The technology innovations in use in the agriculture industry have been touted as second only to those of the US military. What are these innovations? GPS guided tractors, follow-along equipment, application of fertilizer or herbicide only where needed, variable rate planting, artificial intelligence that can identify weeds and spray them individually—these are just a few of these innovations. This unit illustrates how ozobots can be used to simulate one of these advances. This unit features 4 lessons and 7 files. Lessons are aligned to NGSS.

Students use a hurricane tracking map to measure the distance from a specific latitude and longitude location of the eye of a hurricane to a city. Then they use the map's scale factor to convert the distance to miles. They also apply the distance formula by creating an x-y coordinate plane on the map. Students are challenged to analyze what data might be used by computer science engineers to write code that generates hurricane tracking models. Then students analyze a MATLAB® computer code that uses the distance formula repetitively to generate a table of data that tracks a hurricane at specific time intervals. Students come to realize that using a computer program to generate the calculations (instead of by hand) is very advantageous for a dynamic situation like tracking storm movements. Their inspection of some MATLAB code helps them understand how it communicates what to do using mathematical formulas, logical instructions and repeated tasks. They also conclude that the example program is too simplistic to really be a useful tool; useful computer model tools must necessarily be much more complex.

Students learn how to program using loops and switches. They see how loops enable us to easily and efficiently tell a computer to keep repeating an operation. They also see that switches permit programs to follow different instructions based on whether or not preconditions are fulfilled. Using the LEGO MINDSTORMS(TM) NXT robots, sensors and software, student pairs perform three mini programming activities using loops and switches individually, and then combined. With practice, they incorporate these tools into their programming skill sets in preparation for the associated activity. A PowerPoint® presentation, pre/post quizzes and worksheet are provided.

Building on the programming basics learned so far in the unit, students next learn how to program using sensors rather than by specifying exact durations. They start with an examination of algorithms and move to an understanding of conditional commands (until, then), which require the use of wait blocks. Working with the LEGO MINDSTORMS(TM) NXT robots and software, they learn about wait blocks and how to use them in conjunction with move blocks set with unlimited duration. To help with comprehension and prepare them for the associated activity programming challenges, volunteer students act out a maze demo and student groups conclude by programming LEGO robots to navigate a simple maze using wait block programming. A PowerPoint® presentation, a worksheet and pre/post quizzes are provided.

Students learn about how sound sensors work, reinforcing their similarities to the human sense of hearing. They look at the hearing process sound waves converted to electrical signals sent to the brain through human ear anatomy as well as sound sensors. A mini-activity, which uses LEGO MINDSTORMS(TM) NXT intelligent bricks and sound sensors gives students a chance to experiment with the sound sensors in preparation for the associated activity involving the sound sensors and taskbots. A PowerPoint® presentation explains stimulus-to-response pathways, sensor fundamentals, the unit of decibels, and details about the LEGO sound sensor, including how readings are displayed and its three modes of programming sound input. Students take pre/post quizzes and watch a short online video. This lesson and its associated activity enable students to appreciate how robots can take sensor input and use it to make decisions to via programming.

Students learn about how touch sensors work, while reinforcing their similarities to the human sense of touch. They look at human senses and their electronic imitators, with special focus on the nervous system, skin and touch sensors. A PowerPoint® presentation explains stimulus-to-response pathways, how touch sensors are made and work, and then gives students a chance to handle and get familiar with the LEGO touch sensor, including programming LEGO MINDSTORMS(TM) NXT robots to use touch sensor input to play music. Students take pre/post quizzes and watch a short online video. The mini-activities prepare students for the associated activity. This lesson and its associated activity enables students to appreciate how robots can take input from sensors, and use that to make decisions to move.

Students learn about how ultrasonic sensors work, reinforcing the connection between this sensor and how humans, bats and dolphins estimate distance. They learn the echolocation process sound waves transmitted, bounced back and received, with the time difference used to calculate the distance of objects. Two mini-activities, which use LEGO MINDSTORMS(TM) NXT robots and ultrasonic sensors, give students a chance to experiment with ultrasonic sensors in preparation for the associated activity. A PowerPoint® presentation explains stimulus-to-response pathways, sensor fundamentals, and details about the LEGO ultrasonic sensor. Pre/post quizzes are provided. This lesson and its associated activity enable students to gain a deeper understanding of how robots can take sensor input and use it to make decisions via programming.

In this video segment adapted from ZOOM, cast members enter the FIRST LEGO League Challenge tournament and work as a team to program their LEGO robot to navigate a complex obstacle course. [6:01]

Student groups are challenged to program robots with light sensors to follow a black line. Learning both the logic and skills behind programming robots for this challenge helps students improve their understanding of how robots "think" and widens their appreciation for the complexity involved in programming LEGO® MINDSTORMS® NXT robots to do what appears to be a simple task. They test their ideas for approaches to solve the problem and ultimately learn a (provided) working programming solution. They think of real-world applications for line-follower robots that use sensor input. A PowerPoint® presentation and pre/post quizzes are provided.

