In this activity, students will learn to define variables that can be used to reference values and expressions. Once defined, their variables can be used repeatedly throughout a program as substitutes for the original values or expressions.

Modeling the movement of agents, whether they are people, molecules, cars or ideas, is an important part of modeling systems. Different agents will have different movement patterns and varying amount of randomness in their “walks.” The amount of randomness in a walk can have impact on systems.

In this activity, students will learn the mathematical foundation for randomness in walks through a series of activities. The first activity is a table top activity using dice and establishing probabilities of different outcomes. In the second activity, this probability is linked to programming the movement of agents in a simulated world. The final activity is to make a simple model in which the movement of the agent has impact on the state of the environment. Data is collected from runs of the model and analyzed to measure the impact of movement types. For details, see the Dice and Data Instructions, below.

Scientists who are working to discover new medicines often use robots to prepare samples of cells, allowing them to test chemicals to identify those that might be used to treat diseases. Students will meet a scientist who works to identify new medicines. She created free software that ''looks'' at images of cells and determines which images show cells that have responded to the potential medicines. Students will learn about how this technology is currently enabling research to identify new antibiotics to treat tuberculosis. Students will complete hands-on activities that demonstrate how new medicines can be discovered using robots and computer software, starring the student as ''the computer.'' In the process, the students learn about experimental design, including positive and negative controls.

Scientists who are working to discover new medicines often use robots to prepare samples of cells, allowing them to test chemicals to identify those that might be used to treat diseases. Students will meet a scientist who works to identify new medicines. She created free software that ''looks'' at images of cells and determines which images show cells that have responded to the potential medicines. Students will learn about how this technology is currently enabling research to identify new antibiotics to treat tuberculosis. Students will complete hands-on activities that demonstrate how new medicines can be discovered using robots and computer software, starring the student as ''the computer.'' In the process, the students learn about experimental design, including positive and negative controls.

The course addresses dynamic systems, i.e., systems that evolve with time. Typically these systems have inputs and outputs; it is of interest to understand how the input affects the output (or, vice-versa, what inputs should be given to generate a desired output). In particular, we will concentrate on systems that can be modeled by Ordinary Differential Equations (ODEs), and that satisfy certain linearity and time-invariance conditions. We will analyze the response of these systems to inputs and initial conditions. It is of particular interest to analyze systems obtained as interconnections (e.g., feedback) of two or more other systems. We will learn how to design (control) systems that ensure desirable properties (e.g., stability, performance) of the interconnection with a given dynamic system.

Treatment of electromechanical transducers, rotating and linear electric machines. Lumped-parameter electromechanics of interaction. Development of device characteristics: energy conversion density, efficiency; and of system interaction characteristics: regulation, stability, controllability, and response. Use of electric machines in drive systems. Problems taken from current research. This course explores concepts in electromechanics, using electric machinery as examples. It teaches an understanding of principles and analysis of electromechanical systems. By the end of the course, students are capable of doing electromechanical design of the major classes of rotating and linear electric machines and have an understanding of the principles of the energy conversion parts of Mechatronics. In addition to design, students learn how to estimate the dynamic parameters of electric machines and understand what the implications of those parameters are on the performance of systems incorporating those machines.

Students are introduced to the concepts of digital organisms and digital evolution. They learn about the research that digital evolution software makes possible, and compare and contrast it with biological evolution.

MIT App Inventor is an intuitive, visual programming environment that allows everyone – even children – to build fully functional apps for smartphones and tablets.

Exploring Computer Science is a yearlong course developed around a framework of both computer science content and computational practice. Assignments and instruction are contextualized to be socially relevant and meaningful for diverse students. Units utilize a variety of tools/platforms and culminate with final projects around Human-Computer Interaction, Problem Solving, Web Design (HTML, CSS), Programming (Scratch, Edware), Computing & Data Analysis, and Robotics. ECS is recognized nationally as a preparatory course for AP Computer Science Principles. Watch this video and view this fact sheet for more information.

Students plan their final working session together, then work in their project groups to make final changes, test their projects, and check their project against the design requirements.
Students reflect on what they want people to understand when they view their cities.

Students design and create flow charts for the MIT App Inventor tutorials in this computer science activity about program analysis. In program analysis, which is based on determining the behavior of computer programs, flow charts are an important tool for tracing control flow. Control flow is a graphical representation of the logic present in a program and how the program works. Students work through tutorials, design and create flow charts about how the tutorials function, and present their findings to the class. In their final assessment, they create an additional flow chart for an advanced App Inventor tutorial. This activity prepares students with the knowledge and skills to use App Inventor in the future to design and create Android applications.

Inspired by the work of the architect Antoni Gaudi, this research workshop will explore three-dimensional problems in the static equilibrium of structural systems. Through an interdisciplinary collaboration between computer science and architecture, we will develop design tools for determining the form of three-dimensional structural systems under a variety of loads. The goal of the workshop is to develop real-time design and analysis tools which will be useful to architects and engineers in the form-finding of efficient three-dimensional structural systems.

This course will provide a gentle, yet intense, introduction to programming using Python for highly motivated students with little or no prior experience in programming. The course will focus on planning and organizing programs, as well as the grammar of the Python programming language. The course is designed to help prepare students for 6.01 Introduction to EECS. 6.01 assumes some knowledge of Python upon entering; the course material for 6.189 has been specially designed to make sure that concepts important to 6.01 are covered. This course is offered during the Independent Activities Period (IAP), which is a special 4-week term at MIT that runs from the first week of January until the end of the month.

The Girls Who Build: Make Your Own Wearables workshop for high school girls is an introduction to computer science, electrical and mechanical engineering through wearable technology. The workshop, developed by MIT Lincoln Laboratory, consists of two major hands-on projects in manufacturing and wearable electronics. These include 3D printing jewelry and laser cutting a purse, as well as programming LEDs to light up when walking. Participants learn the design process, 3D computer modeling, and machine shop tools, in addition to writing code and building a circuit.

Slide deck to help educators integrate Grades 3-5 core content standards, Michigan K-12 Computer Science Standards and MITECS (Michigan Integrated Technology Competencies for Students).

Video on how to the use K-2 Crosswalk slide deck along with exploring ways to make connections between computer science and grade level curriculum content.

Slide deck to help educators integrate Grades 6-8 core content standards, Michigan K-12 Computer Science Standards and MITECS (Michigan Integrated Technology Competencies for Students).

Video on how to the use 6-8 Crosswalk slide deck along with exploring ways to make connections between computer science and grade level curriculum content.

Slide deck to help educators integrate Grades K-2 core content standards, Michigan K-12 Computer Science Standards and MITECS (Michigan Integrated Technology Competencies for Students).

Video on how to the use K-2 Crosswalk slide deck along with exploring ways to make connections between computer science and grade level curriculum content.