Students learn that fats found in the foods we eat are not all the same; they discover that physical properties of materials are related to their chemical structures. Provided with several samples of commonly used fats with different chemical properties (olive oil, vegetable oil, shortening, animal fat and butter), student groups build and use simple LEGO MINDSTORMS(TM) NXT robots with temperature and light sensors to determine the melting points of the fat samples. Because of their different chemical structures, these fats exhibit different physical properties, such as melting point and color. This activity uses the fact that fats are opaque when solid and translucent when liquid to determine the melting point of each sample upon being heated. Students heat the samples, and use the robot to determine when samples are melted. They analyze plots of their collected data to compare melting points of the oil samples to look for trends. Discrepancies are correlated to differences in the chemical structure and composition of the fats.

Students investigate the motion of a simple pendulum through direct observation and data collection using Android® devices. First, student groups create pendulums that hang from the classroom ceiling, using Android smartphones or tablets as the bobs, taking advantage of their built-in accelerometers. With the Android devices loaded with the (provided) AccelDataCapture app, groups explore the periodic motion of the pendulums, changing variables (amplitude, mass, length) to see what happens, by visual observation and via the app-generated graphs. Then teams conduct formal experiments to alter one variable while keeping all other parameters constant, performing numerous trials, identifying independent/dependent variables, collecting data and using the simple pendulum equation. Through these experiments, students investigate how pendulums move and the changing forces they experience, better understanding the relationship between a pendulum's motion and its amplitude, length and mass. They analyze the data, either on paper or by importing into a spreadsheet application. As an extension, students may also develop their own algorithms in a provided App Inventor framework in order to automatically note the time of each period.

Students visualize and interact with concepts already learned, specifically algebraic equations and solving for unknown variables. They construct a balancing seesaw system (LEGO® Balance Scale) made from LEGO MINDSTORMS® parts and digital components to mimic a balancing scale. They are given example algebraic equation problems to analyze, configure onto the balance scale, and evaluate by manipulating LEGO pieces and gram masses that represent terms of an equation such as unknown variables, coefficients and integers. Digital light sensors, built into the LEGO Balance Scale, detect any balance or imbalances displayed on the balancing scale. The LEGO Balance Scale interactively issues a digital indication of balance or imbalance within the system. If unbalanced, students continue using the LEGO Balance Scale until they are confident in their understanding of solving algebraic equations. The goal is for students to become confident in solving algebraic equations by fundamentally understanding the basics of algebra and real-world algebraic applications.

Lighting is responsible for nearly one-third of the electricity use in buildings. One of the best ways to conserve energy is to make sure the lights are turned off when no one is in a room. This process can be automated using motion sensors. In this activity, students explore material properties as they relate to motion detection, and use that knowledge to make design judgments about what types of motion detectors to use in specific applications.

Students use ultrasonic sensors and LEGO© MINDSTORMS© NXT robots to emulate how bats use echolocation to detect obstacles. They measure the robot's reaction times as it senses objects at two distances and with different sensor threshold values, and again after making adjustments to optimize its effectiveness. Like engineers, they gather and graph data to analyze a given design (from the tutorial) and make modifications to the sensor placement and/or threshold values in order to improve the robot's performance (iterative design). Students see how problem solving with biomimicry design is directly related to understanding and making observations of nature.

Student teams design their own booms (bridges) and engage in a friendly competition with other teams to test their designs. Each team strives to design a boom that is light, can hold a certain amount of weight, and is affordable to build. Teams are also assessed on how close their design estimations are to the final weight and cost of their boom "construction." This activity teaches students how to simplify the math behind the risk and estimation process that takes place at every engineering firm prior to the bidding phase when an engineering firm calculates how much money it will take to build the project and then "bids" against other competitors.

Students learn about the similarities between the human brain and its engineering counterpart, the computer. Since students work with computers routinely, this comparison strengthens their understanding of both how the brain works and how it parallels that of a computer. Students are also introduced to the "stimulus-sensor-coordinator-effector-response" framework for understanding human and robot actions.

Student groups construct simple conductivity probes and then integrate them into two different circuits to test the probe behavior in solutions of varying conductivity (salt water, sugar water, distilled water, tap water). The activity culminates with student-designed experiments that utilize the constructed probes. The focus is to introduce students to the fabrication of the probe and expose them to two different ways to integrate the probe to obtain qualitative and quantitative measurements, while considering the application and utility of a conductivity probe within an engineering context. A provided handout guides teams through the process: background reading and questions; probe fabrication including soldering; probe testing and data gathering (including circuit creation on breadboard); probe connection to Arduino (including circuit creation and code entry) and a second round of testing and data gathering; design and conduct their own lab experiments that use the probes; online electrolyte/nonelectrolyte reading, short video, comprehension check and analysis questions.

