Category Archives: Project Based Learning

The Great (Mini) Robot Race

Robotics – The Synthesis Project

The final project of the two year academy program requires that the students design, fabricate, program and test an autonomous robot. We have been doing this project since the inception of the program, but this year we have made some significant improvements on the project. In this post I will explain the project, and highlight those improvements.

This project is an extremely challenging task that requires successfully completing several “sub-projects”. We tell the students at the beginning of the school year, that this project is more difficult than any of the other projects – by a long shot!

“If you haven’t done everything, then you haven’t done a thing.” – Red Whittaker

We completely changed our robot competition parameters this year. In previous years we had the students design sumo wrestling battle bots. Although this was a fun project, we started to notice that some robots performed really well without really having to “think”. These robots generally lumbered around the ring, sometimes without even actually “seeing” their opponents. Through pure luck they just managed to push their lighter opponents out of the ring. We decided that we needed to change the project in order to force teams to be smarter and we also wanted to get away from a robot competition that seemed to focus on aggressive battle.

Ironically, I suppose, our robot project changes were inspired by the classic Nova film that documented the DARPA challenge known as the Great Robot Race. In this race, the autonomous vehicles raced through the Mohave dessert on a course that was revealed to the competitors only hours before the beginning of the race.

Bob set about building an impressive “maze” for the robots to navigate. The robots had to make their way through a series of 90 degree turns defined by a series of connecting corridors with vertical walls about 20 cm tall. The robots were then given two attempts to make it through the course as fast as they could.

The Brains and Braun

When we first started this project about twelve years ago, we first used a Java based board that we liked, but it was really expensive and we didn’t really need much of the hardware and software features that it offered. About eight years ago, the Arduino board was taking the Maker community by storm and we decided to hop on the Arduino bandwagon, and we have been very happy ever since. The simplicity, online community, the plethora of code examples and tutorials as well as the price have been key points in why we have decided to keep using the Arduino. This year we decided to incorporate DC motors from Sparkfun and Adafruit’s motor shield. The combination allowed the students more flexibility regarding drive train design, and also allowed for some interesting discussions around the advantages and disadvantages of servos vs dc motors. Our only complaint with the shield would be that it would be nice to have the headers pre soldered!

Designing The Circuitry

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One of the major additions to the project was to require that students design and fabricate the circuitry for their robots. We did this by introducing two new skills to the project. Students had to learn how to use a printed circuit board (PCB) design software known as Fritzing, and then they had to learn how to fabricate their PCB boards using a CNC mill.

There are a number of amazing PCB design tools out there – and many are free! They all have their strengths and weaknesses. Here is what we found out as we did our research to find the right tool.

Autodesk’s Circuits is great because its web based, super easy to use and has an amazing feature where you can actually simulate the circuit. You can add a virtual voltmeter of ammeter to your virtual circuit and then with a push of a button, you can get virtual readings on the meters. I found this tool to be amazing for teaching circuitry and I allowed the students to use it as a “key” for their worksheets. It also has the ability to simulate an Arduino too! You can add an Arduino to your project, connect up LED’s, servos, etc. and actually see them light up or rotate as you change the code. It is a bit limited in that it doesn’t support most added libraries, but it is still amazing. We eventually decided not to use it for PCB design because it is unfortunately a bit clunky and doesn’t allow for much customization of the board.

Eagle is of course one of the most advanced and feature rich PCB design tools out there. It is also very complicated. IT of course offers the largest toolset, complete control of the design process and the free version is as close to a professional tool as one could hope for. The problem is that all these features come at a price – complexity. If we had an entire year to spend on this project, I might have decided to go with this tool, but we needed something that the students could learn quickly and weren’t going to get frustrated with…

Fritzing is a free, open source “beta” software that is very similar in look and feel to Autodesk’s Circuits – in fact I think Autodesk’s product must have been inspired by Fritzing? Although Fritzing lacks the amazing simulation tools that Autodesk Circuits has, it does offer a much better PCB design environment. The options that are available for editing the component foot prints, the PCB attributes, etc. make it really nice to work without making the tool too complex. This is the tool we decided to teach and use in class, and the students liked it.

