This lesson explores the similarities between how a human being moves/walks and how a robot moves. This allows students to see the human body as a system, i.e., from the perspective of an engineer. It shows how movement results from (i) decision making, i.e., deciding to walk and move, and (ii) implementing the decision by conveying the decision to the muscle (human) or motor (robot).

The human brain is responsible for all behaviors, thoughts, and experiences described in this textbook. This module provides an introductory overview of the brain, including some basic neuroanatomy, and brief descriptions of the neuroscience methods used to study it.

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.

What does the brain look like? As engineers, how can we look at neural networks without invasive surgery? In this activity, students design and build neuron models based on observations made while viewing neurons through a microscope. The models are used to explain how each structure of the neuron contributes to the overall function. Students share their models with younger students and explain what a neuron is, its function, and how engineers use their understanding of the neuron to make devices to activate neurons.

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 learn about complex networks and how to represent them using graphs. They also learn that graph theory is a useful mathematical tool for studying complex networks in diverse applications of science and engineering, such as neural networks in the brain, biochemical reaction networks in cells, communication networks, such as the internet, and social networks. Topics covered include set theory, defining a graph, as well as defining the degree of a node and the degree distribution of a graph.

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.

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 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.

In this lesson on the brain's neural networks, students investigate the structure and function of the neuron. They discover ways in which engineers apply this knowledge to the development of devices that can activate neurons. After a review of the nervous system specifically its organs, tissue, and specialized cells, called neurons students learn about the parts of the neuron. They explore the cell body, dendrites, axon and axon terminal, and learn how these structures enable neurons to send messages. They learn about the connections between engineering and other fields of study, and the importance of research, as they complete the lesson tasks.

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.

Through six lesson/activity sets, students learn about the functioning of sensors, both human and robotic. In the activities, student groups use LEGO MINDSTORMS(TM) NXT robots and components to study human senses (sight, hearing, smell, taste, touch) in more detail than in previous units in the series. They also learn about the human made rotation, touch, sound, light and ultrasonic sensors. "Stimulus-sensor-coordinator-effector-response" pathways are used to describe the processes as well as similarities between human/animal and robotic equivalent sensory systems. The important concept of sensors converting/transducing signals is emphasized. Through assorted engineering design challenges, students program the LEGO robots to respond to input from various LEGO sensors. The overall framework reinforces the theme of the human body as a system with sensors that is, from an engineering perspective. PowerPoint® presentations, quizzes and worksheets are provided throughout the unit.

Students learn more about how light sensors work, reinforcing their similarities to the human sense of sight. They look at the light sensing process incoming light converted to electrical signals sent to the brain through the human eye anatomy as well as human-made electrical light sensors. A mini-activity, which uses LEGO MINDSTORMS(TM) NXT intelligent bricks and light sensors gives students a chance to investigate how light sensors function in preparation for the associated activity involving the light sensors and taskbots. A PowerPoint® presentation explains stimulus-to-response pathways, sensor fundamentals, and details about the LEGO light sensor, including its two modes of gathering data and what its numerical value readings mean. Students take pre/post quizzes and watch a short online video. 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.

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.

Students are provided with a rigorous background in human "sensors" (including information on the main five senses, sensor anatomies, and nervous system process) and their engineering equivalents, setting the stage for three associated activities involving sound sensors on LEGO® robots. As they learn how robots receive input from sensors, transmit signals and make decisions about how to move, students reinforce their understanding of the human body's sensory process.

Four lessons related to robots and people present students with life sciences concepts related to the human body (including brain, nervous systems and muscles), introduced through engineering devices and subjects (including computers, actuators, electricity and sensors), via hands-on LEGO® robot activities. Students learn what a robot is and how it works, and then the similarities and differences between humans and robots. For instance, in lesson 3 and its activity, the human parts involved in moving and walking are compared with the corresponding robot components so students see various engineering concepts at work in the functioning of the human body. This helps them to see the human body as a system, that is, from the perspective of an engineer. Students learn how movement results from 1) decision making, such as deciding to walk and move, and 2) implementation by conveying decisions to muscles (human) or motors (robot).

Students learn about complex networks and how to use graphs to represent them. They also learn that graph theory is a useful part of mathematics for studying complex networks in diverse applications of science and engineering, including neural networks in the brain, biochemical reaction networks in cells, communication networks, such as the internet, and social networks. Students are also introduced to random processes on networks. An illustrative example shows 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, and demonstrates how scientists and engineers use mathematics and computers to model and simulate random processes on complex networks for the purposes of learning more about our world and creating solutions to improve our health, happiness and safety.