Page 21 – iteration, making, building, and coding in education

Assessing assessment over time – similar triangles & modeling

I’ve kept a question on my similar triangles unit exam over the past three years. While the spirit has generally been the same, I’ve tweaked it to address what seems most important about this kind of task:

My students are generally pretty solid when it comes to seeing a proportion in a triangle and solving for an unknown side. A picture of a tree with a shadow and a triangle already drawn on it is not a modeling task – it is a similar triangles task. The following two elements of the similar triangles modeling concept seem most important to me in the long run:

Certain conditions make it possible to use similar triangles to make measurements. These conditions are the same conditions that make two triangles similar. I want my students to be able to use their knowledge of similarity theorems and postulates to complete the statement: “These triangles in the diagram I drew are similar because…”
Seeing similar triangles in a situation is a learned skill. Dan Meyer presented on this a year ago, and emphasized that a traditional approach rushes the abstraction of this concept without building a need for it. The heavy lifting for students is seeing the triangles, not solving the proportions.

If I can train students to see triangles around them (difficult), wonder if they are similar (more difficult), and then have confidence in knowing they can/can’t use them to find unknown measurements, I’ve done what I set out to do here. What still seems to be missing in this year’s version is the question of whether or not they actually are similar, or under what conditions are they similar. I assessed this elsewhere on the test, but it is so important to the concept of mathematical modeling as a lifestyle that I wish I had included it here.

(Students) thinking like computer scientists

It generally isn’t too difficult to program a computer to do exactly what you want it to do. This requires, however, that you know exactly what you want it to do. In the course of doing this, you make certain assumptions because you think you know beforehand what you want.

You set the thermostat to be 68º because you think that will be warm enough. Then when you realize that it isn’t, you continue to turn it up, then down, and eventually settle on a temperature. This process requires you as a human to constantly sense your environment, evaluate the conditions, and change an input such as the heat turning on or off to improve them. This is a continuous process that requires constant input. While the computer can maintain room temperature pretty effectively, deciding whether the temperature is a good one or not is something that cannot be done without human input.

The difficulty is figuring out exactly what you want. I can’t necessarily say what temperature I want the house to be. I can easily say ‘I’m too warm’ or ‘I’m too cold’ at any given time. A really smart house would be able to take those simple inputs and figure out what temperature I want.

I had an idea for a project for exploring this a couple of years ago. I could try to tell the computer using levels of red, green, and blue exactly what I thought would define something that looks ‘green’ to me. In reality, that’s completely backwards. The way I recognize something as being green never has anything to do with RGB, or hue or saturation – I look at it and say ‘yes’ or ‘no’. Given enough data points of what is and is not green, the computer should be able to find the pattern itself.

With the things I’ve learned recently programming in Python, I was finally able to make this happen last night: a page with a randomly selected color presented on each load:

Sharing the website on Twitter, Facebook, and email last night, I was able to get friends, family, and students hammering the website with their own perceptions of what green does and does not look like. When I woke up this morning, there were 1,500 responses. By the time I left for school, there were more then 3,000, and tonight when my home router finally went offline (as it tends to do frequently here) there were more than 5,000. That’s plenty of data points to use.

I decided this was a perfect opportunity to get students finding their own patterns and rules for a classification problem like this. There was a clearly defined problem that was easy to communicate, and I had lots of real data data to use to check a theoretical rule against. I wrote a Python program that would take an arbitrary rule, apply it to the entire set of 3,000+ responses from the website, and compare its classifications of green/not green to that of the actual data set. A perfect rule for the data set would correctly predict the human data 100% of the time.

I was really impressed with how quickly the students got into it. I first had them go to the website and classify a string of colors as green or not green – some of them were instantly entranced b the unexpected therapeutic effect of clicking the buttons in response to the colors. I soon convinced them to move forward to the more active role of trying to figure out their own patterns. I pushed them to the http://www.colorpicker.com website to choose several colors that clearly were green, and others that were not, and try to identify a rule that described the RGB values for the green ones.

