context is interesting also.

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Marcia Weinhold:

After my AP stats exam, I had my students come up with their own project to program into their TI-83 calculators. The only one I remember is the student who did what you suggest — some kind of sports formula for ranking. I remember it because he was so into it, and his classmates got into it, too, but I hardly knew what they were talking about.

He had good enough explanations for everything he put into the formula, and he ranked some well known players by his formula and everyone agreed with it. But it was building the formula that hooked him, and then he had his calculator crank out the numbers.

Real Work v. Real World

“Make the problem about mobile phones. Kids love mobile phones.”

I’ve heard dozens of variations on that recommendation in my task design workshops. I heard it at Twitter Math Camp this summer. That statement measures tasks along one axis only: the realness of the world of the problem.

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But teachers report time and again that these tasks don’t measurably move the needle on student engagement in challenging mathematics. They’re real world, so students are disarmed of their usual question, “When will I ever use this?” But the questions are still boring.

That’s because there is a second axis we focus on less. That axis looks at work. It looks at what students do.

That work can be real or fake also. The fake work is narrowly focused on precise, abstract, formal calculation. It’s necessary but it interests students less. It interests the world less also. Real work – interesting work, the sort of work students might like to do later in life – involves problem formulation and question development.

That plane looks like this:

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We overrate student interest in doing fake work in the real world. We underrate student interest in doing real work in the fake world. There is so much gold in that top-left quadrant. There is much less gold than we think in the bottom-right.

BTW. I really dislike the term “real,” which is subjective beyond all belief. (eg. What’s “real” to a thirty-year-old white male math teacher and what’s real to his students often don’t correlate at all.) Feel free to swap in “concrete” and “abstract” in place of “real” and “fake.”

Related. Culture Beats Curriculum.

This is a series about “developing the question” in math class.

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Bob Lochel:

I would add that tasks in the bottom-right quadrant, those designed with a “SIMS world” premise, provide less transfer to the abstract than teachers hope during the lesson design process. This becomes counter-productive when a seemingly “progressive” lesson doesn’t produce the intended result on tests, then we go back not only to square 1, but square -5.

Fred Thomas:

I love this distinction between real world and real work, but I wonder about methods for incorporating feedback into real work problems. In my experience, students continue to look at most problems as “fake” so long as they depend on the teacher (or an answer key or even other students) to let them know which answers are better than others. We like to use tasks such as “Write algebraic functions for the percent intensity of red and green light, r=f(t) and g=f(t), to make the on-screen color box change smoothly from black to bright yellow in 10 seconds.” Adding the direct, immediate feedback of watching the colors change makes the task much more real and motivating.

Before I get to the good, here’s the tragic, a comment from a father about a math feedback platform that I don’t want to single out by name. This problem is typical of the genre:

My daughter just tried the sine rule on a question and was asked to give the answer to one decimal place. She wrote down the correct answer and it was marked wrong. But it is correct!!! No feedback given just – it’s wrong. She is now distraught by this that all her friends and teacher will think she is stupid. I don’t understand! It’s not clear at all how to write down the answer – does it have to be over at least two lines? My daughter gets the sine rule but is very upset by this software.

My skin crawls – seriously. Math involves enough intrinsic difficulty and struggle. We don’t need our software tying extraneous weight around our students’ ankles.

Enter Classkick. Even though I’m somewhat curmudgeonly about this space, I think Classkick has loads of promise and it charms the hell out of me.

Five reasons why:

  1. Teachers provide the feedback. Classkick makes it faster. This is a really ideal division of labor. In the quote above we see the computer fall apart over an assessment a novice teacher could make. With Classkick, the computer organizes student work and puts it in front of teachers in a way that makes smart teacher feedback faster.
  2. Consequently, students can do more interesting work. When computers have to assess the math, the math is often trivialized. Rich questions involving written justifications turn into simpler questions involving multiple choice responses. Because the teacher is providing feedback in Classkick, students aren’t limited to the kind of work that is easiest for a computer to assess. (Why the demo video shows students completing multiple choice questions, then, is befuddling.)
  3. Written feedback templates. Butler is often cited for her finding that certain kinds of written feedback are superior to numerical feedback. While many feedback platforms only offer numerical feedback, with Classkick, teachers can give students freeform written feedback and can also set up written feedback templates for the remarks that show up most often.
  4. Peer feedback. I’m very curious to see how much use this feature gets in a classroom but I like the principle a lot. Students can ask questions and request help from their peers.
  5. A simple assignment workflow for iPads. I’m pretty okay with these computery things and yet I often get dizzy hearing people describe all the work and wires it takes to get an assignment to and from a student on an iPad. Dropbox folders and WebDAV and etc. If nothing else, Classkick seems to have a super smooth workflow that requires a single login.