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Fabricating The Circuitry

Back in the fall we decided to invest in a small CNC mill produced by a local company out of San Francisco named Other Machine Co. This machine, called the OtherMill has been an amazing addition to the lab. With this machine, we have been able to teach the students how to fabricate their own PCB’s. The OtherMill is not just for PCB fabrication, in fact we have used it to mill small aluminum parts as well.

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This micro CNC desktop mill is super easy to setup, really easy to use and plays really nicely with Fusion 360 – our 3D CAD and CAM software. I was incredibly surprised and pleased by how easy it is to learn the operating software – known as OtherPlan. The company has a great support website full of great tutorials, and we were able to teach all the students how to use the machine in just a few days.

The PCB files generated by Fritzing (we exported them as Gerber files) worked flawlessly with the OtherMill, and within a very short period of time, all the students had designed and fabricated single sided PCB boards for their robots.

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The Final Results

As with any major changes to a project, there are lessons to be learned. We realized that the task was rather complicated and many of the students did not make it as far through the course as they had hoped. It was clear however that this competition proved more interesting from the perspective of getting students to see the importance of software design. Not only did we see very different software strategies, but the variance in hardware design was surprising. They really had to think about how the hardware and software had to work together, and they had to think about optimization. This was a clear advantage of this competition over the previous year’s competitions. Students spent far more time trying to figure out how they were going to shave time off their attempts, and how they were going to adjust software and hardware to better navigate the course. From our perspective, the changes to the project proved to be fantastic, and we are looking forward to improving on the project design for this year. Some of the things that we are going to do this year is introduce some different sensors for the students (like “feelers”) and also give them a price list and budget so that they have more hardware choices.

Our Custom Designed Bridge Tester

Our Goal – Make A Better Bridge Crusher!

This year Bob and I decided to upgrade our bridge project. We wanted to create an improved device for measuring the load on the model bridges created by the students. Specifically, we wanted to design a way for the students to collect meaningful performance data.

The problem with our old method (filling a bucket with sand until the bridge catastrophically failed) was that it didn’t allow for the students to collect evidence about where and why the bridge failed. In many cases, the bridge actually experienced a significant failure, but because the bridge collapsed around the loading plate, the loading plate actually acted as a support for the bridge.

We had seen other “bridge testers” from vendors (http://www.pitsco.com/Structures_Testing_Instrumenthttp://kelvin.com/kelvin-bridge-material-tester-w-cpad/http://www.vernier.com/products/sensors/vsmt/) but we had the idea that perhaps we could create one that might be better, or at least it might be fun to try. In this post, we are going to share with you what we created and why we think it actually turned out really well, but we also point out some room for improvement.

The Frame

The frame of the entire device is really based on the Vernier Structures and Materials Tester. We thought this frame was probably the best, and we wanted to make our tester from extruded aluminum tubing as well. We went about designing the bridge tester in our favorite CAD program, Fusion360 by Autodesk. We sent our CAD file to the company 8020 and they precut all our t-slotted aluminum frame members to size. This was awesome because it made assembly super easy and it saved us on shipping too! Our experience with this company was amazing – they were super helpful and even gave us some really helpful advice. If you are thinking about making anything requiring t-slotted aluminum, definitely order from them.

The Load Sensors

We wanted a a bridge tester that actually gave us data that allowed us to figure out how and why the student bridges failed. That meant that we needed more data and we needed data that could be connected to the design and fabrication of the bridge. We noticed that all the vendors’ designs had only one load sensor, and some also had a way to detect overall deflection. We suspected that we could get better data if we had four independent load sensors – one for each abutment where the bridges were supported. The four sensors would (theoretically) give the students a way to analyze how the load was being distributed, and thus tell us something about the torsional behavior of the bridge.

Sparkfun load sensor

Sparkfun load sensor

I set out to learn a bit about load sensors and I came across a fantastic tutorial at Sparkfun (https://learn.sparkfun.com/tutorials/getting-started-with-load-cells). We ordered four load sensors (see picture above) from Sparkfun. Our design (shown below) has the four load sensors  fitted with 3D printed “shoes” as the bridge abutments.

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The four load cells.

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Two load cells with abutments.

The sensors are mounted on custom fabricated aluminum plates that can be moved laterally to accommodate slightly different bridge widths. The load sensors had to be connected to load amplifiers that were then connected to an Arduino (more on that below). The load sensors were mounted to the frame of the bridge tester on custom laser cut plates:

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Load cell amplifiers for two load cells.