When they were ready, they started categorizing their examples and being explicit in the patterns they wanted to try. As they came up with their rules (e.g. green has the greatest level) we talked about writing that mathematically and symbolically – suddenly the students were quite naturally thinking about inequalities and how to write them correctly. (How often does that happen?) I showed them where I typed it into my Python script, and soon they were telling me what to type.

In the end, they figured out that the difference of the green compared to each of the other colors was the important element, something that I hadn’t tried when I was playing with it on my own earlier in the day. They really got into it. We had a spirited discussion about whether G+40>B or G>B+40 is correct for comparing the levels of green and blue.

In the end, their rule agreed with 93.1% of the human responses from the website, which beat my personal best of 92.66%. They clearly got a kick out of knowing that they had not only improved upon my answer, but that their logical thinking and mathematically defined rules did a good job of describing the thinking of thousands of people’s responses on this question. This was an abstract task, but they handled it beautifully, both a tribute to the simplicity of the task and to their own willingness to persist and figure it out. That’s perplexity as it is supposed to be.

Other notes:

One of the most powerful applications of computers in the classroom is getting students hands on real data – gobs of it. There is a visible level of satisfaction when students can talk about what they have done with thousands of data points that have meaning that they understand.
I happened upon the perceptron learning algorithm on Wikipedia and was even more excited to find that the article included Python code for the algorithm. I tweaked it to work with my data and had it train using just the first 20 responses to the website. Applying this rule to the checking script I used with the students, it correctly predicted 88% of the human responses. That impresses me to no end.
A relative suggested that I should have included a field on the front page for gender. While I think it may have cut down on the volume of responses, I am hitting myself for not thinking to do that sort of thing, just for analysis.
A student also indicated that there were many interesting bits of data that could be collected this way that interested her. First on the list was color-blindness. What does someone that is color blind see? Is it possible to use this concept to collect data that might help answer this question? This was something that was genuinely interesting to this student, and I’m intrigued and excited by the level of interest she expressed in this.
I plan to take a deeper look at this data soon enough – there are a lot of different aspects of it that interests me. Any suggestions?
Anyone that can help me apply other learning algorithms to this data gets a beer on me when we can meet in person.

Building a need for math – similar polygons & mobile devices

The focus of some of my out-of-classroom obsessions right now is on building the need for mathematical tools. I’m digging into the fact that many people do well on a daily basis without doing what they think is mathematical thinking. That’s not even my claim – it’s a fact. It’s why people also claim the irrelevance of math because what they see as math (school math) almost never enters the scene in one’s day-to-day interactions with the world.

The human brain is pretty darn good at estimating size or shape or eyeballing when it is safe to cross the street – there’s no arithmetic computation there, so one could argue that there’s no math either. The group of people feeling this way includes many adults, and a good number of my own students.

What interests me these days is spending time with them hovering around the boundary of the capabilities of the brain to do this sort of reasoning. What if the gut can’t do a good enough job of answering a question? This is when measurement, arithmetic, and other skills usually deemed mathematical come into play.

We spend a lot of time looking at our electronic devices. I posed this question to my Geometry and Algebra 2 classes on Monday:

The votes were five for A, 5 for B, and 14 for C. There was some pretty solid debate about why they felt one way or another. They made sure to note that the corners of the phone were not portrayed accurately, but aside from that, they immediately saw that additional information was needed.

Some students took the image and made measurements in Geogebra. Some measured an actual 4S. Others used the engineering drawing I posted on the class blog. I had them post a quick explanation of their answers on their personal math blogs as part of the homework. The results revealed their reasoning which was often right on. It also showed some examples of flawed reasoning that I didn’t expect – something I now know I need to address in a future class.

At the end of class today when I had the Geometry class vote again, the results were a bit more consistent:

The students know these devices. Even those that don’t have them know what they look like. It required them to make measurements and some calculations to know which was correct. The need for the mathematics was built in to the activity. It was so simple to get them to make a guess in the beginning based on their intuition, and then figure out what they needed to do, measure, or calculate to confirm their intuition through the idea of similarity. As another chance at understanding this sort of task, I ended today’s class with a similar challenge:

My students spend much of their time staring at a Macbook screen that is dimensioned slightly off from standard television screen. (8:5 vs. 4:3). They do see the Smartboard in the classroom that has this shape, and I know they have seen it before. I am curious to see what happens.

