This video segment adapted from Discovering Women profiles Fermilab physicist and Harvard professor Melissa Franklin.

System design is the central topic of this course. We move beyond the methods developed in circuit design (although we shall have interest in those) and consider situations in which the functional behavior of a system is the first object under consideration.

Learn about an important physics experiment that uses an invention that manipulates light in this interactive activity adapted from NASA.

Students obtain a basic understanding of microfluidic devices, how they are developed and their uses in the medical field. After conducting the associated activity, they watch a video clip and learn about flow rate and how this relates to the speed at which medicine takes effect in the body. What they learn contributes to their ongoing objective to answer the challenge question presented in lesson 1 of this unit. They conclude by solving flow rate problems provided on a worksheet.

Students learn about the form and function of the human heart through the dissection of sheep hearts. They learn about the different parts of the heart and are able to identify the anatomical structures and compare them to the all of the structural components of the human heart they learned about in the associated lesson, Heart to Heart.

As students learn about the creation of biodomes, they are introduced to the steps of the engineering design process, including guidelines for brainstorming. Students learn how engineers are involved in the design and construction of biodomes and use brainstorming to come up with ideas for possible biodome designs. This lesson is part of a series of six lessons in which students use their growing understanding of various environments and the engineering design process, to design and create their own model biodome ecosystems.

This article describes a number of creative projects that incorporate art and literacy skills into a science unit on biomes and ecosystems.

IDS.410J Modeling and Assessment for Policy explores how scientific information and quantitative models can be used to inform policy decision-making. Students will develop an understanding of quantitative modeling techniques and their role in the policy process through case studies and interactive activities. The course addresses issues such as analysis of scientific assessment processes, uses of integrated assessment models, public perception of quantitative information, methods for dealing with uncertainties, and design choices in building policy-relevant models. Examples used in this class focus on models and information used in earth system governance.

A collaboration between the National Aeronautics and Space Administration (NASA) and the CK-12 Foundation, this book provides high school mathematics and physics teachers with an introduction to the main principles of modeling and simulation used in science and engineering. An appendix of lesson plans is included.

Students investigate the ways in which ancient technologies six types of simple machines and combinations are used to construct modern buildings. As they work together to solve a design problem (designing and building a modern structure), they brainstorm ideas, decide on a design, and submit it to a design review before acquiring materials to create it (in this case, a mural depicting it). Emphasis is placed on cooperative, creative teamwork and the steps of the engineering design process.

Distributed systems are the backbone of modern society but entail challenges in areas such as complexity and energy-use. Discover distributed systems from first principles, understand the architectures and techniques derived from them and explore examples of current practical use.

This course will provide learners with a fundamental understanding (theoretical and practical foundations) of how cloud, edge, and big data processing systems work and how they address common challenges for distributed systems such as performance, resilience, and scalability.

Modern IT infrastructure is built as distributed systems, an exciting concept that started with the first computers and evolved rapidly into its present form. From online video meetings to internet services, from social media platforms to online games, we all use and interact with distributed systems on a daily basis and increasingly depend on them. Designing and operating such large-scale distributed systems, however, is complex and typically involves making reasonable compromises. There are fundamental technical barriers as well as economic arguments why we cannot make these systems behave as if they were running on a single, perfectly reliable machine.

In this course, learners will be introduced to the essential functional and non-functional concerns of distributed systems and the common problems encountered while designing them, such as consistency, availability, elasticity, and scalability. A variety of practical solutions that have been established in the leading tech industry in recent years will be reviewed. These provide re-usable building blocks to create new large-scale applications. These recent developments, especially around cloud computing, large-scale data processing, distributed machine learning, and other fields are often not reflected in textbooks and are absent from many traditional curricula but are at the heart of this course.

The learning progress is assessed through a variety of different activities including quizzes, design exercises, experiments, and open questions, with peer review of other students’ solutions. In the final project, learners will design a distributed system based on the learners’ own experience and interests and describe the functional and non-functional properties of the system.

What You'll Learn:
Describe the principles of distributed systems.
Contrast distributed systems with other forms of computation (e.g., single machine computation, parallel computing).
Identify applications of distributed systems in science, engineering, business, and home use, and in particular the use of cloud and serverless applications, big data and graph processing applications, interactive and online gaming, etc.
Analyze and design core architectures, components, and techniques in distributed systems.
Solve practical problems related to modern uses of distributed systems.

Students make Moebius strips and use them to demonstrate the interconnectedness of an environment. They explore the natural cycles water, oxygen/carbon dioxide, carbon, nitrogen that exist within the environment.

Small molecules are chemicals that can interact with proteins to affect their functions. Learn about the structure and biological functions of various small molecules like sugar and caffeine. Also featured on the HHMI DVD, Scanning Life's Matrix: Genes, Proteins, and Small Molecules. Available free from HHMI.

Discover what controls how fast tiny molecular motors in our body pull through a single strand of DNA. How hard can the motor pull in a tug of war with the optical tweezers? Discover what helps it pull harder. Do all molecular motors behave the same?

In this activity, students interact with 12 models to observe emergent phenomena as molecules assemble themselves. Investigate the factors that are important to self-assembly, including shape and polarity. Try to assemble a monolayer by "pushing" the molecules to the substrate (it's not easy!). Rotate complex molecules to view their structure. Finally, create your own nanostructures by selecting molecules, adding charges to them, and observing the results of self-assembly.

In this two-part activity, learners use everyday materials to visualize one mole of gas or 22.4 liters of gas. The first activity involves sublimating dry ice in large garbage bag. The second activity uses plastic bottles.

Study the motion of a toy car on a ramp and use motion sensors to digitally graph the position data and then analyze it. Make predictions about what the graphs will look like, and consider what the corresponding velocity graphs would look like.

There is need for a rigorous, quantitative multidisciplinary design methodology that works with the non-quantitative and creative side of the design process in engineering systems. The goal of multidisciplinary systems design optimization is to create advanced and complex engineering systems that must be competitive not only in terms of performance, but also in terms of life-cycle value. The objective of the course is to present tools and methodologies for performing system optimization in a multidisciplinary design context. Focus will be equally strong on all three aspects of the problem: (i) the multidisciplinary character of engineering systems, (ii) design of these complex systems, and (iii) tools for optimization.

This story-based lesson presents information on the early investigation into solar and cosmic X-rays, as well as the scientists working in pursuit of X-ray detection and imaging, that set the stage for a program of space-based astronomy. The lesson is narrated by Dr. Herbert Friedman, and includes information on his work, as well as his childhood, home life, and interests while a college student.

Students are introduced to the field of biomechanics and how the muscular system produces human movement. They learn the importance of the muscular system in our daily lives, why it is important to be able to repair muscular system injuries and how engineering can help.