The load amplifiers have to be used with the load sensors in order to amplify the signal so that the Arduino can read the data correctly.

The Loading Mechanism

Bob designed and fabricated the loading mechanism that was based on many of the designs we had seen online. It consists of a block that is free to move vertically up or down a threaded rod which is then connected to a spoked wheel.

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Loading wheel.

When the wheel is turned, the block moves up or down the threaded rod. This bar is connected to a loading plate via a metal cable that hooks into the loading plate and the block:

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Load plate from below – revealing loading wire attachment.

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Loading wire attached to threaded block.

The loading plate is placed on the loading plane of the bridge (the “roadway”), and then the bridge is loaded by spinning the wheel, which lowers the block, which pulls the bridge downwards:

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Loading plate on bridge.

Collecting The Data: The Software

 The software responsible for collecting the data is made up of two programs – one that runs on the Arduino micro-controller that is connected to the load sensors, and the other is a Processing sketch that runs on a computer/laptop connected to the Arduino via USB. The code is pretty simple, and it was mostly written using code from other sources and then modified for our specific purposes.

The Arduino code just collects the data from the four load sensors and then sends the data serially as a comma delimited package. The Processing code reads the serial port and then essentially dumps the data into a csv file. It does have some flourishes like a graphical display of the individual sensor loads as well as a display of the total load and whether or not the bridge has met the minimum load requirement set in the project descriptor.

You can view and download all the code here on GitHub.

The Performance Report

When the data is displayed in a graphing program, it looks like this:

Sample bridge data

Sample bridge data

You can see that the four sensors do not read equal values, and that the bridge begins distributing the load unevenly. The blue and orange lines show that these two load sensors were equally loading and were taking on a larger load than the green and red values from the other two load sensors. Later inspection of the bridge showed that this bridge failed at the load sensors that were recording a higher load value. Also, these sensors were located diagonally from one another, and once again showed that the bridge was being twisted.

You can also see that around 80 seconds (the 800 data sample) that the bridge experienced a sudden decrease in load – this was the point of failure. The data clearly shows a point at which the bridge failed and thus gives us a clear metric for performance.

The student teams were each given the results and were asked to answer these questions:

  1. What was the maximum load that your bridge sustained before failure?
  2. Calculate the load to weight ratio of your bridge.
  3. What were the individual maximum force values on each load sensor before failure?
  4. Identify on your bridge where the bridge failed. Take a picture of this point of failure and note its location.
  5. Based on the load data for the four sensors, describe why your bridge may have failed.
  6. What could you have done to increase the performance of your bridge?

The data really allowed for some rich analysis and the students were able to make some really informed critiques of their design and fabrication quality. We have been very happy with the results!

Future Improvements

For version 2.0 we hope to add these improvements:

  • Add the ability to measure deflection. We think that this might be done by measuring the angular displacement of the loading wheel, but we aren’t sure just yet.
  • Some way for the software to detect a failure – perhaps a way to detect a significant decrease in the load data. It would have to allow for some downward movement of the load data because there is some settling and deforming that can occur that might not be catastrophic.
  • It would be nice to clean up the code – especially the Processing code. I’d like to add some fancy GUI elements too so that it is a bit more attractive.

If you would like to build your own advanced bridge tester for your classroom, we can send you all our CAD files, software files and even answer questions. Its not easy to build, but its fun, and we spent about $350 dollars on this project as opposed to the $1000 to $1300 that the vendors are selling theirs for.

Simulate, Test, Analyze: A Framework For Rigor

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“Have Fun Storming The Castle!”

At the end of this fall semester, the second year students in the Academy rolled and carried their medieval mechanisms of mayhem to the SRHS track and we spent the afternoon watching the devices hurl lacrosse balls across the athletic field.This project was the final performance assessment of the semester and required that students design a gravitationally powered projectile launcher. This is an age old engineering/applied physics project.

Like many engineering projects done in high school, the physics principles governing the dynamics of the project are quite complicated, and ultimately the actual “application” of the science principles is often cursory. Students don’t have the background or mathematical abilities to to do the complex calculations needed to make an optimization adjustment to their mechanical device.This leads to the disconnection between the science content and engineering practice. Students don’t have the ability to make an informed decision about design choices. This is because it is difficult, very difficult.