Issues?

Handwriting math on a tablet is a chore. An iPad screen stretches 45 square inches. Go ahead and write all the math you can on an iPad screen – equations, diagrams, etc – then take 45 square inches of paper and do the same thing. Then compare the difference. This problem isn’t exclusive to Classkick.

Classkick doesn’t specify a business model though they, like everybody, think being free is awesome. In 2014, I hope we’re all a little more skeptical of “free” than we were before all our favorite services folded for lack of revenue.

This isn’t “instant student feedback” like their website claims. This is feedback from humans and humans don’t do “instant.” I’m great with that! Timeliness is only one important characteristic of feedback. The quality of that feedback is another far more important characteristic.

In a field crowded with programs that offer mediocre feedback instantaneously, I’m happy to see Classkick chart a course towards offering good feedback just a little faster.

2014 Sep 17. Solid reservations from Scott Farrar and some useful classroom testimony from Adrian Pumphrey.

2014 Sep 21. Jonathan Newman praises the student sharing feature.

2014 Sep 21. More positive classroom testimony, this entry from Amy Roediger.

2014 Sep 22. Mo Jebara, the founder of Mathspace, has responded to my initial note with a long comment arguing for the adaptive math software in the classroom. I have responded back.

In my modeling workshops this summer, we first modeled the money duck, asking ourselves, what would be a fair price for some money buried inside a soap shaped like a duck? We learned how to use the probability distribution model and define its expected value. We developed the question of expected value before answering it.

Then the blogosphere’s intrepid Clayton Edwards extracted an answer from the manufacturers of the duck, which gave us all some resolution. For every lot of 300 ducks, the Virginia Candle Company includes one $50, one $20, one $10, one $5, and the rest are all $1. That’s an expected value of $1.27, netting them a neat $9.72 profit per duck on average.

That’s a pretty favorable distribution:

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They’re only able to get away with that distribution because competition in the animal-shaped cash-containing soap marketplace is pretty thin.

So after developing the question and answering the question, we then extended the question. I had every group decide on a) an animal, b) a distribution of cash, c) a price, and put all that on the front wall of the classroom – our marketplace. They submitted all of that information into a Google form also, along with their rationale for their distribution.

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Then I told everybody they could buy any three animals they wanted. Or they could buy the same animal three times. (They couldn’t buy their own animals, though.) They wrote their names on each sheet to signal their purchase. Then they added that information to another Google form.

Given enough time, customers could presumably calculate the expected values of every product in the marketplace and make really informed decisions. But I only allowed a few minutes for the purchasing phase. This forced everyone to judge the distribution against price on the level of intuition only.

During the production and marketing phase, people were practicing with a purpose. Groups tweaked their probability distributions and recalculated expected value over and over again. The creativity of some groups blew my hair back. This one sticks out:

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Look at the price! Look at the distribution! You’ll walk away a winner over half the time, a fact that their marketing department makes sure you don’t miss. And yet their expected profit is positive. Over time, they’ll bleed you dry. Sneaky Panda!

I took both spreadsheets and carved them up. Here is a graph of the number of customers a store had against how much they marked up their animal.

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Look at that downward trend! Even though customers didn’t have enough time to calculate markup exactly, their intuition guided them fairly well. Question here: which point would you most like to be? (Realization here: a store’s profit is the area of the rectangle formed around the diagonal that runs from the origin to the store’s point. Sick.)

So in the mathematical world, because all the businesses had given themselves positive expected profit, the customers could all expect negative profit. The best purchase was no purchase. Javier won by losing the least. He was down only $1.17 all told.

But in the real world, chance plays its hand also. I asked Twitter to help me rig up a simulator (thanks, Ben Hicks) and we found the actual profit. Deborah walked away with $8.52 because she hit an outside chance just right.

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Profit Penguin was the winning store for both expected and actual profit.

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Their rationale:

Keep the concept simple and make winning $10s and $20s fairly regular to entice buyers. All bills – coins are for babies!

So there.

We’ve talked already about developing the question and answering the question. Daniel Willingham writes that we spend too little time on the former and too much time rushing to the latter. I illustrated those two phases previously. We could reasonably call this post: extending the question.

To extend a question, I find it generally helpful to a) flip a question around, swapping the knowns and unknowns, and b) ask students to create a question. I just hadn’t expected the combination of the two approaches to bear so much fruit.

I’ve probably left a lot of territory unexplored here. If you teach stats, you should double-team this one with the economics teacher and let me know how it goes.

This is a series about “developing the question” in math class.

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