This activity helps students understand the significance of programming and also how the LEGO MINDSTORMS(TM) NXT robot's sensors assist its movement and make programming easier. Students compare human senses to robot sensors, describing similarities and differences.

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 lesson describes the function and components of the human nervous system. It helps students understand the purpose of our brain, spinal cord, nerves and the five senses. How the nervous system is affected during spaceflight is also discussed in this lesson.

Students learn about the human body's system components, specifically its sensory systems, nervous system and brain, while comparing them to robot system components, such as sensors and computers. The unit's life sciences-to-engineering comparison is accomplished through three lessons and five activities. The important framework of "stimulus-sensor-coordinator-effector-response" is introduced to show how it improves our understanding the cause-effect relationships of both systems. This framework reinforces the theme of the human body as a system from the perspective of an engineer. This unit is the second of a series, intended to follow the Humans Are Like Robots unit.

Vision is the primary sense of many animals and much is known about how vision is processed in the mammalian nervous system. One distinct property of the primary visual cortex is a highly organized pattern of sensitivity to location and orientation of objects in the visual field. But how did we learn this? An important tool is the ability to design experiments to map out the structure and response of a system such as vision. In this activity, students learn about the visual system and then conduct a model experiment to map the visual field response of a Panoptes robot. (In Greek mythology, Argus Panoptes was the "all-seeing" watchman giant with 100 eyes.) A simple activity modification enables a true black box experiment, in which students do not directly observe how the visual system is configured, and must match the input to the output in order to reconstruct the unseen system inside the box.

Building on their understanding of graphs, students are introduced to random processes on networks. They walk through an illustrative example to see how a random process can be used to represent the spread of an infectious disease, such as the flu, on a social network of students. This demonstrates how scientists and engineers use mathematics to model and simulate random processes on complex networks. Topics covered include random processes and modeling disease spread, specifically the SIR (susceptible, infectious, resistant) model.

Students observe and test their reflexes, including the (involuntary) pupillary response and (voluntary) reaction times using their dominant and non-dominant hands, as a way to further explore how reflexes occur in humans. They gain insights into how our bodies react to stimuli, and how some reactions and body movements are controlled automatically, without conscious thought. Using information from the associated lesson about how robots react to situations, including the stimulus-to-response framework, students see how engineers use human reflexes as examples for controls for robots.

Students learn about human reflexes, how our bodies react to stimuli and how some body reactions and movements are controlled automatically, without thinking consciously about the movement or responses. In the associated activity, students explore how reflexes work in the human body by observing an involuntary human reflex and testing their own reaction times using dominant and non-dominant hands. Once students understand the stimulus-to-response framework components as a way to describe human reflexes and reactions in certain situations, they connect this knowledge to how robots can be programmed to conduct similar reactions.

Students continue to build a rigorous background in human sensors and their engineering equivalents by learning about electronic touch, light, sound and ultrasonic sensors that measure physical quantities somewhat like eyes, ears and skin. Specifically, they learn about microphones as one example of sound sensors, how sounds differ (intensity, pitch) and the components of sound waves (wavelength, period, frequency, amplitude). Using microphones connected to computers running (free) Audacity® software, student teams experiment with machine-generated sounds and their own voices and observe the resulting sound waves on the screen, helping them to understand that sounds are waves. Students take pre/post quizzes, complete a worksheet and watch two short online videos about "seeing" sound.

Why do humans have two ears? How do the properties of sound help with directional hearing? Students learn about directional hearing and how our brains determine the direction of sounds by the difference in time between arrival of sound waves at our right and left ears. Student pairs use experimental set-ups that include the headset portions of stethoscopes to investigate directional hearing by testing each other's ability to identify the direction from which sounds originate.

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.

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.

This activity helps students understand how a LEGO MINDSTORMS(TM) NXT robot moves using motors and wheels. Then students relate the concepts of decision-making actuation and motion in humans to their parallels in mechanized robots, and understand the common themes associated with movement.

Students learn about electric motors and rotational sensors. They learn that motors convert electrical energy to mechanical energy and typically include rotational sensors to enable distance measuring. They also learn the basics about gear trains and gear ratios. Students create a basic program using the LEGO MINDSTORMS(TM) NXT interface to control a motor to move a small robot. Then, through a 10-minute mini-activity, they make measurements and observations to test a LEGO rotation sensor's ability to measure distance in rotations. This prepares them for the associated activity during which they calculate how many wheel rotations are needed to travel a distance. A PowerPoint® presentation, worksheet and pre/post quizzes are provided.

Students gain a rigorous background in the primary human "sensors," as preparation for comparing them to some electronic equivalents in the associated activity. A review of human vision, hearing, smell, taste and touch, including the anatomies and operational principles, is delivered through a PowerPoint® presentation. Students learn the concept of "stimulus-sensor-coordinator-effector-response" to describe the human and electronic sensory processes. Student pairs use blindfolds, paper towels and small candies in a taste/smell sensory exercise. They take pre/post quizzes and watch two short online videos. Concepts are further strengthened by conducting the associated activity the following day, during which they learn about electronic touch, light, sound and ultrasonic sensors and then "see" sound waves while using microphones connected to computers running (free) Audacity® software.

Student teams act as engineers and learn about systems thinking and scale by reassembling the separated pages of the engaging picture book, “Zoom,” by Istvan Banyai. The book is a series of 31 wordless pictures that start very close-up and then zoom out—from a rooster’s comb to outer space. Like a movie camera, each subsequent page pulls back to reveal the context of the previous scene as something different than what you originally thought. When the 31 un-numbered pages are jumbled, it is a surprising challenge for teams to figure out how the pictures connect. The task prompts students to pause and look closer so as to adjust to new points of view and problem solve to find a logical sequence. It requires them to step back and take a broader view. Students learn that engineers work together as teams and look at things very closely so that they see different things and come up with more than one solution when problem solving. To conclude, students go outside and practice their skills by imagining and then drawing their own Zoom-like small booklet stories inspired by items found in nature. The classic duck/rabbit ambiguous drawing is provided as a kickoff visual aid.