Over the past few years I have been very interested in addressing this problem. This post discusses a framework that I have been working on to incorporate science into engineering projects. I think this framework allows high school students to engage in difficult scientific analysis without overwhelming them.

A Framework For Rigor

I won’t claim that this is a perfect solution, but so far I think we have experienced some success in creating a tighter relationship between science and engineering.  Last December I helped conduct a workshop at the NCCPA Professional Development Conference in Petaluma, CA. The name of the workshop was “NGSS, Prediction Reports and Your Science Class” and the point of this workshop was to give the attendees a framework for incorporating the Engineering standards into the science curriculum.  My co-presenter (Vipul Gupta) and I focused on the creation of prediction reports using computer simulations as a way to address two very important standards in the NGSS framework:

Using Simulations with Informed Input

Computer simulations are very popular in the educational space. They give teachers and students a virtual space where students can interact with virtual lab equipment or virtual objects that behave similarly to physical objects in the real world. With that said, they can fail to address students misconceptions because they do not always succeed in linking a conceptual model to the physical behavior. I also believe that the best simulations are ones that output data that can be analyzed with other scientific/mathematical tools. I also think that a good simulation requires that students provide meaningful input that gives them opportunities for analyzing the relationship between the input and the output.

Simulations used in engineering projects can be extremely helpful in addressing one of the main problems in engineering education. Students often design and build mechanical devices without understanding the physical principles that govern the design. The design process becomes an exercise in trial and error, or simply is reduced to copying a design from the internet.

To do a predictive analysis of a rocket’s flight, or a bridge’s structural performance is extremely difficult and often requires advanced mathematics and physics. Simulations can give the students the ability to analyze their designs and understand how changing the design inputs affects the output. Once again, it is important to find a simulation that requires students to understand the inputs and outputs.

Virtual Trebuchet

For example, in our project, students were introduced to an online Trebuchet simulation tool. This simulation tool is great because it requires that the student learn how to measure and calculate certain inputs. The students must have a working knowledge of rotational inertia, center of mass, and other concepts before they use the simulation. This was ideal for our project because it gave students a relevance and motivation . They had learn about these concepts in order to actually use the simulation. The students could then change certain inputs and see how that would change the efficiency of the design, or the range of the projectile. The point is that they needed physics knowledge in order to use the tool. They might not have the ability to know how the simulation eventually calculated the output, but they knew that the simulation required an understanding of the inputs.

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Example Report

The Prediction Report

The next step is to ask the students to prepare a prediction report. This report is designed to get students to demonstrate their understanding of the inputs, display evidence of the required calculations or measurements needed to create the inputs and then analyze the simulation outputs. In the report for this project, I asked students to show a set of calculations and measurements for determining the center of mass of their throwing arm and the rotational inertia (moment of inertia). Students also had to provide similar information for the counterweight.  The students then had to run the simulation and document the outputs from the simulation.

The Test:  Data is Needed

The next step is to test the device. To make this step more rigorous and to be able to relate the scientific analytical process to the engineering process, it is crucial for the students to collect data that can be used to analyze the performance of their device/product and then reflect on how they would improve their design.

For this project, we decided to use high-speed video and Vernier’s LoggerPro video analysis software to plot the position of the projectile as it was launched from the device.

The Analysis

The analysis is actually broken into two parts. The first part requires a collection of calculations while the second part uses those calculations to make some qualitative assessments.

For example, in the above project, students had to use the collected position data from the video analysis tool to calculate the kinetic energy of the projectile and then the efficiency of the device. They had to be proficient at the analytical tool, which in itself requires physics content knowledge, providing once again an opportunity to apply scientific models in the analysis portion of this engineering project.

I have included the instructions for the analysis report here: Projectile Launcher Analysis Report.