Volumes of Revolution – Using This Stuff.

As an activity before our spring break, the Calculus class put its knowledge of finding volumes of revolution to, well, find volumes of things. It was easy to find different containers to use for this – a sample:

We used Geogebra to place points and model the profile of the containers using polynomials. There were many rich discussions about wise placement of points and which polynomials make more sense to use. One involved the subtle differences between these two profiles and what they meant for the resulting volume through calculus methods:

The task was to predict the volume and then use flasks and graduated cylinders to accurately measure the volume. Lowest error wins. I was happy though that by the end, nobody really cared about ‘winning’. They were motivated themselves to theorize why their calculated answer was above or below, and then adjust their model to test their theories and see how their answer changes.

As usual, I have editorial reflections:

If I had students calculating the volume by hand by integration every time, they would have been much more reluctant to adjust their answers and figure out why the discrepancies existed. Integration within Geogebra was key to this being successful. Technology greases the rails of mathematical experimentation in a way that nothing else does.
There were a few many lessons that needed to happen along the way as the students worked. They figured out that the images had to be scaled to match the dimensions in Geogebra to the actual dimensions of the object. They figured out that measurements were necessary to make this work. The task demanded that the mathematical tools be developed, so I showed them what they needed to do as needed. It would have been a lot more boring and algorithmic if I had done all of the presentation work up front, and then they just followed steps.
There were many opportunities for reinforcing the fundamentals of the Calculus concepts through the activity. This is a tangible example of application – the actual volume is either close to the calculated volume or not – there’s a great deal more meaning built up here that solidifies the abstraction of volume of revolution. There were several ‘aha’ moments and I saw them happen. That felt great.

Coding IS a super(edu)power

I’ve been really impressed by the Dan Meyer/Dave Major collaboration. If you don’t know what I’m talking about, you need to click on that link immediately. Seeing both Dan and Dave post on their respective blogs about the thought and rationale that goes into these activities is like a masters class in pedagogy, digital media, and user design.

The common thread that I really like about these tools is the clean and minimalist way they pose an idea, encourage a bit of play and intuition, and then get out of the way. Dan has talked about these ideas philosophically for a while, and seeing Dave make these happen is really exciting. They talk about this being the future of textbooks, but I am willing to wager that textbooks will get fidgety at displaying a task to a user atop a blank white screen. The trend has been so far in the other direction that I am skeptical, but I am hopeful that they will start to listen. These exercises are like a visit to the Museum of Modern Art. Textbooks and online learning otherwise tends to look either like a visit to Chuck-E-Cheese or the town library, over-thinking or under-thinking the power of aesthetics to creating a learning environment that is stimulating enough, but not distracting.

Being a committed Twitter follower, I of course interrupted their workflow with suggestions. I was looking for an easy way to collect student responses to a question along the lines of Activeprompt, but for tasks that are not about finding a location. I had posed a question to my Geometry class and was really excited about greasing the rails for gathering student responses and putting them in one place. This is the same idea as what Dan/Dave had done, but with a bit less of a framework pushing it in a direction.

Dave’s suggestion was, well, intimidating:

I had been playing around with web2py, Django, Laravel, and other template frameworks that said they would make things easy for me, but it just didn’t click how they would do this. I have done lots of small Python projects, but the prospect of making a website seemed downright unlikely. I spent three hours putting together this gem using the CSS I had learned from CodeAcademy:

I was not proud of this, but it was the best I thought I could do.

Through the power of Twitter, I was able to actually have a conversation with Dave and learn how he put his own work together. He uses frameworks such as Raphael.js and Sinatra in a way that does just enough to achieve the design goal. I learned that he wasn’t doing everything from scratch. He took what he needed from what he knew about these different tools and constructing precisely what he envisioned for his application. I prefer Python to Ruby because, well, I don’t know Ruby. I found Bottle which works beautifully as a small and simple set of tools for building a web application in Python, just as Dave had done with his tools.

