Grades:
6th Grade, 7th Grade, 8th Grade
This lesson integrates technology (microbits), engineering design, and career exploration for middle school students. It encourages hands-on learning and critical thinking through the creation of
Grades:
5th Grade, 6th Grade, 7th Grade, 8th Grade
Students use the engineering design process to plan, create, code, and share a unique, functioning illuminating e-textile sweater using a Circuit Playground Express (CPX).
Grades:
10th Grade, 11th Grade, 12th Grade
This is part 2 of a two-part series. This lesson looks deeper into early electronic encryption tools and how they relate to cryptography today. The tools discussed are: Hebern Rotor Machine, Enigma
Grades:
5th Grade
Students will learn the basics of coding and robotics using EdBlocks programming language to create musical sequences with Edison robots. They will explore the concepts of rhythm, pitch, and tempo
Grades:
Kindergarten, 1st Grade, 2nd Grade
In this lesson, students will be introduced to basic concepts of robotics and coding through hands-on exploration with Edison robots. They will develop foundational skills in sequencing and problem
Grades:
6th Grade, 7th Grade, 8th Grade
This lesson shows how to use VEX IQ robots in your classroom. There are links to the VEX free resources that can be used to help new or experienced robotics teachers.
Grades:
7th Grade
In this lesson, the students will use the Sphero bots and the data they collected in previous lessons to create block-code to navigate a course for the Sphero Bolt to travel. The block code used is
Grades:
7th Grade, 8th Grade, 9th Grade, 10th Grade, 11th Grade, 12th Grade
In this lesson the students will develop the code they previously planned out and will deploy their code to the drone. They will continue the process of reflection and iterative improvement. This is
Grades:
7th Grade, 8th Grade, 9th Grade, 10th Grade, 11th Grade, 12th Grade
In this lesson students will collect data on the performance of their drone. Students will design a systematic process of data collection that will then lead to the development of a predictive model