Finally, students are given the opportunity to use the information gathered in the analysis report to reflect on their design, and more importantly use the information to inform how they would improve on a future design. I have included below the set of questions that I asked my students:

  1. Compare the efficiency calculation of the simulation to the efficiency rating that you calculated for your actual performance. Please describe why you think these values are not the same.
  2. Consider the design of your trigger. What design and fabrication decisions would you change in order to improve your trigger, AND explain WHY you would make those changes.
  3.  Consider the design of your sling. What design and fabrication decisions would you change in order to improve your sling, AND explain WHY you would make those changes.
  4. Consider the design of your release mechanism (called the nose). What design and fabrication decisions would you change in order to improve this mechanism, AND explain WHY you would make those changes.
  5. Consider the design of your arm. What design and fabrication decisions would you change in order to improve your arm, AND explain WHY you would make those changes.
  6. Consider the design of all other components and the overall design. What design and fabrication decisions would you change in order to improve your device (other than the trigger, sling and arm), AND explain WHY you would make those changes.

Conclusion

The overall design of this framework can be boiled down to this:

  • Engage students in a computer simulation that simplifies the process of modeling and analyzing a complex physical/chemical/biological process, but be sure that the simulation requires some conceptual and computational thinking.
  • When testing the performance of the design (bridge, rocket, etc.) make sure that the students are required to  collect data that can be analyzed and that once again demands that they apply their theoretical models.
  • Design an assessment that uses the analysis and gives the students an opportunity to make informed judgements of their designs for the purpose of redesign.

Building the Electrical Current Model with The Amazing $25 Programmable Power Supply

Not Just For Teaching Robotics

Thanks to the generous donations of supporters of the Physics Academy, we were able to purchase a new set of Arduino Uno micro-controllers for use in this year’s robotics competition. As I was planning out the unit on teaching DC circuits, I realized that some of our DC power supplies might need to be replaced. I got to thinking – could the Arduino replace these hulking, expensive power supplies?

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The answer has been (with one caveat) – yes. The above power supplies are nice, no doubt about it, but they are big, costly ($199) and they are not as nearly as extensible as a micro-controller.

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The Arduino micro-controller can act as a fixed 5V power supply, or using its PWM pins, you can vary the voltage from 0V to 5V with a resolution of about 20 mV. The other advantage about using the Arduino is that it gives you a chance to teach a little bit of programming too! In our case, it allows for a great introduction to robotics well before we are ready to start our unit on robotics.

The one disadvantage is that you can’t test any circuits that need over 5V of electrical potential difference, nor can you test things like motors or other higher current (> 40 mA) circuits. We didn’t find this to be a big problem, but if you do, you can actually purchase a shield (an attachment that fits on top of the Arduino) from Adafruit Industries that allows you to use a higher voltage, higher current power supply that is controllable through the Arduino.

Mapping Electrical Potential (Voltage)

One of the first activities that the students do, which is a great activity from the AMTA curriculum repository, is to have the students “map” the voltage between two metal bars that are partially submerged in water.

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Using the Arduino as the power supply, the students use a multimeter to check the voltage at specific locations on a grid that is placed under the transparent pan holding the water. These numbers are recorded into a spreadsheet. Excel has a great tool for doing a 3D map of the values.

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What results is a really nice visualization of the potential isolines and the spacial variance of the voltage, and thus the electrical field.

Ohm’s Law – A Flow Model

We then move from voltage maps to flow model. The students investigate how voltage, current and resistance are related to one another. The students begin by investigating the current flowing into and out of a resistor, and most are surprised to find that the current in the same flowing into a resistor as it is flowing out. They expect that current should be “used up” by the resistor – causing a bulb to glow for example. When they find that this is not the case, they either think that they have done the experiment incorrectly or that perhaps the multimeter is not precise enough. This confusion comes from the idea that they are expecting current and energy to be equivalent.

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The hydrology analogy is introduced as a possible model for describing this phenomenon. We discuss the movement of water past a water wheel, and how the water flowing into the wheel is equal to the amount of water flowing “out” from the wheel. Students quickly realize that the wheel still turns, not because the water is “used up”, but because the water looses energy.

The final challenge for the students is to confront the oddity that is parallel circuits. This is made a bit easier by thinking about the flow model, but the confusion with parallel circuits stems from the idea that a battery is a constant current supplier – which of course it is not. The Arduino, just like a battery, will increase the amount of current flowing from its digital output pins when more pathways are added for the current to flow. This is where I would be careful to make sure however that you don’t approach the 40 mA limit. If you do, you can get some weird results in your observations as the Arduino will naturally cut off current draws around this range to protect its electronics.