Using Bottle and continuing to learn how it works, I made this yesterday.

I shared it with Dave, and he revealed another of his design secrets: Bootstrap. Again, dumbstruck by the fact this sort of tool exists, but also that I hadn’t considered that it might. This led me to clean up my previous submission and reconsider what might be possible. With a bit more tinkering, I turned this into what I had envisioned: a flexible tool for collecting and sharing student responses to a question

I was just tickled pink. Dave had shown me his prototype for what he made in response to my prompt – I was blown away by it, as with the rest of his work. Today, however, I proudly used my web app with two of my classes and was happy to see that it worked as designed.

The point behind writing about this is not to brag about my abilities – I don’t believe there is anything to brag about here. Learning to code has gotten a good mix of press lately on both the positive and negative side. It is not necessarily something to be learned on its own, for its own sake.

I do want to emphasize the following:

My comfort with coding is developed enough at this point that I could take my idea for how to do something in the classroom using programming and piece it together so that it could work. I got to this point by messing around and leaving failed projects and broken code behind. This is how I learn, and it has not been a straight line journey.
If I was not in the classroom on a regular basis, I doubt I would have these ideas for what I could do with coding if I had the time to focus on it completely. In other words, if I ditched the classroom to code full time (which I am not planning to do) I would run out of things to code.
Twitter and the internet have been essential to my figuring out how to do this. Chatting virtually with Dave, as an example, was how I learned there was a better way than the approach I was taking. There are no other people in my real world circles who would have introduced me to the tools that I’ve learned about from Dave and other people in the twitterverse. Face to face contact is important, but it’s even better getting virtual face time with people that have the expertise and experience to do the things I want to learn to do.
I have been writing code and learning to code from the perspective of trying to do a specific and well defined task. This is probably the most effective and authentic learning situation around. We should be looking for ways to get students to experience this same process, but not by pushing coding for its own sake. As with any technology, the use needs to be defined and demanded by the task.
The really big innovations in ed-tech will come from within because that’s where the problems are experienced by real people every day. Outsiders might visit and see a way to help based on a quick scan of what they perceive as a need. I’m not saying outsiders won’t or can’t generate good ideas or resources. I just think that tools need to be designed with the users in mind. The best way to do this is to give teachers the time, resources, and the support to build those tools themselves if they want to learn how.

You can check out my code at Github here. Let me know if you want to give it a shot or if you have suggestions. This experiment is far from over.

Building a need for algebraic reasoning – how can computers help?

I hear this all the time, and it drives me up a wall.

I haven’t solved for x in years, and I’m doing just fine.

Few people realize that while they aren’t using algebraic properties in their daily lives, they use the analog concept of finding missing values all the time. You won’t win this argument with most people though. It just doesn’t seem like algebra.

As math teachers, we also get annoyed when students are able to do this with nothing in between:

Certainly in a Calculus class, this should not surprise us – at that level we would expect an ability to eyeball the solution. At the other end of the post elementary math progression, however, when we are teaching two step equations for the first time, our response might be this: “Yes, you got that one, but I could give you one that has negative numbers or (GASP!) decimals or fractions in it. Then what would you do? This is why it’s important that you pay attention to this lesson. You have to do it this other way in order to get credit.”

I’ve had this conversation, and it has always made me feel ridiculous. It’s an arbitrary and crappy argument. It might be a valid one if standardized (or your own) tests of algebraic concepts are involved, but using tests as a motivation for doing anything makes the whole enterprise feel cheap, even when doing so needs to happen.

