In a simulation of potential future space missions to Europa, one of Jupiter’s moons, student teams are challenged to direct a robot placed in an enclosed maze to search for and find the most “alien life.” The robot is equipped with a camera to send a live feed of its surroundings in the maze. Students control the robot from outside the maze by looking at the live feed on a smartphone and using the robot’s remote control, making a map as they go. The student teams compete as if they are space agencies creating their own exploratory systems to meet the challenge’s criteria and constraints and prove “in the field” that they have the best plan to win the mission contract and get the job. This activity simulates the real-world research of scientists and engineers developing a robot with the capabilities to explore under the ice-covered surface of Europa.

Students learn about probability through a LEGO® MINDSTORMS® NTX-based activity that simulates a game of "rock-paper-scissors." The LEGO robot mimics the outcome of random game scenarios in order to help students gain a better understanding of events that follow real-life random phenomenon, such as bridge failures, weather forecasts and automobile accidents. Students learn to connect keywords such as certainty, probable, unlikely and impossibility to real-world engineering applications.

Students learn about rotary encoders and discover how they operate through hands-on experimentation. Rotary encoders are applied in tools to determine angle measurements and for translations of angular motion. One common rotary encoder application is in a computer's ball-type mouse—the ball itself is a type of rotary encoder. In this activity, students experiment with two rotary encoders, including one from a computer mouse and one created using a LEGO® MINDSTORMS® NXT kit. They collect data to define and graph the relationship between the motion of the rotary encoder and its output.

This content package is a curated collection of STEM instructional resources to support the introduction and exploration of programming and robotics in grades 3-5. Resources include lesson plans, engagement activities, ebooks, digital texts, and videos.

Students develop an understanding of the concepts of "push" and "pull" as they "save" stuffed animals from danger using LEGO MINDSTORMS(TM) NXT robots. After learning more about the concepts through a robot demonstration, students explore the concepts themselves in the context of saving stuffed animala from the table edges. They choose to either push or pull the animal to safety, depending on the orientation of the robot and toy. They see the consequences of their choices, learning the importance of understanding these force concepts and the differences between them.

Students use data acquisition equipment to learn about force and displacement in regard to simple and complex machines. In the engineering world, materials and systems are tested by applying forces and measuring the resulting displacements. The relationship between the force applied on a material, and its resulting displacement, is a distinct property of the material, which is measured in order to evaluate the material for correct use in structures and machines.

Students consider human senses and the many everyday human-made sensors so common in their lives. They learn about the three components of biosensors—a special type of sensor—and their functions and importance. With this understanding, students identify various organs in the human body that behave as sensors, such as the pancreas. Using LEGO® MINDSTORMS® NXT robots, provided rbt robot programs and LEGO sensors (light, ultrasonic, sound, touch), students gain first-hand experience with sensors and come to see how engineer-designed sensors play important roles in our daily lives, informing people of their surroundings and ultimately improving our quality of life.

Students learn about contamination and pollution, specifically in reference to soil in and around rivers. To start, groups use light sensors to take light reflection measurements of different colors of sand (dyed with various amounts of a liquid food dye), generating a set of "soil" calibration data. Then, they use a stream table with a simulated a river that has a scattering of "contaminated wells" represented by locations of unknown amounts of dye. They make visual observations and use light sensors again to take reflection measurements and refer to their earlier calibration data to determine the level of "contamination" (color dye) in each well. Acting as engineers, they determine if their measured data is comparable to visual observations. The small-scale simulated flowing river shows how contamination can spread.

Students use a simple seesaw to visualize solving a two- or three-step mathematics equation, while solving a basic structural engineering weight balance problem in the process. They solve two-step equations on a worksheet and attempt to solve the challenge of "balancing a beam" through hands-on problems. The use of sensor equipment for correct position monitoring aids students in balancing the structure, as well as balancing the equation as they solve it on paper.

Students act as chemical engineers and use LEGO® MINDSTORMS® NXT robotics to record temperatures and learn about the three states of matter. Properties of matter can be measured in various ways, including volume, mass, density and temperature. Students measure the temperature of water in its solid state (ice) as it is melted and then evaporated.

Students generally do not know the complexity that goes into building and programming a robotic arm. In actuality, creating such an arm comes from a design that involves mechanical, electrical, and computer science engineers. This activity allows students to control a robotic arm from both a machine's and a computer science engineer's perspective by letting them perform a simple task with a few entertaining instructions and constraints.

Students apply their knowledge of constructing and programming LEGO MINDSTORMS (TM)NXT robots to create sumobots - strong robots capable of pushing other robots out of a ring. To meet the challenge, groups follow the steps of the engineering design process and consider robot structure, weight and gear ratios in their designs to make their robots push as hard as possible to force robot opponents out of the ring. A class competition serves as the final test to determine the best designed robot, illustrating the interrelationships between designing, building and programming. This activity gives students the opportunity to be creative as well as have fun applying and combining what they have learned through the previous activities and lessons in this and prior units in the series. A PowerPoint (tm) presentation, pre/post quizzes and a worksheet are provided.

Students measure different types of small-sized beams and calculate their respective moments of inertia. They compare the calculations to how much the beams bend when loads are placed on them, gaining insight into the ideal geometry and material for load-bearing beams.

With the challenge to program computers to mimic the human reaction after touching a hot object, students program LEGO® robots to "react" and move back quickly once their touch sensors bump into something. By relating human senses to electronic sensors used in robots, students see the similarities between the human brain and its engineering counterpart, the computer, and come to better understand the functioning of sensors in both applications. They apply an understanding of the human "stimulus-sensor-coordinator-effector-response" framework to logically understand human and robot actions.

Students learn basic concepts of robotic logic and programming by working with Boe-Bot robots—a simple programmable robotic platform designed to illustrate basic robotic concepts. Under the guidance of the instructor and a provided lab manual, student groups build simple circuits and write codes to make their robots perform a variety of tasks, including obstacle and light detection, line following and other motion routines. Eight sub-activities focus on different sensors, including physical sensors, phototransistors and infrared headlights. Students test their newly acquired skills in the final activity, in which they program their robots to navigate an obstacle course.

Students strengthen their communicate skills about measurements by learning the meaning of base units and derived units, including speed one of the most common derived units (distance/time). Working in groups, students measure the time for LEGO MINDSTORMS(TM) NXT robots to move a certain distance. The robots are started and stopped via touch sensors and programmed to display the distance traveled. Using their collected data, students complete a worksheet to calculate the robots' (mean/average) speeds at given motor powers.

Students work as engineers to design and test trebuchets (in this case LEGO® MINDSTORMS® robots) that can launch objects. During the testing stage, they change one variable at a time to study its effect on the outcome of their designs. Specifically, they determine how far objects travel depending on their weights. As students learn about the different components of robot design and the specific function controls, they determine what design features are important for launching objects.

Students are introduced to the concepts of torque, power, friction and gear ratios. Teams modify two robotic LEGO® MINDSTORMS® vehicles by changing their gear ratios, wheel sizes, weight and engine power, while staying within a limit of points to spend on modifications. The robots face each other on a track with a string attaching one to the other. The winning robot, the one with the best adjustments, pulls the other across the line.

Student pairs first act out the instructions a robot is given with one person providing instructions and the other person following the instructions. This activity helps students understand how robots are programmed and with what type of precision commands must be given. Then students program LEGO MINDSTORMS(TM) NXT taskbots to navigate a simple maze. The goal is to teach students that robot computers simply follow directions exactly as they are given, thus one must be very clear and logical with programming instructions.