Conclusion

The switch to the Arduino has been quite successful, and as stated before, it launches the students into the robotics project with a knowledge that the Arduino is simply a controllable power supply. They learn very quickly from that point on that the Arduino can also act like a voltmeter too! Using its analog input and switching the digital pins to be input pins, the Arduino can also mimic the functionality of a multimeter. If you are considering new power supplies, I would recommend looking into this as an option.

A Modernized Bridge Design Contest

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Modernizing An Old Classic

We have just completed the second project in the Academy for the 2014-15 school year. It was a huge success! This project takes a classic physics project and “upgrades” it by incorporating modern engineering design technology and fabrication techniques.

We started with a great project that is now available online through Engineering Encounters. This was a project that was originally published by Stephen J. Ressler of the United States Military Academy. It is a rigorous approach to designing and building bridges from file folders:

https://bridgecontest.org/resources/file-folder-bridges/

Its a great project with an incredible set of resources, background information, and step by step instructions. Unlike less rigorous and involved bridge design projects (using toothpicks for example), this project has the students building compression members (beams) and tension members (cords) and gussets to better model real world designs and to give the students the opportunity to learn and make decisions about which members to use in different parts of their own designs.

The only issue that we had with this project is that it requires the rather tedious process of having students trace out the unfolded beam designs onto file folder material and then use scissors and  blades to cut out each beam and cord. But we have a laser cutter! There had to be a way to incorporate both 3D CAD design and our laser cutter in order to modernize this process. We also knew that Autodesk Inventor had some really amazing tools for analyzing design structures.

From Sheet Metal To Manila Folders

Autodesk Inventor has an amazing set of tools for designing sheet metal parts. Using these tools, an engineer can construct 3D models made of folded metal parts made from just about any thickness of metal stock. Once you have designed the folded metal part, Inventor will create a flat pattern design for you that you could then send to a CNC plasma cutter to cut from sheet metal stock. You would then fold the part up manually and you would have your folded part.

Inventor gives you the ability to custom define the thickness of your stock, and some of the parameters around how it can be bent. We defined our stock to be as thick as manila folder paper. The next step is a bit tricky, but with the help of a great video I came across from Rob Cohee, we were able to define custom folded paper beam stock that the students could then use to build out their frames. Once again, Inventor has an amazing set of tools for defining structural frames (called The Frame Generator) that can then be populated with any kind of structural beam. You can also define your own structural beams that can be used to populate your frame.

I have included a video below that we use with the students to help guide them through this process:

Using the frame generator tool in Inventor also allows the student to miter and trim the beam members, which allows the students to focus on design rather than getting lost in the time consuming process of calculating the cut angles. The following video shows you how this can be done:

Once the students had designed the bridges, it was time to prepare the flat patterns and have the laser cutter do the work of cutting them out.

Fold, Glue, Repeat. (Some Assembly Required)

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The students prepare their flat pattern cut-outs for the laser cutter and then you let the laser “rip”! Its awesome to sit back and watch this machine cut. I never get sick of watching it! Having the students do this would take SO much longer, the cut parts would be less accurate, and as all CTE teachers know, one of the most dangerous tools in the shop is an Exacto blade.

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Some might argue that the “manual” process of cutting all these beams out by hand is “good for the students”, but we feel that saving time here allows us to use that time in other areas, such as virtual testing.  Before the students get to build their design, we ask them to use Inventor’s frame analysis tools to help them analyze potential weaknesses in their designs. The following video shows just how amazing this tool is:

Once the students have done their analysis and cut their construction members, its time for folding and gluing, and folding, and gluing, and … At this point our project does not differ from the Engineering Encounters project. The students use a sheet of paper (actually two 11 x 17 sheets) with an elevation view (printed from Inventor as a CAD drawing) glued to a board as a guide for assembling the beams, cords and gussets:

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This process goes relatively quickly as the students have done all the prep work to make sure that the pieces all fit together. Once again, this really demonstrates how modern technology can allow the students to focus their attention on design.

To Break Or Not To Break

Once the bridges are assembled, its time to test them out. The performance metrics for the contest are not actually based on the strongest bridge but rather a more realistic approach. We have attached a monetary value to each beam, gusset and cord. The bridges are then tested to a set value – the required load. The bridge that holds that load and is “manufactured” least amount of money is then given the highest marks.