The bigger issue is that it perpetuates the reputation of math teachers and mathematicians as protectors of a sacred bag of secrets that nobody outside of a math classroom will need. It also presents a problem of artificiality. If I can suddenly make something harder by adding fractions or decimals, does doing so make it any easier for me to assess whether my students know what they are doing in solving an equation? I think we haven’t done a great job of building in the need for algebra, especially in light of what computers can do. I’ve never had a student sarcastic and comfortable enough with me to do this, but bear with me. The theoretical argument in the back of my mind to what I said in response to the student I described earlier is this:

Really teach? With that college degree of yours, you could make up a question that I can’t use my knowledge of arithmetic to solve? Impressive. I guess that even though I did everything my previous teachers told me to do – memorize multiplication tables, learn to add fractions with like/unlike denominators, draw lots of pie charts demonstrating equivalent fractions, AND draw lots of connect-the-dot dinosaurs as reviews of plotting in the coordinate plane, I still need you. Glad to be here. Oh, your tie is crooked. At least I can still help you out with that.

Furthermore, I wonder about the challenge of motivating algebra given that Wolfram Alpha, CAS, and even the lowly TI-83 solver can solve equations without breaking a sweat.

I’m not teaching introductory algebra right now, but the thinking I’ve done on how computers put the thinking back into process has me wondering how motivating the need for Algebra could be different, and better given how easy it is to compute these days. The most basic way that people interact with numbers is through tables and graphs – is it possible to motivate algebra through this familiar idea? Can we use the computer to compute a bunch of stuff, and see what it tells us?

Some food for thought:

This is precisely the sort of thing we are looking for when we are solving an equation, but it’s rare that we think about it this way. It’s also something that most people outside of a classroom will do with a table of values in a newspaper or a website, for example. It is typically for more practical reasons (predicting value of a stock, figuring out when a bus will arrive at our location from a schedule that doesn’t have every stop, etc) than simply finding ‘x’ as we ask students to do in the classroom. Is this algebra? Staring at a table of values is tedious, but I know people that would rather do this than solve an equation or do anything that smells like school math.

Again, in our adult lives, we make estimations from given information from a table or graph from time to time, but few adults actually call this algebra. Is it obvious to an adult that changing the interval in the right way would allow the exact answer to be found? Is it obvious to a student? It’s a subtle point here, but I think it’s the sort of reasoning we want our students to be capable of doing. Is that type of understanding something inherently important in algebraic reasoning? How’s that going for us now?

We know there are algorithmic ways to solve this one, but I’ve already said here and in previous posts that I want to get away from mathematical thinking as a bag of algorithms. How good of an answer to this can we get from a table? I don’t know about you, but I have yet to feel like I’ve taught well the idea of an irrational number in a good, intuitive way that doesn’t result in students memorizing tricks. I think this hints at this concept in ways that is inaccessible without using computers. Even on a calculator, it’s difficult to focus in on solutions as smoothly as I think can be done with a table of rapidly computed values.

I’m not suggesting that we shouldn’t teach properties of numbers and inverse operations in the context of solving equations algebraically. I think we need to do a better job of selling the idea of algebra as being an enhancement of what we already have built in to our brains. We estimate what time we need to cross the street to not get hit by a truck but also to minimize our time waiting. We know that if the high is 68 degrees at 3 PM, that it will probably be a nice temperature outside at one-o-clock. This way of feeling our way to a solution through intuition, however, is not the optimal way to solve problems, especially when our intuition is wrong. There needs to be a better way.

Our students (and many adults) often don’t know how to create tools to help them solve the problems they face. They choose to do things that are tedious because they don’t know a better way, and the math skills they have developed previously are disconnected and seem irrelevant as a result. We do understand the idea of computation, but we often aren’t good at doing it ourselves. If nothing else, it’s pushing people to become more confident that they know what they are looking at when we see a bunch of numbers together.

Computational modeling & projectile motion, EPISODE IV

I’ve always wondered how I might assess student understanding of projectile motion separately from the algebra. I’ve tried in the past to do this, but since my presentation always started with algebra, it was really hard to separate the two. In my last three posts about this, I’ve detailed my computational approach this time. A review:

We used Tracker to manually follow a ball tossed in the air. It generated graphs of position vs. time for both x and y components of position. We recognized these models as constant velocity (horizontal) and constant acceleration particle models (vertical).
We matched graphical models to a given projectile motion problem and visually identified solutions. We saw the limitations of this method – a major one being the difficulty finding the final answer accurately from a graph. This included a standards quiz on adapting a Geogebra model to solve a traditional projectile motion problem.
We looked at how to create a table of values using the algebraic models. We identified key points in the motion of the projectile (maximum height, range of the projectile) directly from the tables or graphs of position and velocity versus time. This was followed with the following assessment
We looked at using goal seek in the spreadsheet to find these values more accurately than was possible from reading the tables.