Students identify different bridge designs and construction materials used in modern day engineering. They work in construction teams to create paper bridges and spaghetti bridges based on existing bridge designs. Students progressively realize the importance of the structural elements in each bridge. They also measure vertical displacements under the center of the spaghetti bridge span when a load is applied. Vertical deflection is measured using a LEGO MINDSTORMS(TM) NXT intelligent brick and ultrasonic sensor. As they work, students experience tension and compression forces acting on structural elements of the two bridge prototypes. In conclusion, students discuss the material properties of paper and spaghetti and compare bridge designs with performance outcomes.

Students learn the importance of the Pythagorean theorem as applied in radar imaging. They use a sensor unit with IRED (infrared emitting diode) to measure triangle distances and the theorem to calculate and verify distances. Student groups calibrate the sensor units to ensure accurate distance measurements. A "pretend" outdoor radar imaging model is provided to groups for sensor unit testing.

Students continue their exploration of the human senses and their engineering counterparts, focusing on the auditory sense. Working in small groups, students design, create and run programs to control the motion of LEGO® TaskBots. By doing this, they increase their understanding of the use and function of sound sensors, gain experience writing robot programs, and reinforce their understanding of the sensory process.

Students use simple household materials, such as PVC piping and compact mirrors, to construct models of laser-based security systems. The protected object (a "mummified troll" or another treasure of your choosing) is placed "on display" in the center of the modeled room and protected by a laser system that utilizes a laser beam reflected off mirrors to trigger a light trip sensor with alarm.

Students gain a deeper understanding of how sound sensors work through a hands-on design challenge involving LEGO MINDSTORMS(TM) NXT taskbots and sound sensors. Student groups each program a robot computer to use to the sound of hand claps to control the robot's movement. They learn programming skills and logic design in parallel. They experience how robots can take sensor input and use it to make decisions to move and turn, similar to the human sense of hearing. A PowerPoint® presentation and pre/post quizzes are provided.

Student teams design and create LEGO® structures to house and protect temperature sensors. They leave their structures in undisturbed locations for a week, and regularly check and chart the temperatures. This activity engages students in the design and analysis aspects of engineering.

Students' understanding of how robotic ultrasonic sensors work is reinforced in a design challenge involving LEGO MINDSTORMS(TM) NXT robots and ultrasonic sensors. Student groups program their robots to move freely without bumping into obstacles (toy LEGO people). They practice and learn programming skills and logic design in parallel. They see how robots take input from ultrasonic sensors and use it to make decisions to move, resulting in behavior similar to the human sense of sight but through the use of sound sensors, more like echolocation. Students design-test-redesign-retest to achieve successful programs. A PowerPoint® presentation and pre/post quizzes are provided.

Students' understanding of how robotic light sensors work is reinforced in a design challenge involving LEGO MINDSTORMS(TM) NXT robots and light sensors. Working in pairs, students program LEGO robots to follow a flashlight as its light beam moves around. Students practice and learn programming skills and logic design in parallel. They see how robots take input from light sensors and use it to make decisions to move, similar to the human sense of sight. Students also see how they perform the steps of the engineering design process in the course of designing and testing to achieve a successful program. A PowerPoint® presentation and pre/post quizzes are provided.

Students experience haptic (the sense of touch) feedback by using LEGO® MINDSTORMS® NXT robots and touch sensors to emulate touch feedback recognition. With four touch sensors connected to LEGO NXTs, they design sensor attachments that feel physically distinguishable from each another. Then students answer questions and communicate their answers to the NXT by pressing the touch sensor that is associated with the right multiple-choice answer letter. Haptics becomes essential when students must use the NXT sensors to answer the next set of questions without the aid of their vision. This challenges them to rely solely on the tactile feeling of each unique touch sensor attachment that they created in order to choose the correct peripheral slot. Students also learn about real-world applications of haptics technology.

Students learn about the anatomy of the ear and how the ears work as a sound sensor. Ear anatomy parts and structures are explained in detail, as well as how sound is transmitted mechanically and then electrically through them to the brain. Students use LEGO® robots with sound sensors to measure sound intensities, learning how the NXT brick (computer) converts the intensity of sound measured by the sensor input into a number that transmits to a screen. They build on their experiences from the previous activities and establish a rich understanding of the sound sensor and its relationship to the TaskBot's computer.

Students explore materials engineering by modifying the material properties of water. Specifically, they use salt to lower the freezing point of water and test it by making ice cream. Using either a simple thermometer or a mechatronic temperature sensor, students learn about the lower temperature limit at which liquid water can exist such that even if placed in contact with a material much colder than 0 degrees Celsius, liquid water does not get colder than 0 °C. This provides students with an example of how materials can be modified (engineered) to change their equilibrium properties. They observe that when mixed with salt, liquid water's lower temperature limit can be dropped. Using salt-ice mixtures to cool the ice cream mixes to temperatures lower than 0 °C works better than ice alone.

This lesson highlights the similarities between human sensors and their engineering counterparts. Taking this approach enables students to view the human body as a system, that is, from the perspective of an engineer. Humans have recreated most human sensors in robots – eyes, ears and sensors for temperature, touch and smell. The lesson inculdes a PowerPoint file that is programmed to run a Jeopardy-style game as a fun assessment tool.