Once the bridge has been tested at the required load, we then give the students the choice to see just how much the bridges can hold before catastrophic failure. Most students (encouraged by both peers and staff!) decide to take their bridge to the limit.

Its always a fun way to end the project!

Analyzing A Rocket’s Performance – A Common Core Assessment

Overview: What is Common? Argumentation

You might be one of the many Americans that are a bit perplexed by this whole new Common Core State Standards (CCSS) “stuff”. In this post I will try my best to explain how I designed an assessment for the first year students in the Academy that aligns with the Common Core. This was partly motivated by a district wide push to bring all curriculum in alignment with the CCSS, specifically as it relates to literacy.

For context, I will identify the educational goal that in part motivated this effort. Our school site administration has identified argumentation as a key curricular focus that all staff will address this year. This has given the school the ability to focus on literacy and has allowed the school staff to guide their efforts towards a collaborative goal.

This assessment was organized into three parts: the prediction, the analysis, and the reflection. Each part of the assessment focused on specific standards.

Part 1: The Prediction Report

If you haven’t had a chance to read a previous post where I describe how the students conducted experiments and collected data pertaining to building a predictive model, then I might suggest it, as it is really the first part of this assessment.

The standards addressed in this part of the assessment are as follows:

CCSS.ELA-Literacy.RST.11-12.3
Follow precisely a complex multistep procedure when carrying out experiments, taking measurements, or performing technical tasks; analyze the specific results based on explanations in the text.

CCSS.ELA-Literacy.RST.11-12.7
Integrate and evaluate multiple sources of information presented in diverse formats and media (e.g., quantitative data, video, multimedia) in order to address a question or solve a problem.

To summarize the first part of the assessment, the students were required to collect data in order to create a prediction report describing the performance of their model rockets. The report had to include these elements:

  1. Force diagrams (free-body diagrams) depicting the predicted forces acting on the rocket during the a) thrust phase, b) cruise phase, and c) descent phase.
  2. Net force equations that identify the causal relationship governing the motion state of the rocket.
  3. Three motion graphs depicting the predicted behavior of the rocket. This included its predicted acceleration, velocity and position as a function of time.

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The student teams submitted these reports prior to the actual launch.

Part 2: Analysis Report

The next step was to run the actual experiment – the launching of the rockets! Although the launch day was soggy, we still had a successful afternoon, and we got some great data. The details of the launch are described in a previous post.

The standard addressed in this part of the assessment was as follows:

CCSS.ELA-Literacy.RST.11-12.9
Synthesize information from a range of sources (e.g., texts, experiments, simulations) into a coherent understanding of a process, phenomenon, or concept, resolving conflicting information when possible.

The students were given their prediction reports back, and then also given the data from the small altimeters that were used to collect altitude data. The students were then asked to create an analysis of their rocket’s performance:

IMG_0834

This report required these elements:

  1. Using the data analysis tools in LoggerPro, they had to identify:
    1. The acceleration of the rocket during the thrust phase (a best estimate)
    2. The acceleration of the rocket during the cruise phase (a best estimate)
    3. The maximum velocity of the rocket (a best estimate)
    4. The descent velocity (a best estimate)
  2. A velocity vs time graph from the information above.
  3. An acceleration vs time graph.

Part 3: Reflection (Addressing Counter-claims)

The final part of the assessment asked the students to compare the prediction and analysis reports and then propose reasons for discrepancies between the data. I also asked the students to respond to some Aristotelian counter claims by using their data and the models that we had collectively established in class.

The standards addressed in this part of the assessment were:

CCSS.ELA-Literacy.RST.11-12.8
Evaluate the hypotheses, data, analysis, and conclusions in a science or technical text, verifying the data when possible and corroborating or challenging conclusions with other sources of information.

CCSS.ELA-Literacy.WHST.9-10.1.a
Introduce precise claim(s), distinguish the claim(s) from alternate or opposing claims, and create an organization that establishes clear relationships among the claim(s), counterclaims, reasons, and evidence.

I asked the students to respond to the following questions which required that the students use data to support their analysis.