After this, I gave a quiz to assess their abilities – the same set of questions, but asked first using a table…

… and then using a graph:

The following data describes a can of soup thrown from a window of a building.

How long is the can in the air?

What is the maximum height of the can?

How high above the ground is the window?

Is the can thrown horizontally? Explain your answer.

How far from the base of the building does the can hit the ground?

What is the speed of the can just before it hits the ground?</li

I was really happy with the results class wide. They really understood what they were looking at and answered the questions correctly. They have also been pretty good at using goal seek to find these values fairly easily.

I did a lesson that last day on solving the problems algebraically. It felt really strange going through the process – students already knew how to set up a problem solution in the spreadsheet, and there really wasn’t much that we gained from obtaining an algebraic solution by hand, at least in my presentation. Admittedly, I could have swung too far in the opposite direction selling the computational methods and not enough driving the need for algebra.

The real need for algebra, however, comes from exploring general cases and identifying the existence of solutions to a problem. I realized that these really deep questions are not typical of high school physics treatments of projectile motion. This is part of the reason physics gets the reputation of a subject full of ‘plug and chug’ problems and equations that need to be memorized – there aren’t enough problems that demand students match their understanding of how the equations describe real objects that move around to actual objects that are moving around.

I’m not giving a unit assessment this time – the students are demonstrating their proficiency at the standards for this unit by answering the questions in this handout:
Projectile Motion – Assessment Questions

These are problems that are not pulled directly out of the textbook – they all require the students to figure out what information they need for building and adapting their computer models to solve them. Today they got to work going outside, making measurements, and helping each other start the modeling process. This is the sort of problem solving I’ve always wanted students to see as a natural application of learning, but it has never happened so easily as it did today. I will have to see how it turns out, of course, when they submit their responses, but I am really looking forward to getting a chance to do so.

A computational approach to modeling projectile motion, part 3.

I’ve been really excited about how this progression is going with my physics class – today the information really started to click, and I think they are seeing the power of letting the computer do the work.

Here’s what we did last time:

In a fit of rage, Mr. Weinberg throws a Physics textbook while standing in the sand box outside the classroom. By coincidence, the book enters the classroom window exactly when it reaches its maximum height and starts to fall back down.

Is it appropriate to neglect air resistance in analyzing this situation? Justify your answer.
We want to use this problem to estimate the height of the classroom window above the ground. Identify any measurements you would take in order to solve this problem. (No, you may not measure the height of the classroom window above the ground.)
Use your spreadsheet to find the height of the window as accurately as you can.

Note: This activity got the students using the spreadsheet they put together last time to figure out the maximum height of the object. They immediately recognized that they needed some combination of dimensions, an angle, and a launch speed of the book.

These tables of values are easy to read, but we want to come up with a more efficient way to get the information we need to solve a problem.

The table below represents a particular projectile. Identify as much about its movement as you can. How high does it go? How far does it go? When does it get there? That’s the kind of thing we’re interested in here.

Note that at this point the students are spending time staring at tables of equations. This is clearly not an efficient way to solve a problem, but it’s one that they understand, even the weakest students. They can estimate the maximum height by looking at the table of y-values, but the tedium of doing so is annoying, and this is what I want. I try to model this table of values with the spreadsheet they put together with them telling me what to do. Every time I change a value for initial speed or initial height, the location of the maximum changes. It’s never in the same place.

Eventually, someone notices the key to finding the maximum isn’t with the y-position function. It’s with the vertical velocity. When does the y-component equal zero?

