Students work as physicists to understand centripetal acceleration concepts. They also learn about a good robot design and the accelerometer sensor. They also learn about the relationship between centripetal acceleration and centripetal force governed by the radius between the motor and accelerometer and the amount of mass at the end of the robot's arm. Students graph and analyze data collected from an accelerometer, and learn to design robots with proper weight distribution across the robot for their robotic arms. Upon using a data logging program, they view their own data collected during the activity. By activity end , students understand how a change in radius or mass can affect the data obtained from the accelerometer through the plots generated from the data logging program. More specifically, students learn about the accuracy and precision of the accelerometer measurements from numerous trials.

Students prepare for the associated activity in which they investigate acceleration by collecting acceleration vs. time data using the accelerometer of a sliding Android device. Based on the experimental set-up for the activity, students form hypotheses about the acceleration of the device. Students will investigate how the force on the device changes according to Newton's Second Law. Different types of acceleration, including average, instantaneous and constant acceleration, are introduced. Acceleration and force is described mathematically and in terms of processes and applications.

In the first of two sequential lessons, students create mobile apps that collect data from an Android device's accelerometer and then store that data to a database. This lesson provides practice with MIT's App Inventor software and culminates with students writing their own apps for measuring acceleration. In the second lesson, students are given an app for an Android device, which measures acceleration. They investigate acceleration by collecting acceleration vs. time data using the accelerometer of a sliding Android device. Then they use the data to create velocity vs. time graphs and approximate the maximum velocity of the device.

Students develop an app for an Android device that utilizes its built-in internal sensors, specifically the accelerometer. The goal of this activity is to teach programming design and skills using MIT's App Inventor software (free to download from the Internet) as the vehicle for learning. The activity should be exciting for students who are interested in applying what they learn to writing other applications for Android devices. Students learn the steps of the engineering design process as they identify the problem, develop solutions, select and implement a possible solution, test the solution and redesign, as needed, to accomplish the design requirements.

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 conduct an experiment to study the acceleration of a mobile Android device. During the experiment, they run an application created with MIT's App Inventor that monitors linear acceleration in one-dimension. Students use an acceleration vs. time equation to construct an approximate velocity vs. time graph. Students will understand the relationship between the object's mass and acceleration and how that relates to the force applied to the object, which is Newton's second law of motion.

In this open-ended, hands-on activity that provides practice in engineering data analysis, students are given gait signature metric (GSM) data for known people types (adults and children). Working in teams, they analyze the data and develop models that they believe represent the data. They test their models against similar, but unknown (to the students) data to see how accurate their models are in predicting adult vs. child human subjects given known GSM data. They manipulate and graph data in Excel® to conduct their analyses.

Student teams use sensors—motion detectors and accelerometers—to collect walking gait data from group members. They import their collected position and acceleration data into Excel® for graphing and analysis to discover the relationships between position, velocity and acceleration in the walking gaits. Then they apply their understanding of slopes of secant lines and Riemann sums to generate and graph additional data. These activities provide practice in the data collection and analysis of systems, similar to the work of real-world engineers.

Gait analysis is the study of human motion that can be utilized as biometric information or identification, for medical diagnostics or for comparative biomechanics. In this activity, students observe walking human subjects and then discuss parameters that could be used to characterize walking gaits. They use accelerometers to collect and graph acceleration vs. time data that can help in gait analysis—all part of practicing the engineering data analysis process. Students complete this activity before learning the material presented in the associated lesson.

Students work through an online tutorial on MIT's App Inventor to learn how to create Android applications. Using those skills, they create their own applications and use them to collect data from an Android device accelerometer and store that data to databases. NOTE: Teachers and students must have a working knowledge of basic programming and App Inventor to complete this lesson. This lesson is not an introduction to MIT's App Inventor and is not recommended for use without prior knowledge of App Inventor to produce an end product. This lesson is an application for App Inventor that allows for the storage of persistent data (data that remains in memory even if an app is closed). This required prior knowledge can come from other experiences with the App Inventor. Also, many additional resources are available, such as tutorials from MIT. This lesson could also be used as an enrichment project for students who are self-motivated to learn the App Inventor software.

After students have complete the associated activity to collect and graph acceleration data from walking human subjects, they learn more about gait analysis---the study of human motion, which is used as biometric data for human medical diagnostics and (non-human) comparative biomechanics. They learn about the steps that comprise the universal process of engineering analysis—data collection, data analysis, mathematical modeling and reporting—and consider how these steps could be applied to analyze a person's gait, which prepares them to conduct the second associated activity.