Students are challenged to design and program Arduino-controlled robots that behave like simple versions of the automated guided vehicles engineers design for real-world applications. Using Arduino microcontroller boards, infrared (IR) sensors, servomotors, attachable wheels and plastic containers (for the robot frame), they make "Lunch-Bots." Teams program the robots to meet the project constraints—to follow a line of reflective tape, make turns and stop at a designated spot to deliver a package, such as a sandwich or pizza slice. They read and interpret analog voltages from IR sensors, compare how infrared reflects differently off different materials, and write Arduino programs that use IR sensor inputs to control the servomotors. Through the process, students experience the entire engineering design process. Pre/post-quizzes and coding help documents are provided.

Based on their experience exploring the Mars rover Curiosity and learning about what engineers must go through to develop a vehicle like Curiosity, students create Android apps that can control LEGO MINDSTORMS(TM) NXT robots, simulating the difficulties the Curiosity rover could encounter. The activity goal is to teach students programming design and programming skills using MIT's App Inventor software as the vehicle for the learning. The (free to download) App Inventor program enables Android apps to be created using building blocks without having to actually know a programming language. At activity end, students are ready to apply what they learn to write other applications for Android devices.

As part of a design challenge, students learn how to use a rotation sensor (located inside the casing of a LEGO® MINDSTORMS ® NXT motor) to measure how far a robot moves with each rotation. Through experimentation and measurement with the sensor, student pairs determine the relationship between the number of rotations of the robot's wheels and the distance traveled by the robot. Then they use this ratio to program LEGO robots to move precise distances in a contest of accuracy. The robot that gets closest to the goal without touching the toy figures at the finish line is the winning programming design. Students learn how rotational sensors measure distance, how mathematics can be used for real-world purposes, and about potential sources of error due to gearing when using rotation sensor readings for distance calculations. They also become familiar with the engineering design process as they engage in its steps, from understanding the problem to multiple test/improve iterations to successful design.

As the first engineering design challenge of the unit, students are introduced to the logic for solving a maze. First they observe a blindfolded student volunteer being guided through a classroom maze by the simple verbal instructions of another student. In this demonstration, the blindfolded student represents a robot and the guiding student represents programming commands. Then student groups apply that logic to program LEGO MINDSTORMS(TM) NXT robots to navigate through a maze, first with no sensors, and then with sensors. A PowerPoint® presentation, pre/post quizzes and a worksheet are provided.

Students work as engineers to learn about the properties of molecules and how they move in 3D space through the use of LEGO MINDSTORMS(TM) NXT robotics. They design and build molecular models and use different robotic sensors to control the movement of the molecular simulations. Students learn about the size of atoms, Newman projections, and the relationship of energy and strain on atoms. This unique modular modeling activity is especially helpful in providing students with a spatial and tactile understanding of how molecules behave.

Students design, build and evaluate a spring-powered mouse trap racer. For evaluation, teams equip their racers with an intelligent brick from a LEGO© MINDSTORMS© NXT Education Base Set and a HiTechnic© acceleration sensor. They use acceleration data collected during the launch to compute velocity and displacement vs. time graphs. In the process, students learn about the importance of fitting mathematical models to measurements of physical quantities, reinforce their knowledge of Newtonian mechanics, deal with design compromises, learn about data acquisition and logging, and carry out collaborative assessment of results from all participating teams.

Students' understanding of how robotic touch sensors work is reinforced through a hands-on design challenge involving LEGO MINDSTORMS(TM) NXT intelligent bricks, motors and touch sensors. They learn programming skills and logic design in parallel as they program robot computers to play sounds and rotate a wheel when a touch sensor is pressed, and then produce different responses if a different touch sensor is activated. Students see first-hand how robots can take input from sensors and use it to make decisions to move as programmed, including simultaneously moving a motor and playing music. A PowerPoint® presentation and pre/post quizzes are provided.

This activity helps students understand how a motor in a LEGO MINDSTORMS(TM) NXT robot uses electricity produced by the battery to move a robot to do useful work in the form of throwing a ball. Students relate the concepts of electricity and battery to the movement of the LEGO NXT motor and connected links.

Using new knowledge acquired in the associated lesson, students program LEGO MINDSTORMS(TM) NXT robots to go through a maze using movement blocks. The maze is created on the classroom floor with cardboard boxes as its walls. Student pairs follow the steps of the engineering design process to brainstorm, design and test programs to success. Through this activity, students understand how to create and test a basic program. A PowerPoint® presentation, pre/post quizzes and worksheet are provided.

Students apply concepts of disease transmission to analyze infection data, either provided or created using Bluetooth-enabled Android devices. This data collection may include several cases, such as small static groups (representing historically rural areas), several roaming students (representing world-travelers), or one large, tightly knit group (representing urban populations). To explore the algorithms to a deeper degree, students may also design their own diseases using the App Inventor framework.