This is where the true power of doing this on the spreadsheet comes alive. We look at the table of values, but quickly see that we don’t need a whole table. We go from this:

…to this:

Clearly this t-value is wrong. Students can adjust the value of the time in that cell until the velocity in the cell below is zero. A weak student will get how to do this – they are involved in the process. The tedium of doing this will prompt the question – is there a better way? Is this when we finally switch to an algebraic approach? No, not yet. This is where we introduce the Goal Seek tool.

The spreadsheet will do the adjustment process for us and find the answer we are looking for. With this answer in hand, we can then move on to posing other questions, and using goal seek to find the values we are looking for.

The process of answering a projectile motion question (how far does it go? how high does it go?) through a spreadsheet then becomes a process of posing the right questions:

This is the type of reasoning we want the students to understand within the projectile motion model. Whether your tool of choice for answering these questions is the graph, equations, or a table of values, posing these questions is the meat and potatoes of this entire unit in my opinion.

The next step is to then introduce algebraic manipulation as an even more general way to answer these questions, including in cases where we don’t have numbers, but are seeking general expressions.

Today I had a student answer the following questions using the goal seek method with the numerical models I’ve described above:

A ball is thrown horizontally from a window at 5 m/s. It lands on the ground 2.5 seconds later. How far does the ball travel before hitting the ground? How high is the window?

He solved it before anyone else. This is a student that has struggled to do any sort of algebraic manipulation all year. There’s something to this, folks. This is the opening to the fourth class of this unit, and we are now solving the same level questions as the non-AP students did a year ago with an algebraic approach and roughly the same amount of instruction time. Some things to keep in mind:

My students are consistently using units in all of their answers. It is always like pulling teeth trying to get them to include units – not so much at the moment.
They are spending their time figuring out the right questions to ask, not which equation to ‘plug’ into to get an answer.
They immediately see what information is missing in their model at the beginning of a problem. They read the questions carefully to see what they need.
The table of values gives them an estimate they can use for the problem. They have an idea of what the number should be from the table, and then goal seek improves the accuracy of the number.
At the end of the problem, students have all of the initial information filled out to describe all of the parts of the problem. They can check that the horizontal range, maximum height, and other waypoints of the path match the given constraints of the problem. This step of checking the answer is a built-in feature to the process of matching a model – not an extra step that I have to demand at the end. If it doesn’t match all of the given constraints, it is obvious.

I am looking for push back – is there anything I am missing in this approach? I get that deriving formulas is not going to come easily this way, but I think with a computer algebra system, it’s not far away.

Playing with robots – a weekend well spent

This weekend marked the culmination of a few months of work from my robotics students. We traveled to Shanghai to compete in the FIRST Tech Challenge tournament with 47 other teams. I got involved in FIRST nine years ago when teachers at my school in the Bronx tracked me down after hearing of my engineering background. They had just won the Rookie of the Year award the season before, and were excited to have an engineer around to help. Given that it was my first year teaching, I wasn’t able to be nearly as involved as I wanted to be. It was enough of a hook to get me to see how powerful programs like FIRST really are for working on the ‘demand’ side of the educational system, the problem-solving-hands-on-building stuff that makes students see what the end game of education can be. Playing with robots on a competition field is no more ‘real world’ than estimating the number of pennies in a pyramid, but the learning opportunities in both are rich and demanding. Nine years later, I am still as convinced as ever that these are the types of activities our students need to understand the context of the skills we teach them in our classrooms.

This weekend, we met stiff competition from our Chinese competitors. They built cascaded elevator systems, scissor lifts, and sensor systems that helped to play this year’s game, a tic-tac-toe variant played using colored rings on a set of horizontal pegs. More impressive for me was seeing the mentors noticeably bored and checking their phones while the students were the ones focused on tweaking their robots and fixing programming snafus.

This, however, was not our main challenge. The biggest issues that we faced were of our own creation – how to achieve consistency in our lifting mechanism using a web of zip-ties, or discovering just how unstable our own lifting mechanism was. The students were constantly sawing different parts of the robots off to make room for the solution to the last problem they created while trying to solve another. Clearing the complex residue of multiple good ideas to leave a simple, capable solution is the ultimate goal of a good design. The overall process of doing this is difficult, even with experience. They are early enough on the curve to know that there is much that they do not know though, and their positive and cheerful manner throughout was inspiring. Even after multiple technical issues and defeats on the field, they left the competition today feeling accomplished and full of ideas.