  1. Compare the predicted NET force on your rocket during the thrust phase to the actual NET force on your rocket during the thrust phase by using your data – you will need to estimate the actual NET force during this phase. Using these numbers as evidence (you must include these values in your answer), describe at least one reason these values are different.
  2. Compare the predicted maximum height of your rocket with the actual maximum by using your data. Using these numbers as evidence (you must include these values in your answer), describe at least one reason these values are different.
  3. Compare the predicted descent velocity during the descent phase to the actual descent velocity from your data. Using these numbers as evidence (you must include these values in your answer), describe at least one reason these values are different.
  4. Look at your data and then also at your prediction graphs. Describe at least two differences between the graphs, AND WHY you think these differences exist.
  5. Based on the actual data you collected, what design changes would you make IF you could create this rocket from scratch again? Give at least two examples of design changes you would make.

I also included two questions that asked the students to respond to an alternative explanation for the behavior of their rocket. These claims were specifically created in order to address student misconceptions involving inertia and residual forces.  Below I have included the questions and example student responses:

Question 1:
“Make a counter claim to the following statement from someone who is an “Aristotelian”: The reason that the rocket continued to move upwards after the fuel had run out is that the fuel force continued to push on the rocket, but lessened until the rocket reached its apex, when the rocket stopped moving and the thrust force disappeared. Once the thrust force disappeared, the rocket began falling back to earth!”

Example Response:
“This is incorrect because as soon as the fuel runs out there is no longer a thrust force acting on the rocket. After the fuel runs out the only force acting on the rocket is the force of gravity which will slow down the rocket until its velocity is zero and then the rocket will continue accelerating downward and fall to the earth.”

Question 2:
“Make a counter claim to the following statement from someone who is an “Aristotelian”:The reason that the rocket descended back to earth is because the rocket is heavier than air and so the force from gravity was greater than any air resistance force on the parachute, thus resulting in the rocket falling back to earth.”

Example Response:
“Actually, the reason the rocket descended to earth is because the forces of gravity and drag were equal. The rocket was falling at terminal velocity, and we know that when an object is traveling at a constant velocity there is no acceleration. If the force of gravity working on the rocket was greater, the rocket would be accelerating in its descent. Knowing that the rocket falls in this way, we can conclude that the forces of gravity and drag working on the parachute were equal.”

Conclusion

I am very pleased by the students’ performances on this assessment, and many of the students enjoyed the process and appreciated the opportunity to connect their learning and demonstrate their knowledge and skill. I feel that there is much to consider for the next time I do this kind of assessment, which will be at the end of the spring semester.

One area I can quickly see I need to help the students develop is making connections to data more explicit. Most students would justify their arguments by stating that a certain explanation was evident. I need to help them develop the skill of presenting evidence more clearly and then linking their arguments to the actual evidence. This was an implicit practice, but it needs to be more explicit.

I hope to hear from you all about how I might perfect this process, and prepare the students to excel on this kind of authentic, problem based assessment.

Thanks!

We Have Lift Off!

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This is a follow up post to Modeling A Rocket’s Journey – A Synthesis where I described how the students in the first year program were engaged in creating a predictive report for their model rockets. I want to emphasize that these model rockets were not kits. Each rocket was designed using 3D CAD software, and each component was either fabricated from raw material, or was created from material that was not intended for use in model rocketry. The only exception to this is the actual rocket motor.

The next step was to launch the rockets and have the altimeter payload collect altitude data.

Launch Conditions – A Bit Soggy

Unfortunately the week of our scheduled launch happened to be a week of some pretty hefty rains. We rescheduled the launch twice before finally accepting the soggy launch conditions. With umbrellas and rain jackets, we trudged out to the baseball diamond and got to work setting up for the launch. We had some minor difficulties in the wet weather, but eventually had a very successful launch day.

Most of the rockets were able to launch and deploy their valuable payload – the Pnut Altimeter.

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The students seemed very excited to finally see the rockets launch, and to see the successful deployment of the parachutes. Although we all got a little wet and muddy, we had a great time!

The Altimeter Data

The altimeters use a small barometric pressure sensor to collect altitude data (the altimeters also contain a small temperature sensor and voltage sensor). The altitude is recorded in feet every .05 seconds. Here is an example of one rocket’s recorded flight data:

altitude_vs_time

https://plot.ly/~stemples/9

The students were then asked to use the data to create a comparative analysis report. I will detail how the assignment was set up and also discuss how the students performed on this assignment. That will be for another post.

I want to also thank Mr. Kainz for his amazing photos that are displayed here.