I was most inspired by my students’ reactions to seeing the clever designs of their Chinese counterparts. I have witnessed students wandering the pits at FIRST events and greeting unique and capable designs with accusation as the immediate reaction. “They could do that because they have so much more money” or “the mentors did all the work – it isn’t fair because we do everything on our team.” I understand the sentiment, but have always passed it off as being overly pessimistic. Some skilled teams make it look easy without always making obvious the associated level of effort required to execute such designs.

What made me particularly proud of my students this weekend was seeing them look at other designs and go through two stages of processing them. First, they would remark how cool it was that the team was able to solve the problem in such a unique way. Second, with some thinking about just how, they would say something along the lines of we could have done that.

While our ranking was closer to the bottom than I (or they) will reluctantly reveal, I don’t care much at this point. The team is young and will hopefully have more opportunities to learn and build together over the next couple of years. Their satisfaction was evident in watching the final matches with a clear sense of accomplishment, even while not being part of them. Their sense of togetherness is stronger than ever.

Our bus lost its headlights on the way back, forcing us to spend an hour and a half at a repair place while the driver and nine other people figured it out while the usual pattern of loud Mandarin was punctuated with hacking and drags off cigarettes. The team, meanwhile, procured a healthy supply of snacks and seemed content to sing along to music played off their school laptops. This is a close group that has only grown closer. Easily the highlight of the whole weekend right there.

The post where I remind myself that written instructions for computer tasks stink.

It’s not so much that I can’t follow written instructions. I’m human and I miss steps occasionally, but with everything written down, it’s easy to retrace steps and figure out where I went wrong if I did miss something. The big issue is that written instructions are not the best way to show someone how to do something. Text is good for some specific things, but defining steps for completing a task on a computer is not one of them.

Today I showed my students the following video at the start of class.
GEO-U6D2.1-Constructing Parallelogram in Geogebra

I also gave them this image on the handout, which I wrote last year, but students only marginally followed:

It was remarkable how this simple change to delivery made the whole class really fun to manage today.

Students saw exactly what I wanted them to produce, and how to produce it.
The arrows in the video identified one of the vocabulary words from previous lessons as it appeared on screen.
My ESOL students were keeping up (if not outpacing) the rest of the class.
The black boxes introduced both the ideas of what I wanted them to investigate using Geogebra, and simultaneously teased them to make their own guesses about what was hidden. They had theories immediately, and they knew that I wanted them to figure out what was hidden through the activity described in the video. Compare this to the awkwardness of doing so through text, where they have to guess both what I am looking for, and what it might look like. You could easily argue this is on the wrong side of abstraction.
I spent the class going around monitoring progress and having conversations. Not a word of whole-class direct instruction for the fifty minutes of class that followed showing the video. Some students I directed to algebraic exercises to apply their observations. Others I encouraged to start proofs of their theorems. Easy differentiation for the different levels of students in the room.

Considering how long I sometimes spend writing unambiguous instructions for an exploration, and then the heartbreak involved when I inevitably leave out a crucial element, I could easily be convinced not to try anymore.

One student on a survey last year critiqued my use of Geogebra explorations saying that it wasn’t always clear what the goal was, even when I wrote it on the paper. These exploratory tasks are different enough and more demanding than sitting and watching example problems, and require a bit more selling for students to buy into them being productive and useful. These tasks need to quickly define themselves, and as Dan Meyer suggests, get out of the way so that discovery and learning happens as soon as possible.

Today was a perfect example of how much I have repeatedly shot myself in the foot during previous lessons trying to establish a valid context for these tasks through written instructions. The gimmick of hiding information from students is not the point – yes there was some novelty factor here that may have led to them getting straight to work as they did today. This was all about clear communication of objectives and process, and that was the real power of what transpired today.

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